From a56a8c54a5a848487a3debbdf14a3bfdf7c1ed8e Mon Sep 17 00:00:00 2001 From: fspzar123 <111989473+fspzar123@users.noreply.github.com> Date: Fri, 7 Jun 2024 18:25:27 +0530 Subject: [PATCH 1/2] First Commit --- .../Dataset/README.md | 37 + .../Dataset/economic_calendar_19_24.csv | 1877 +++++++++++ .../Dataset/gold_price_19_24.csv | 1280 ++++++++ .../Dataset/sentiment_labeled_data.csv | 1280 ++++++++ .../Images/Accuracies of Models.png | Bin 0 -> 29773 bytes .../Images/Avg Price by country.png | Bin 0 -> 21705 bytes .../Images/Dist of events per date.png | Bin 0 -> 17982 bytes .../Images/Dist of price by country.png | Bin 0 -> 26021 bytes .../Images/HeatMap Of Correlation.png | Bin 0 -> 53985 bytes .../Images/Trend of Price&Vol_K.png | Bin 0 -> 71749 bytes .../Images/Weekly-Gold.png | Bin 0 -> 83981 bytes .../Model/README.md | 83 + ...ents.out.tfevents.1717589276.Shawn.25944.0 | Bin 0 -> 4900 bytes ...ents.out.tfevents.1717589418.Shawn.25944.1 | Bin 0 -> 4900 bytes ...ents.out.tfevents.1717589834.Shawn.25944.2 | Bin 0 -> 4900 bytes ...ents.out.tfevents.1717589993.Shawn.25944.3 | Bin 0 -> 4900 bytes ...ents.out.tfevents.1717590151.Shawn.25944.4 | Bin 0 -> 4900 bytes .../Model/project_folder.ipynb | 2762 +++++++++++++++++ .../requirements.txt | 5 + 19 files changed, 7324 insertions(+) create mode 100644 The Effect of Economic News on Gold Prices Analysis/Dataset/README.md create mode 100644 The Effect of Economic News on Gold Prices Analysis/Dataset/economic_calendar_19_24.csv create mode 100644 The Effect of Economic News on Gold Prices Analysis/Dataset/gold_price_19_24.csv create mode 100644 The Effect of Economic News on Gold Prices Analysis/Dataset/sentiment_labeled_data.csv create mode 100644 The Effect of Economic News on Gold Prices Analysis/Images/Accuracies of Models.png create mode 100644 The Effect of Economic News on Gold Prices Analysis/Images/Avg Price by country.png create mode 100644 The Effect of Economic News on Gold Prices Analysis/Images/Dist of events per date.png create mode 100644 The Effect of Economic News on Gold Prices Analysis/Images/Dist of price by country.png create mode 100644 The Effect of Economic News on Gold Prices Analysis/Images/HeatMap Of Correlation.png create mode 100644 The Effect of Economic News on Gold Prices Analysis/Images/Trend of Price&Vol_K.png create mode 100644 The Effect of Economic News on Gold Prices Analysis/Images/Weekly-Gold.png create mode 100644 The Effect of Economic News on Gold Prices Analysis/Model/README.md create mode 100644 The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589276.Shawn.25944.0 create mode 100644 The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589418.Shawn.25944.1 create mode 100644 The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589834.Shawn.25944.2 create mode 100644 The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589993.Shawn.25944.3 create mode 100644 The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717590151.Shawn.25944.4 create mode 100644 The Effect of Economic News on Gold Prices Analysis/Model/project_folder.ipynb create mode 100644 The Effect of Economic News on Gold Prices Analysis/requirements.txt diff --git a/The Effect of Economic News on Gold Prices Analysis/Dataset/README.md b/The Effect of Economic News on Gold Prices Analysis/Dataset/README.md new file mode 100644 index 000000000..09e5478d3 --- /dev/null +++ b/The Effect of Economic News on Gold Prices Analysis/Dataset/README.md @@ -0,0 +1,37 @@ +# About Dataset +Explore the intricate dance between gold prices and key economic events across major global players – Canada, Japan, USA, Russia, European Union, and China. This comprehensive dataset spans from January 2019 to December 2023, offering a nuanced analysis of how economic news from these influential regions impacts the ever-volatile gold market. Delve into the ebb and flow of financial landscapes, uncovering trends, correlations, and invaluable insights for strategic decision-making in the dynamic world of investments. + +## Historical Gold Price Dataset: + +* Day: The day of the week when the data was recorded. +* Date: The specific date corresponding to the recorded gold price. +* Hour: The time of day when the gold price was recorded. +* Country: The country associated with the economic event or news affecting gold prices. +* Event: The economic event or news that potentially influenced gold prices. +* Actual: The actual reported value or figure related to the economic event. +* Previous: The previously reported value or figure for the same economic event. +* Consensus: The consensus forecast or expected value for the economic event. +* Forecast: The forecasted value or figure for the economic event. + +## Economic Calendar Dataset: + +* Day: The day of the week when the economic event is scheduled. +* Date: The specific date when the economic event is expected to occur. +* Hour: The time of day when the economic event is scheduled. +* Country: The country associated with the economic event. +* Event: The specific economic event or news scheduled to take place. +* Actual: The actual reported value or figure related to the economic event. +* Previous: The previously reported value or figure for the same economic event. +* Consensus: The consensus forecast or expected value for the economic event. +* Forecast: The forecasted value or figure for the economic event. + +## Sentiment Labeled Data: +* Date: The specific date when the economic event is expected to occur +* Price: The price of Gold in Dollars(US) on that particular Date. +* Vol_K: Volume of the Gold traded. +* Change_percent: The percentage of change in the Previous and Actual +* Country: The country associated with the economic event +* Event: The specific economic event or news scheduled to take place. +* D_Consensus: The difference in the Previous Consensus and Actual Consensus. +* D_Forecast: The difference in the Previous Forecast and Actual Forecast. +* Sentiment: The Sentiment (Positive, Negative, Neutral) assigned to the event based on the Change_Percent. \ No newline at end of file diff --git a/The Effect of Economic News on Gold Prices Analysis/Dataset/economic_calendar_19_24.csv b/The Effect of Economic News on Gold Prices Analysis/Dataset/economic_calendar_19_24.csv new file mode 100644 index 000000000..4c7684b9e --- /dev/null +++ b/The Effect of Economic News on Gold Prices Analysis/Dataset/economic_calendar_19_24.csv @@ -0,0 +1,1877 @@ +Day,Date,Hour,Country,Event,Actual,Previous,Consensus,Forecast +Tuesday,01/01/19,20:45,CN,Caixin Manufacturing PMI DEC,49.7,50.2,50.1,50.1 +Friday,01/04/19,8:30,US,Non Farm Payrolls DEC,312K,176K,177K,165K +Sunday,01/06/19,,CN,US-China Trade Talks,,,, +Monday,01/07/19,10:00,CA,Ivey PMI s.a DEC,59.7,57.2,56.8,56.7 +Monday,01/07/19,,CN,US-China Trade Talks,,,, +Tuesday,01/08/19,0:00,JP,Consumer Confidence DEC,42.7,42.9,,42 +Tuesday,01/08/19,5:00,EA,Business Confidence DEC,0.82,1.04,0.99,1.1 +Tuesday,01/08/19,8:30,CA,Balance of Trade NOV,-2.06B,-0.85B,-1.95B, +Wednesday,01/09/19,20:30,CN,Inflation Rate YoY DEC,0.019,2.20%,0.021,0.022 +Friday,01/11/19,4:30,GB,Balance of Trade NOV,-2.904B,-3.037B,, -2.2B +Friday,01/11/19,8:30,US,Core Inflation Rate YoY DEC,0.022,2.20%,0.022,0.022 +Friday,01/11/19,8:30,US,Inflation Rate YoY DEC,0.019,2.20%,0.019,0.022 +Wednesday,01/16/19,4:30,GB,Inflation Rate YoY DEC,0.021,2.30%,0.021,0.022 +Thursday,01/17/19,18:30,JP,Inflation Rate YoY DEC,0.003,0.80%,0.003,0.006 +Friday,01/18/19,8:30,CA,Inflation Rate YoY DEC,0.02,1.70%,0.017,0.017 +Tuesday,01/22/19,4:30,GB,Claimant Count Change DEC,20.8K,24.8K,20K,10K +Tuesday,01/22/19,18:50,JP,Balance of Trade DEC,-55B,-738B,-29.5B,-25B +Wednesday,01/30/19,0:00,JP,Consumer Confidence JAN,41.9,42.7,42.5,42.4 +Wednesday,01/30/19,5:00,EA,Business Confidence JAN,0.69,0.86,0.75,0.75 +Wednesday,01/30/19,19:01,GB,Gfk Consumer Confidence JAN,-14,-14,-15,-16 +Wednesday,01/30/19,20:00,CN,NBS Manufacturing PMI JAN,49.5,49.4,49.3,49.8 +Thursday,01/31/19,20:45,CN,Caixin Manufacturing PMI JAN,48.3,49.7,49.5,50 +Friday,02/01/19,8:30,US,Non Farm Payrolls JAN,304K,222K,165K,170K +Wednesday,02/06/19,8:30,US,Balance of Trade NOV,-49.3B,-55.7B,-54B,-53B +Wednesday,02/06/19,10:00,CA,Ivey PMI s.a JAN,54.7,59.7,56,58 +Monday,02/11/19,4:30,GB,Balance of Trade DEC,-3.229B,-3.615B,, -1.9B +Wednesday,02/13/19,4:30,GB,Inflation Rate YoY JAN,0.018,2.10%,0.019,0.02 +Wednesday,02/13/19,8:30,US,Core Inflation Rate YoY JAN,0.022,2.20%,0.021,0.02 +Wednesday,02/13/19,8:30,US,Inflation Rate YoY JAN,0.016,1.90%,0.015,0.019 +Thursday,02/14/19,8:30,US,Retail Sales MoM DEC,-0.012,0.10%,0.002,0.003 +Thursday,02/14/19,20:30,CN,Inflation Rate YoY JAN,0.017,1.90%,0.019,0.019 +Tuesday,02/19/19,4:30,GB,Claimant Count Change JAN,14.2K,20.2K,2.7K,5.1K +Tuesday,02/19/19,18:50,JP,Balance of Trade JAN,-1415B,-57B,-1011B,-1000B +Thursday,02/21/19,8:30,US,Durable Goods Orders MoM DEC,0.012,1%,0.015,0.025 +Thursday,02/21/19,18:30,JP,Inflation Rate YoY JAN,0.002,0.30%,0.002,0.005 +Wednesday,02/27/19,5:00,EA,Business Confidence FEB,0.69,0.69,0.6,0.61 +Wednesday,02/27/19,8:30,CA,Inflation Rate YoY JAN,0.014,2%,0.015,0.018 +Wednesday,02/27/19,19:01,GB,Gfk Consumer Confidence FEB,-13,-14,-15,-17 +Wednesday,02/27/19,20:00,CN,NBS Manufacturing PMI FEB,49.2,49.5,49.5,49.8 +Thursday,02/28/19,20:45,CN,Caixin Manufacturing PMI FEB,49.9,48.3,48.5,49 +Friday,03/01/19,0:00,JP,Consumer Confidence FEB,41.5,41.9,41.6,41.3 +Friday,03/01/19,8:30,US,Personal Income MoM DEC,0.01,0.30%,0.004,0.004 +Friday,03/01/19,8:30,US,Personal Income MoM JAN,-0.001,1%,0.003,0.003 +Friday,03/01/19,8:30,US,Personal Spending MoM DEC,-0.005,0.60%,-0.002,-0.002 +Monday,03/04/19,,CN,National People’s Congress,,,, +Wednesday,03/06/19,8:30,CA,Balance of Trade DEC,-4.59B,-1.98B,-2.8B,-1.7B +Wednesday,03/06/19,8:30,US,Balance of Trade DEC,-59.8B,-50.3B,-57.9B,-56B +Wednesday,03/06/19,10:00,CA,Ivey PMI s.a FEB,50.6,54.7,55.1,53 +Friday,03/08/19,8:30,US,Non Farm Payrolls FEB,20K,311K,180K,190K +Friday,03/08/19,20:30,CN,Inflation Rate YoY FEB,0.015,1.70%,0.015,0.016 +Monday,03/11/19,7:30,US,Retail Sales MoM JAN,0.002,-1.60%,0,0.003 +Tuesday,03/12/19,4:30,GB,Balance of Trade JAN,-3.825B,-3.448B,-3.5B,-2.6B +Tuesday,03/12/19,7:30,US,Core Inflation Rate YoY FEB,0.021,2.20%,0.022,0.022 +Tuesday,03/12/19,7:30,US,Inflation Rate YoY FEB,0.015,1.60%,0.016,0.016 +Wednesday,03/13/19,7:30,US,Durable Goods Orders MoM JAN,0.004,1.30%,-0.005,-0.009 +Sunday,03/17/19,18:50,JP,Balance of Trade FEB,339B,-1416B,310.2B,-200B +Tuesday,03/19/19,4:20,GB,Claimant Count Change FEB,27K,15.7K,2.7K,9.1K +Wednesday,03/20/19,4:30,GB,Inflation Rate YoY FEB,0.019,1.80%,0.018,0.018 +Thursday,03/21/19,18:30,JP,Inflation Rate YoY FEB,0.002,0.20%,0.003,0.001 +Friday,03/22/19,7:30,CA,Inflation Rate YoY FEB,0.015,1.40%,0.014,0.015 +Wednesday,03/27/19,7:30,CA,Balance of Trade JAN,-4.25B,-4.82B,-3.5B,-3.9B +Wednesday,03/27/19,7:30,US,Balance of Trade JAN,-51.1B,-59.9B,-57B,-59B +Wednesday,03/27/19,,CN,US-China Trade Talks,,,, +Thursday,03/28/19,5:00,EA,Business Confidence MAR,0.53,0.69,0.66,0.6 +Thursday,03/28/19,19:01,GB,Gfk Consumer Confidence MAR,-13,-13,-14,-13 +Thursday,03/28/19,,CN,US-China Trade Talks,,,, +Friday,03/29/19,7:30,US,Personal Income MoM FEB,0.002,-0.10%,0.003,0.002 +Friday,03/29/19,7:30,US,Personal Spending MoM JAN,0.001,-0.60%,0.003,0.004 +Saturday,03/30/19,20:00,CN,NBS Manufacturing PMI MAR,50.5,49.2,49.5,49.6 +Sunday,03/31/19,18:50,JP,Tankan Large Manufacturers Index Q1,12,19,13,18 +Sunday,03/31/19,20:45,CN,Caixin Manufacturing PMI MAR,50.8,49.9,50.1,49.8 +Monday,04/01/19,7:30,US,Retail Sales MoM FEB,-0.002,0.70%,0.003,0.002 +Tuesday,04/02/19,7:30,US,Durable Goods Orders MoM FEB,-0.016,0.10%,-0.018,-0.007 +Thursday,04/04/19,9:00,CA,Ivey PMI s.a MAR,54.3,50.6,51.1,50.4 +Friday,04/05/19,7:30,US,Non Farm Payrolls MAR,196K,33K,180K,178K +Monday,04/08/19,0:00,JP,Consumer Confidence MAR,40.5,41.5,42.3,42 +Wednesday,04/10/19,3:30,GB,Balance of Trade FEB,-4.860B,-5.345B,,-1.2B +Wednesday,04/10/19,7:30,US,Core Inflation Rate YoY MAR,0.02,2.10%,0.021,0.022 +Wednesday,04/10/19,7:30,US,Inflation Rate YoY MAR,0.019,1.50%,0.018,0.017 +Wednesday,04/10/19,20:30,CN,Inflation Rate YoY MAR,0.023,1.50%,0.023,0.02 +Tuesday,04/16/19,3:30,GB,Claimant Count Change MAR,28.3K,26.7K,20K,5K +Tuesday,04/16/19,18:50,JP,Balance of Trade MAR,529B,335B,372.2B,250B +Wednesday,04/17/19,3:30,GB,Inflation Rate YoY MAR,0.019,1.90%,0.02,0.019 +Wednesday,04/17/19,7:30,CA,Balance of Trade FEB,-2.9B,-3.09B,-3.5B,-3.9B +Wednesday,04/17/19,7:30,CA,Inflation Rate YoY MAR,0.019,1.50%,0.019,0.017 +Wednesday,04/17/19,7:30,US,Balance of Trade FEB,-49.4B,-51.1B,-53.5B,-52.8B +Thursday,04/18/19,7:30,US,Retail Sales MoM MAR,0.016,-0.20%,0.009,0.006 +Thursday,04/18/19,18:30,JP,Inflation Rate YoY MAR,0.005,0.20%,0.005,0.003 +Thursday,04/25/19,7:30,US,Durable Goods Orders MoM MAR,0.027,-1.10%,0.008,0.005 +Monday,04/29/19,4:00,EA,Business Confidence APR,0.42,0.54,0.49,0.51 +Monday,04/29/19,7:30,US,Personal Income MoM MAR,0.001,0.20%,0.004,0.003 +Monday,04/29/19,7:30,US,Personal Spending MoM MAR,0.009,0.10%,0.007,0.005 +Monday,04/29/19,7:30,US,Personal Spending MoM FEB,0.001,0.30%,0.002,0.003 +Monday,04/29/19,18:01,GB,Gfk Consumer Confidence APR,-13,-13,-12,-12 +Monday,04/29/19,20:00,CN,NBS Manufacturing PMI APR,50.1,50.5,50.5,50.8 +Monday,04/29/19,20:45,CN,Caixin Manufacturing PMI APR,50.2,50.8,51,51 +Monday,04/29/19,,CN,US-China Trade Talks,,,, +Monday,04/29/19,7:30,US,Non Farm Payrolls APR,263K,189K,185K,178K +Tuesday,05/07/19,9:00,CA,Ivey PMI s.a APR,55.9,54.3,53,53.5 +Wednesday,05/08/19,20:30,CN,Inflation Rate YoY APR,0.025,2.30%,0.025,0.021 +Thursday,05/09/19,0:00,JP,Consumer Confidence APR,40.4,40.5,40.3,41 +Thursday,05/09/19,7:30,CA,Balance of Trade MAR,-3.21B,-3.42B,-2.45B, -2.3B +Thursday,05/09/19,7:30,US,Balance of Trade MAR,-50B,-49.3B,-50.2B, -50.1B +Thursday,05/09/19,3:30,GB,Balance of Trade MAR,-5.408B,-6.219B,,-2.7B +Thursday,05/09/19,7:30,US,Core Inflation Rate YoY APR,0.021,2%,0.021,0.02 +Thursday,05/09/19,7:30,US,Inflation Rate YoY APR,0.02,1.90%,0.021,0.019 +Tuesday,05/14/19,3:30,GB,Claimant Count Change APR,24.7K,22.6K,24.2K,25K +Wednesday,05/15/19,7:30,CA,Inflation Rate YoY APR,0.02,1.90%,0.02,0.02 +Wednesday,05/15/19,7:30,US,Retail Sales MoM APR,-0.002,1.70%,0.002,0.003 +Tuesday,05/21/19,18:50,JP,Balance of Trade APR,60.4B,527.8B,203.2B,272B +Wednesday,05/22/19,3:30,GB,Inflation Rate YoY APR,0.021,1.90%,0.022,0.018 +Thursday,05/23/19,18:30,JP,Inflation Rate YoY APR,0.009,0.50%,0.009,0.003 +Thursday,05/23/19,7:30,US,Durable Goods Orders MoM APR,-0.021,1.70%,-0.02,-0.017 +Tuesday,05/28/19,4:00,EA,Business Confidence 05,0.3,0.42,0.4,0.36 +Thursday,05/30/19,18:01,GB,Gfk Consumer Confidence 05,-10,-13,-12,-12 +Thursday,05/30/19,20:00,CN,NBS Manufacturing PMI 05,49.4,50.1,49.9,50.2 +Thursday,05/30/19,0:00,JP,Consumer Confidence 05,39.4,40.4,40.6,40.5 +Thursday,05/30/19,7:30,US,Personal Income MoM APR,0.005,0.10%,0.003,0.002 +Thursday,05/30/19,7:30,US,Personal Spending MoM APR,0.003,1.10%,0.002,0.001 +Sunday,06/02/19,20:45,CN,Caixin Manufacturing PMI 05,50.2,50.2,50,50.4 +Thursday,06/06/19,7:30,CA,Balance of Trade APR,-0.97B,-2.34B,-2.8B,-3B +Thursday,06/06/19,7:30,US,Balance of Trade APR,-50.8B,-51.9B,-50.7B,-51.2B +Thursday,06/06/19,9:00,CA,Ivey PMI s.a 05,55.9,55.9,56.7,54.7 +Friday,06/07/19,7:30,US,Non Farm Payrolls 05,75K,224K,185K,190K +Monday,06/10/19,3:30,GB,Balance of Trade APR,-2.740B,-6.151B,,-3.2B +Tuesday,06/11/19,3:30,GB,Claimant Count Change 05,23.2K,19.1K,22.9K,21K +Tuesday,06/11/19,20:30,CN,Inflation Rate YoY 05,0.027,2.50%,0.027,0.025 +Wednesday,06/12/19,7:30,US,Core Inflation Rate YoY 05,0.02,2.10%,0.021,0.021 +Wednesday,06/12/19,7:30,US,Inflation Rate YoY 05,0.018,2%,0.019,0.019 +Friday,06/14/19,7:30,US,Retail Sales MoM 05,0.005,0.30%,0.006,0.006 +Tuesday,06/18/19,18:50,JP,Balance of Trade 05,-967.1B,56.8B,-979.2B,-851B +Wednesday,06/19/19,3:30,GB,Inflation Rate YoY 05,0.02,2.10%,0.02,0.021 +Wednesday,06/19/19,7:30,CA,Inflation Rate YoY 05,0.024,2%,0.021,0.021 +Thursday,06/20/19,18:30,JP,Inflation Rate YoY 05,0.007,0.90%,0.007,0.01 +Wednesday,06/26/19,7:30,US,Durable Goods Orders MoM 05,-0.013,-2.80%,-0.001,0.002 +Thursday,06/27/19,4:00,EA,Business Confidence JUN,0.17,0.3,0.23,0.25 +Thursday,06/27/19,18:01,GB,Gfk Consumer Confidence JUN,-13,-10,-11,-9 +Friday,06/28/19,7:30,US,Personal Income MoM 05,0.005,0.50%,0.003,0.003 +Friday,06/28/19,7:30,US,Personal Spending MoM 05,0.004,0.60%,0.004,0.002 +Saturday,06/29/19,20:00,CN,NBS Manufacturing PMI JUN,49.4,49.4,49.5,49.8 +Sunday,06/30/19,18:50,JP,Tankan Large Manufacturers Index Q2,7,12,9,8 +Sunday,06/30/19,20:45,CN,Caixin Manufacturing PMI JUN,49.4,50.2,50,49.6 +Monday,07/01/19,0:00,JP,Consumer Confidence JUN,38.7,39.4,39.2,40.8 +Wednesday,07/03/19,7:30,CA,Balance of Trade 05,0.76B,-1.08B,-1.5B,-1.3B +Wednesday,07/03/19,7:30,US,Balance of Trade 05,-55.5B,-51.2B,-54B,-54.3B +Friday,07/05/19,7:30,US,Non Farm Payrolls JUN,224K,72K,160K,171K +Friday,07/05/19,9:00,CA,Ivey PMI s.a JUN,52.4,55.9,55,54 +Tuesday,07/09/19,20:30,CN,Inflation Rate YoY JUN,0.027,2.70%,0.027,0.026 +Wednesday,07/10/19,3:30,GB,Balance of Trade 05,-2.324B,-3.716B,,-2.6B +Thursday,07/11/19,7:30,US,Core Inflation Rate YoY JUN,0.021,2%,0.02,0.02 +Thursday,07/11/19,7:30,US,Inflation Rate YoY JUN,0.016,1.80%,0.016,0.017 +Tuesday,07/16/19,3:30,GB,Claimant Count Change JUN,38K,24.5K,22.8K,15K +Tuesday,07/16/19,7:30,US,Retail Sales MoM JUN,0.004,0.40%,0.001,0.004 +Wednesday,07/17/19,3:30,GB,Inflation Rate YoY JUN,0.02,2%,0.02,0.021 +Wednesday,07/17/19,7:30,CA,Inflation Rate YoY JUN,0.02,2.40%,0.02,0.022 +Wednesday,07/17/19,18:50,JP,Balance of Trade JUN,589.5B,-968.3B,420B,510B +Thursday,07/18/19,18:30,JP,Inflation Rate YoY JUN,0.007,0.70%,0.007,0.008 +Thursday,07/25/19,7:30,US,Durable Goods Orders MoM JUN,0.02,-2.30%,0.007,0.007 +Monday,07/29/19,,CN,US-China Trade Talks,,,, +Tuesday,07/30/19,4:00,EA,Business Confidence JUL,-0.12,0.17,0.08,0.08 +Tuesday,07/30/19,7:30,US,Personal Income MoM JUN,0.004,0.40%,0.004,0.003 +Tuesday,07/30/19,7:30,US,Personal Spending MoM JUN,0.003,0.50%,0.003,0.003 +Tuesday,07/30/19,18:01,GB,Gfk Consumer Confidence JUL,-11,-13,-13,-14 +Tuesday,07/30/19,20:00,CN,NBS Manufacturing PMI JUL,49.7,49.4,49.6,49.3 +Tuesday,07/30/19,,CN,US-China Trade Talks,,,, +Wednesday,07/31/19,0:00,JP,Consumer Confidence JUL,37.8,38.7,38.5,41 +Wednesday,07/31/19,20:45,CN,Caixin Manufacturing PMI JUL,49.9,49.4,49.6,49.2 +Friday,08/02/19,7:30,CA,Balance of Trade JUN,0.14B,0.56B,-0.3B,0.3B +Friday,08/02/19,7:30,US,Balance of Trade JUN,-55.2B,-55.3B,-54.6B,-54.7B +Friday,08/02/19,7:30,US,Non Farm Payrolls JUL,164K,193K,164K,160K +Wednesday,08/07/19,9:00,CA,Ivey PMI s.a JUL,54.2,52.4,53,51.8 +Thursday,08/08/19,20:30,CN,Inflation Rate YoY JUL,0.028,2.70%,0.027,0.027 +Friday,08/09/19,3:30,GB,Balance of Trade JUN,1.779B,-2.002B,,-2.9B +Tuesday,08/13/19,3:30,GB,Claimant Count Change JUL,28K,31.4K,32K,12K +Tuesday,08/13/19,7:30,US,Core Inflation Rate YoY JUL,0.022,2.10%,0.021,0.021 +Tuesday,08/13/19,7:30,US,Inflation Rate YoY JUL,0.018,1.60%,0.017,0.017 +Wednesday,08/14/19,3:30,GB,Inflation Rate YoY JUL,0.021,2%,0.019,0.02 +Thursday,08/15/19,7:30,US,Retail Sales MoM JUL,0.007,0.30%,0.003,0.003 +Sunday,08/18/19,18:50,JP,Balance of Trade JUL,-249.6B,589.6B,-200B,-320B +Wednesday,08/21/19,7:30,CA,Inflation Rate YoY JUL,0.02,2%,0.017,0.018 +Thursday,08/22/19,18:30,JP,Inflation Rate YoY JUL,0.005,0.70%,0.005,0.008 +Monday,08/26/19,7:30,US,Durable Goods Orders MoM JUL,0.021,1.80%,0.012,0.008 +Thursday,08/29/19,0:00,JP,Consumer Confidence AUG,37.1,37.8,,37.6 +Thursday,08/29/19,4:00,EA,Business Confidence AUG,0.11,-0.11,0.08,-0.2 +Thursday,08/29/19,18:01,GB,Gfk Consumer Confidence AUG,-14,-11,-12,-12 +Friday,08/30/19,7:30,US,Personal Income MoM JUL,0.001,0.50%,0.003,0.003 +Friday,08/30/19,7:30,US,Personal Spending MoM JUL,0.006,0.30%,0.005,0.004 +Friday,08/30/19,20:00,CN,NBS Manufacturing PMI AUG,49.5,49.7,49.7,49.5 +Sunday,09/01/19,20:45,CN,Caixin Manufacturing PMI AUG,50.4,49.9,49.8,49.8 +Wednesday,09/04/19,7:30,CA,Balance of Trade JUL,-1.12B,-0.06B,-0.4B,-0.1B +Wednesday,09/04/19,7:30,US,Balance of Trade JUL,-54B,-55.5B,-53.5B,-53.4B +Friday,09/06/19,7:30,US,Non Farm Payrolls AUG,130K,159K,158K,151K +Friday,09/06/19,9:00,CA,Ivey PMI s.a AUG,60.6,54.2,53,53.9 +Monday,09/09/19,3:30,GB,Balance of Trade JUL,-0.219B,-0.132B,,-2.3B +Monday,09/09/19,20:30,CN,Inflation Rate YoY AUG,0.028,2.80%,0.026,0.026 +Tuesday,09/10/19,3:30,GB,Claimant Count Change AUG,28.2K,19.8K,30K,16K +Thursday,09/12/19,7:30,US,Core Inflation Rate YoY AUG,0.024,2.20%,0.023,0.022 +Thursday,09/12/19,7:30,US,Inflation Rate YoY AUG,0.017,1.80%,0.018,0.019 +Friday,09/13/19,7:30,US,Retail Sales MoM AUG,0.004,0.80%,0.002,0.004 +Tuesday,09/17/19,18:50,JP,Balance of Trade AUG,-136.3B,-250.7B,-355.9B,-430B +Wednesday,09/18/19,3:30,GB,Inflation Rate YoY AUG,0.017,2.10%,0.019,0.019 +Wednesday,09/18/19,7:30,CA,Inflation Rate YoY AUG,0.019,2%,0.02,0.019 +Thursday,09/19/19,18:30,JP,Inflation Rate YoY AUG,0.003,0.50%,0.006,0.008 +Thursday,09/19/19,20:30,CN,Loan Prime Rate 1Y,0.042,4.25%,,0.0415 +Thursday,09/26/19,18:01,GB,Gfk Consumer Confidence SEP,-12,-14,-14,-14 +Friday,09/27/19,4:00,EA,Business Confidence SEP,-0.22,0.12,0.11,0.19 +Friday,09/27/19,7:30,US,Durable Goods Orders MoM AUG,0.002,2%,-0.01,-0.012 +Friday,09/27/19,7:30,US,Personal Income MoM AUG,0.004,0.10%,0.004,0.003 +Friday,09/27/19,7:30,US,Personal Spending MoM AUG,0.001,0.50%,0.003,0.004 +Sunday,09/29/19,20:00,CN,NBS Manufacturing PMI SEP,49.8,49.5,49.5,49.9 +Sunday,09/29/19,20:45,CN,Caixin Manufacturing PMI SEP,51.4,50.4,50.2,50 +Monday,09/30/19,18:50,JP,Tankan Large Manufacturers Index Q3,5,7,2,1 +Wednesday,10/02/19,0:00,JP,Consumer Confidence SEP,35.6,37.1,,37.3 +Friday,10/04/19,7:30,CA,Balance of Trade AUG,-0.96B,-1.38B,-1B,-0.8B +Friday,10/04/19,7:30,US,Balance of Trade AUG,-54.9B,-54B,-54.5B,-54.3B +Friday,10/04/19,7:30,US,Non Farm Payrolls SEP,136K,168K,145K,165K +Friday,10/04/19,9:00,CA,Ivey PMI s.a SEP,48.7,60.6,54.3,58 +Thursday,10/10/19,3:30,GB,Balance of Trade AUG,-1.546B,-1.681B,,-3.8B +Thursday,10/10/19,7:30,US,Core Inflation Rate YoY SEP,0.024,2.40%,0.024,0.024 +Thursday,10/10/19,7:30,US,Inflation Rate YoY SEP,0.017,1.70%,0.018,0.019 +Monday,10/14/19,20:30,CN,Inflation Rate YoY SEP,0.03,2.80%,0.029,0.029 +Tuesday,10/15/19,3:30,GB,Claimant Count Change SEP,21.1K,16.3K,26.5K,24K +Wednesday,10/16/19,3:30,GB,Inflation Rate YoY SEP,0.017,1.70%,0.018,0.019 +Wednesday,10/16/19,7:30,CA,Inflation Rate YoY SEP,0.019,1.90%,0.021,0.02 +Wednesday,10/16/19,7:30,US,Retail Sales MoM SEP,-0.003,0.60%,0.003,0.003 +Thursday,10/17/19,18:30,JP,Inflation Rate YoY SEP,0.002,0.30%,0.004,0.004 +Sunday,10/20/19,18:50,JP,Balance of Trade SEP,-123B,-143.5B,54B,151B +Sunday,10/20/19,20:30,CN,Loan Prime Rate 1Y,0.042,4.20%,,0.0405 +Thursday,10/24/19,7:30,US,Durable Goods Orders MoM SEP,-0.011,0.30%,-0.008,-0.006 +Wednesday,10/30/19,5:00,EA,Business Confidence OCT,-0.19,-0.23,-0.24,0.14 +Wednesday,10/30/19,19:01,GB,Gfk Consumer Confidence OCT,-14,-12,-13,-16 +Wednesday,10/30/19,20:00,CN,NBS Manufacturing PMI OCT,49.3,49.8,49.8,49.6 +Thursday,10/31/19,0:00,JP,Consumer Confidence OCT,36.2,35.6,35.5,34.9 +Thursday,10/31/19,7:30,US,Personal Income MoM SEP,0.003,0.50%,0.003,0.003 +Thursday,10/31/19,7:30,US,Personal Spending MoM SEP,0.002,0.20%,0.002,0.002 +Thursday,10/31/19,20:45,CN,Caixin Manufacturing PMI OCT,51.7,51.4,51,50.9 +Friday,11/01/19,7:30,US,Non Farm Payrolls OCT,128K,180K,89K,100K +Tuesday,11/05/19,8:30,CA,Balance of Trade SEP,-0.98B,-1.24B,-0.7B, -0.3B +Tuesday,11/05/19,8:30,US,Balance of Trade SEP,-52.5B,-55B,-52.5B,-52.0B +Wednesday,11/06/19,10:00,CA,Ivey PMI s.a OCT,48.2,48.7,0.8,53 +Friday,11/08/19,20:30,CN,Inflation Rate YoY OCT,0.038,3%,0.033,0.03 +Monday,11/11/19,4:30,GB,Balance of Trade SEP,-3.36B,-1.76B,,-2.2B +Tuesday,11/12/19,4:30,GB,Claimant Count Change OCT,33K,13.5K,21.3K,27K +Wednesday,11/13/19,4:30,GB,Inflation Rate YoY OCT,0.015,1.70%,0.016,0.016 +Wednesday,11/13/19,8:30,US,Core Inflation Rate YoY OCT,0.023,2.40%,0.024,0.024 +Wednesday,11/13/19,8:30,US,Inflation Rate YoY OCT,0.018,1.70%,0.017,0.016 +Friday,11/15/19,8:30,US,Retail Sales MoM OCT,0.003,-0.30%,0.002,0.003 +Tuesday,11/19/19,18:50,JP,Balance of Trade OCT,17.3B,-124.8B,301B,219B +Tuesday,11/19/19,20:30,CN,Loan Prime Rate 1Y,0.0415,4.20%,0.042,0.041 +Wednesday,11/20/19,8:30,CA,Inflation Rate YoY OCT,0.019,1.90%,0.019,0.02 +Thursday,11/21/19,18:30,JP,Inflation Rate YoY OCT,0.002,0.20%,0.003,0.004 +Wednesday,11/27/19,8:30,US,Durable Goods Orders MoM OCT,0.006,-1.40%,-0.008,-0.006 +Wednesday,11/27/19,10:00,US,Personal Income MoM OCT,0,0.30%,0.003,0.002 +Wednesday,11/27/19,10:00,US,Personal Spending MoM OCT,0.003,0.20%,0.003,0.002 +Thursday,11/28/19,5:00,EA,Business Confidence NOV,-0.23,-0.2,-0.14,-0.16 +Thursday,11/28/19,19:01,GB,GfK Consumer Confidence NOV,-14,-14,-14,-13 +Friday,11/29/19,0:00,JP,Consumer Confidence NOV,38.7,36.2,35.4,36 +Friday,11/29/19,20:00,CN,NBS Manufacturing PMI NOV,50.2,49.3,49.5,49.8 +Sunday,12/01/19,20:45,CN,Caixin Manufacturing PMI NOV,51.8,51.7,51.4,51.1 +Thursday,12/05/19,8:30,CA,Balance of Trade OCT,-1.08B,-1.23B,-1.37B,-1.4B +Thursday,12/05/19,8:30,US,Balance of Trade OCT,-47.2B,-51.1B,-48.7B, -48.1B +Thursday,12/05/19,10:00,CA,Ivey PMI s.a NOV,60,48.2,53.8,48.6 +Friday,12/06/19,8:30,US,Non Farm Payrolls NOV,266K,156K,180K,175K +Monday,12/09/19,20:30,CN,Inflation Rate YoY NOV,0.045,3.80%,0.042,0.043 +Tuesday,12/10/19,4:30,GB,Balance of Trade OCT,-5.19B,-1.92B,,-3.0B +Wednesday,12/11/19,8:30,US,Core Inflation Rate YoY NOV,0.023,2.30%,0.023,0.023 +Wednesday,12/11/19,8:30,US,Inflation Rate YoY NOV,0.021,1.80%,0.02,0.019 +Thursday,12/12/19,18:50,JP,Tankan Large Manufacturers Index Q4,0,5,2,2 +Friday,12/13/19,8:30,US,Retail Sales MoM NOV,0.002,0.40%,0.005,0.003 +Tuesday,12/17/19,4:30,GB,Claimant Count Change NOV,28.8K,26.4K,24.5K,29K +Tuesday,12/17/19,18:50,JP,Balance of Trade NOV,-82.1B,15.7B,-369B,-620B +Wednesday,12/18/19,4:30,GB,Inflation Rate YoY NOV,0.015,1.50%,0.014,0.014 +Wednesday,12/18/19,8:30,CA,Inflation Rate YoY NOV,0.022,1.90%,0.022,0.021 +Thursday,12/19/19,18:30,JP,Inflation Rate YoY NOV,0.005,0.20%,0.002,0.003 +Thursday,12/19/19,19:01,GB,GfK Consumer Confidence DEC,-11,-14,-14,-12 +Thursday,12/19/19,20:30,CN,Loan Prime Rate 1Y,0.0415,4.15%,,0.0405 +Friday,12/20/19,10:00,US,Personal Income MoM NOV,0.005,0.10%,0.003,0.002 +Friday,12/20/19,10:00,US,Personal Spending MoM NOV,0.004,0.30%,0.004,0.003 +Monday,12/23/19,8:30,US,Durable Goods Orders MoM NOV,-0.02,0.20%,0.015,0.011 +Monday,12/30/19,20:00,CN,NBS Manufacturing PMI DEC,50.2,50.2,50.1,50.3 +Wednesday,01/01/20,20:45,CN,Caixin Manufacturing PMI DEC,51.5,51.8,51.8,52.2 +Friday,01/03/20,14:00,US,FOMC Minutes,,,, +Tuesday,01/07/20,8:30,CA,Balance of Trade NOV,-1.09B,-1.61B,-1.15B, -0.9B +Tuesday,01/07/20,8:30,US,Balance of Trade NOV,-43.1B,-46.9B,-43.8B, -43B +Tuesday,01/07/20,10:00,CA,Ivey PMI s.a DEC,51.9,60,53.8,56 +Wednesday,01/08/20,0:00,JP,Consumer Confidence DEC,39.1,38.7,38,39 +Wednesday,01/08/20,5:00,EA,Business Confidence DEC,-0.25,-0.21,-0.16,-0.1 +Wednesday,01/08/20,20:30,CN,Inflation Rate YoY DEC,0.045,4.50%,0.047,0.047 +Friday,01/10/20,8:30,US,Non Farm Payrolls DEC,145K,256K,164K,165K +Monday,01/13/20,4:30,GB,Balance of Trade NOV,4.03B,-1.34B,,-3.2B +Tuesday,01/14/20,8:30,US,Core Inflation Rate YoY DEC,0.023,2.30%,0.023,0.022 +Tuesday,01/14/20,8:30,US,Inflation Rate YoY DEC,0.023,2.10%,0.023,0.023 +Wednesday,01/15/20,4:30,GB,Inflation Rate YoY DEC,0.013,1.50%,0.015,0.015 +Wednesday,01/15/20,,US,US-China Phase 1 Trade Deal Signature,,,, +Thursday,01/16/20,8:30,US,Retail Sales MoM DEC,0.003,0.30%,0.003,0.003 +Sunday,01/19/20,20:30,CN,Loan Prime Rate 1Y,0.0415,4.15%,,0.0405 +Tuesday,01/21/20,4:30,GB,Claimant Count Change DEC,14.9K,14.9K,22.6K,26K +Wednesday,01/22/20,8:30,CA,Inflation Rate YoY DEC,0.022,2.20%,0.022,0.022 +Wednesday,01/22/20,18:50,JP,Balance of Trade DEC,-152.5B,-85.2B,-150B,-124B +Thursday,01/23/20,18:30,JP,Inflation Rate YoY DEC,0.008,0.50%,0.004,0.005 +Tuesday,01/28/20,8:30,US,Durable Goods Orders MoM DEC,0.024,-3.10%,0.004,0.006 +Wednesday,01/29/20,0:00,JP,Consumer Confidence JAN,39.1,39.1,40.8,40.5 +Wednesday,01/29/20,,US,USMCA Trade Deal Signature,,,, +Thursday,01/30/20,5:00,EA,Business Confidence JAN,-0.23,-0.32,-0.19,-0.18 +Thursday,01/30/20,19:01,GB,Gfk Consumer Confidence JAN,-9,-11,-9,-10 +Thursday,01/30/20,20:00,CN,NBS Manufacturing PMI JAN,50,50.2,50,50 +Friday,01/31/20,8:30,US,Personal Income MoM DEC,0.002,0.40%,0.003,0.004 +Friday,01/31/20,8:30,US,Personal Spending MoM DEC,0.003,0.40%,0.003,0.005 +Friday,01/31/20,18:00,GB,Brexit Deadline,,,, +Sunday,02/02/20,20:45,CN,Caixin Manufacturing PMI JAN,51.1,51.5,51.3,50.5 +Monday,02/03/20,8:10,RU,Full Year GDP Growth 2019,0.013,2.50%,, +Wednesday,02/05/20,8:30,CA,Balance of Trade DEC,-0.4B,-1.2B,-0.61B, -0.8B +Wednesday,02/05/20,8:30,US,Balance of Trade DEC,-48.9B,-43.7B,-48.2B,-49B +Friday,02/07/20,8:30,US,Non Farm Payrolls JAN,225K,147K,160K,148K +Friday,02/07/20,10:00,CA,Ivey PMI s.a JAN,57.3,51.9,53.3,52.3 +Sunday,02/09/20,20:30,CN,Inflation Rate YoY JAN,0.054,4.50%,0.049,0.051 +Tuesday,02/11/20,4:30,GB,Balance of Trade DEC,7.715B,1.821B,,-2.6B +Thursday,02/13/20,8:30,US,Core Inflation Rate YoY JAN,0.023,2.30%,0.022,0.023 +Thursday,02/13/20,8:30,US,Inflation Rate YoY JAN,0.025,2.30%,0.024,0.024 +Friday,02/14/20,8:30,US,Retail Sales MoM JAN,0.003,0.20%,0.003,0.003 +Tuesday,02/18/20,4:30,GB,Claimant Count Change JAN,5.5K,2.6K,22.6K,15K +Tuesday,02/18/20,18:50,JP,Balance of Trade JAN,-1312.6B,-154.6B,-1694.9B,-1723B +Wednesday,02/19/20,4:30,GB,Inflation Rate YoY JAN,0.018,1.30%,0.016,0.014 +Wednesday,02/19/20,8:30,CA,Inflation Rate YoY JAN,0.024,2.20%,0.023,0.023 +Wednesday,02/19/20,20:30,CN,Loan Prime Rate 1Y,0.0405,4.15%,,0.0395 +Thursday,02/20/20,18:30,JP,Inflation Rate YoY JAN,0.007,0.80%,0.007,0.007 +Sunday,02/23/20,,CN,NPC Committee Meeting,,,, +Wednesday,02/26/20,18:00,US,President Trump Speech ,,,, +Thursday,02/27/20,5:00,EA,Business Confidence FEB,-0.04,-0.19,-0.28,-0.27 +Thursday,02/27/20,8:30,US,Durable Goods Orders MoM JAN,-0.002,2.90%,-0.015,-0.02 +Thursday,02/27/20,19:01,GB,Gfk Consumer Confidence FEB,-7,-9,-8,-8 +Friday,02/28/20,8:30,US,Personal Income MoM JAN,0.006,0.10%,0.003,0.003 +Friday,02/28/20,8:30,US,Personal Spending MoM JAN,0.002,0.40%,0.003,0.002 +Friday,02/28/20,20:00,CN,NBS Manufacturing PMI FEB,35.7,50,46,45 +Sunday,03/01/20,20:45,CN,Caixin Manufacturing PMI FEB,40.3,51.1,45.7,46 +Tuesday,03/03/20,0:00,JP,Consumer Confidence FEB,38.4,39.1,40.6,37.7 +Tuesday,03/03/20,11:00,US,Fed Press Conference,,,, +Friday,03/06/20,8:30,CA,Balance of Trade JAN,-1.47B,-0.73B,-0.83B, -0.7B +Friday,03/06/20,8:30,US,Balance of Trade JAN,-45.3B,-48.6B,-46.1B, -45.8B +Friday,03/06/20,8:30,US,Non Farm Payrolls FEB,273K,273K,175K,165K +Friday,03/06/20,10:00,CA,Ivey PMI s.a FEB,54.1,57.3,53.6,56 +Monday,03/09/20,20:30,CN,Inflation Rate YoY FEB,0.052,5.40%,0.052,0.051 +Wednesday,03/11/20,4:00,GB,BoE Press Conference,,,, +Wednesday,03/11/20,4:30,GB,Balance of Trade JAN,4.2B,6.3B,,-3.7B +Wednesday,03/11/20,7:30,GB,Spring Budget 2020,,,, +Wednesday,03/11/20,7:30,US,Core Inflation Rate YoY FEB,0.024,2.30%,0.023,0.023 +Wednesday,03/11/20,7:30,US,Inflation Rate YoY FEB,0.023,2.50%,0.022,0.023 +Wednesday,03/11/20,20:00,US,President Trump Statement on Coronavirus,,,, +Friday,03/13/20,14:00,US,President Trump Statement on Coronavirus,,,, +Sunday,03/15/20,17:30,US,Fed Press Conference,,,, +Tuesday,03/17/20,4:30,GB,Claimant Count Change FEB,17.3K,-0.2K,21.4K,24K +Tuesday,03/17/20,7:30,US,Retail Sales MoM FEB,-0.005,0.60%,0.002,0.001 +Tuesday,03/17/20,18:50,JP,Balance of Trade FEB,1109.8B,-1313.2B,917.2B,915B +Wednesday,03/18/20,7:30,CA,Inflation Rate YoY FEB,0.022,2.40%,0.021,0.022 +Wednesday,03/18/20,8:00,CA,Prime Minister Trudeau Speech ,,,, +Wednesday,03/18/20,18:30,JP,Inflation Rate YoY FEB,0.004,0.70%,0.008,0.005 +Thursday,03/19/20,20:30,CN,Loan Prime Rate 1Y,0.0405,4.05%,,0.0395 +Tuesday,03/24/20,11:00,CA,Parliamentary Debate & Vote on Coronavirus Aid Package,,,, +Wednesday,03/25/20,2:00,GB,Inflation Rate YoY FEB,0.017,1.80%,0.017,0.015 +Wednesday,03/25/20,7:30,US,Durable Goods Orders MoM FEB,0.012,0.10%,-0.008,-0.007 +Friday,03/27/20,7:30,US,Personal Income MoM FEB,0.006,0.60%,0.004,0.003 +Friday,03/27/20,7:30,US,Personal Spending MoM FEB,0.002,0.20%,0.002,0.003 +Monday,03/30/20,4:00,EA,Business Confidence MAR,-0.28,-0.06,-0.05,-0.6 +Monday,03/30/20,18:01,GB,Gfk Consumer Confidence MAR,-9,-7,-15,-16 +Monday,03/30/20,20:00,CN,NBS Manufacturing PMI MAR,52,35.7,45,44.2 +Tuesday,03/31/20,18:50,JP,Tankan Large Manufacturers Index Q1,-8,0,-10,-12 +Tuesday,03/31/20,20:45,CN,Caixin Manufacturing PMI MAR,50.1,40.3,45.5,45.7 +Thursday,04/02/20,7:30,CA,Balance of Trade FEB,-0.98B,-1.66B,-1.87B, -2B +Thursday,04/02/20,7:30,US,Balance of Trade FEB,-39.9B,-45.5B,-40B, -39B +Friday,04/03/20,7:30,US,Non Farm Payrolls MAR,-701K,275K,-100K,-150K +Sunday,04/05/20,18:01,GB,Gfk Consumer Confidence MAR,-34,-9,,-30 +Monday,04/06/20,0:20,JP,Consumer Confidence MAR,30.9,38.4,,36.8 +Tuesday,04/07/20,9:00,CA,Ivey PMI s.a MAR,26,54.1,41,43 +Tuesday,04/07/20,,EA,Eurogroup Meeting,,,, +Thursday,04/09/20,1:00,GB,Balance of Trade FEB,-2.8B,2.4B,,2.2B +Thursday,04/09/20,20:30,CN,Inflation Rate YoY MAR,0.043,5.20%,0.048,0.05 +Thursday,04/09/20,,EA,Eurogroup Meeting,,,, +Friday,04/10/20,7:30,US,Core Inflation Rate YoY MAR,0.021,2.40%,0.023,0.023 +Friday,04/10/20,7:30,US,Inflation Rate YoY MAR,0.015,2.30%,0.016,0.015 +Wednesday,04/15/20,7:30,US,Retail Sales MoM MAR,-0.087,-0.40%,-0.08,-0.065 +Sunday,04/19/20,18:50,JP,Balance of Trade MAR,4.9B,1108.8B,420B, 400B +Sunday,04/19/20,20:30,CN,Loan Prime Rate 1Y,0.0385,4.05%,0.0385,0.0385 +Tuesday,04/21/20,1:00,GB,Claimant Count Change MAR,12.2K,5.9K,175K,272K +Wednesday,04/22/20,1:00,GB,Inflation Rate YoY MAR,0.015,1.70%,0.015,0.013 +Wednesday,04/22/20,7:30,CA,Inflation Rate YoY MAR,0.009,2.20%,0.012,0.015 +Thursday,04/23/20,18:01,GB,Gfk Consumer Confidence APR,-34,-34,-40,-46 +Thursday,04/23/20,18:30,JP,Inflation Rate YoY MAR,0.004,0.40%,,0.002 +Friday,04/24/20,7:30,US,Durable Goods Orders MoM MAR,-0.144,1.10%,-0.119,-0.12 +Wednesday,04/29/20,4:25,EA,Business Confidence APR,-1.81,-0.28,,-1.24 +Wednesday,04/29/20,20:00,CN,NBS Manufacturing PMI APR,50.8,52,51,47.6 +Wednesday,04/29/20,21:45,CN,Caixin Manufacturing PMI APR,49.4,50.1,50.3,47.8 +Thursday,04/30/20,0:00,JP,Consumer Confidence APR,21.6,30.9,,22.3 +Thursday,04/30/20,7:30,US,Personal Income MoM MAR,-0.02,0.60%,-0.015,-0.01 +Thursday,04/30/20,7:30,US,Personal Spending MoM MAR,-0.075,0.20%,-0.05,-0.063 +Tuesday,05/05/20,7:30,CA,Balance of Trade MAR,-1.41B,-0.89B,-2B, -1.5B +Tuesday,05/05/20,7:30,US,Balance of Trade MAR,-44.4B,-39.8B,-44B,-44.2B +Thursday,05/07/20,9:00,CA,Ivey PMI s.a APR,22.8,26,25,20 +Thursday,05/07/20,7:30,US,Non Farm Payrolls APR,-20500K,-870K,-22000K,-21780K +Thursday,05/07/20,20:30,CN,Inflation Rate YoY APR,0.033,4.30%,0.037,0.036 +Tuesday,05/12/20,7:30,US,Core Inflation Rate YoY APR,0.014,2.10%,0.017,0.016 +Tuesday,05/12/20,7:30,US,Inflation Rate YoY APR,0.003,1.50%,0.004,0.005 +Wednesday,05/13/20,1:00,GB,Balance of Trade MAR,-6.7B,-1.5B,,-1.7B +Wednesday,05/13/20,7:30,US,Retail Sales MoM APR,-0.164,-8.30%,-0.12,-0.118 +Tuesday,05/19/20,1:00,GB,Claimant Count Change APR,856.5K,12.1K,676.5K,650K +Tuesday,05/19/20,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,0.0385,0.0385 +Wednesday,05/20/20,1:00,GB,Inflation Rate YoY APR,0.008,1.50%,0.009,0.008 +Wednesday,05/20/20,7:30,CA,Inflation Rate YoY APR,-0.002,0.90%,-0.001,-0.001 +Wednesday,05/20/20,18:50,JP,Balance of Trade APR,-930B,5.4B,-560B,-480B +Thursday,05/21/20,18:01,GB,Gfk Consumer Confidence 05,-34,-33,,-42 +Thursday,05/21/20,18:30,JP,Inflation Rate YoY APR,0.001,0.40%,,0.002 +Thursday,05/21/20,,CN,National People’s Congress,,,, +Thursday,05/28/20,4:00,EA,Business Confidence 05,-2.43,-1.99,,-3 +Thursday,05/28/20,7:30,US,Durable Goods Orders MoM APR,-0.172,-16.60%,-0.19,-0.19 +Thursday,05/28/20,0:00,JP,Consumer Confidence 05,24,21.6,,25.1 +Thursday,05/28/20,7:30,US,Personal Income MoM APR,0.105,-2.20%,-0.065,-0.066 +Thursday,05/28/20,7:30,US,Personal Spending MoM APR,-0.136,-6.90%,-0.126,-0.114 +Saturday,05/30/20,20:00,CN,NBS Manufacturing PMI 05,50.6,50.8,51,50.5 +Saturday,05/30/20,20:45,CN,Caixin Manufacturing PMI 05,50.7,49.4,49.6,49.5 +Thursday,06/04/20,7:30,CA,Balance of Trade APR,-3.25B,-1.53B,-2.36B, 0.5B +Thursday,06/04/20,7:30,US,Balance of Trade APR,-49.4B,-42.3B,-49B, -54.3B +Thursday,06/04/20,18:01,GB,Gfk Consumer Confidence Final 05,-36,-33,-34,-34 +Friday,06/05/20,7:30,US,Non Farm Payrolls 05,2509K,-20687K,-8000K,-8870K +Friday,06/05/20,9:00,CA,Ivey PMI s.a 05,39.1,22.8,,25 +Tuesday,06/09/20,20:30,CN,Inflation Rate YoY 05,0.024,3.30%,0.027,0.027 +Wednesday,06/10/20,7:30,US,Core Inflation Rate YoY 05,0.012,1.40%,0.013,0.012 +Wednesday,06/10/20,7:30,US,Inflation Rate YoY 05,0.001,0.30%,0.002,0.002 +Friday,06/12/20,1:00,GB,Balance of Trade APR,0.31B,-3.96B,,-6.2B +Tuesday,06/16/20,1:00,GB,Claimant Count Change 05,528.9K,1032.7K,400K,330K +Tuesday,06/16/20,7:30,US,Retail Sales MoM 05,0.177,-14.70%,0.08,0.075 +Tuesday,06/16/20,18:50,JP,Balance of Trade 05,-833.4B,-931.9B,-970.8B,-880B +Wednesday,06/17/20,1:00,GB,Inflation Rate YoY 05,0.005,0.80%,0.005,0.005 +Wednesday,06/17/20,7:30,CA,Inflation Rate YoY 05,-0.004,-0.20%,0,0 +Thursday,06/18/20,18:30,JP,Inflation Rate YoY 05,0.001,0.10%,0.001,0.001 +Sunday,06/21/20,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.037 +Thursday,06/25/20,7:30,US,Durable Goods Orders MoM 05,0.158,-18.10%,0.109,0.085 +Friday,06/26/20,7:30,US,Personal Income MoM 05,-0.042,10.80%,-0.06,-0.056 +Friday,06/26/20,7:30,US,Personal Spending MoM 05,0.082,-12.60%,0.09,0.095 +Monday,06/29/20,20:00,CN,NBS Manufacturing PMI JUN,50.9,50.6,50.4,50.2 +Tuesday,06/30/20,18:50,JP,Tankan Large Manufacturers Index Q2,-34,-8,-31,-34 +Tuesday,06/30/20,20:45,CN,Caixin Manufacturing PMI JUN,51.2,50.7,50.5,50.3 +Wednesday,07/01/20,0:00,JP,Consumer Confidence JUN,28.4,24,,30 +Thursday,07/02/20,7:30,CA,Balance of Trade 05,-0.68B,-4.27B,-3B, -2.8B +Thursday,07/02/20,7:30,US,Balance of Trade 05,-54.6B,-49.8B,-53B, -53B +Thursday,07/02/20,7:30,US,Non Farm Payrolls JUN,4800K,2699K,3000K,2900K +Thursday,07/02/20,18:01,GB,Gfk Consumer Confidence Final JUN,-27,-30,,-32 +Tuesday,07/07/20,9:00,CA,Ivey PMI s.a JUN,58.2,39.1,,43 +Wednesday,07/08/20,6:30,GB,Supplementary Budget,,,, +Wednesday,07/08/20,20:30,CN,Inflation Rate YoY JUN,0.025,2.40%,0.025,0.025 +Thursday,07/09/20,,EA,Eurogroup Meeting,,,, +Tuesday,07/14/20,1:00,GB,Balance of Trade 05,4.3B,2.3B,,-0.8B +Tuesday,07/14/20,7:30,US,Core Inflation Rate YoY JUN,0.012,1.20%,0.011,0.012 +Tuesday,07/14/20,7:30,US,Inflation Rate YoY JUN,0.006,0.10%,0.006,0.005 +Wednesday,07/15/20,1:00,GB,Inflation Rate YoY JUN,0.006,0.50%,0.004,0.006 +Thursday,07/16/20,1:00,GB,Claimant Count Change JUN,-28.1K,566.4K,250K,210K +Thursday,07/16/20,7:30,US,Retail Sales MoM JUN,0.075,18.20%,0.05,0.045 +Sunday,07/19/20,18:50,JP,Balance of Trade JUN,-268.8B,-838.2B,-35.8B,-40B +Sunday,07/19/20,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,0.0385,0.0385 +Monday,07/20/20,18:30,JP,Inflation Rate YoY JUN,0.001,0.10%,,0.001 +Wednesday,07/22/20,7:30,CA,Inflation Rate YoY JUN,0.007,-0.40%,0.003,0.003 +Thursday,07/23/20,18:01,GB,Gfk Consumer Confidence JUL,-27,-30,-26,-26 +Monday,07/27/20,7:30,US,Durable Goods Orders MoM JUN,0.073,15.10%,0.07,0.05 +Thursday,07/30/20,20:00,CN,NBS Manufacturing PMI JUL,51.1,50.9,50.7,51 +Friday,07/31/20,0:00,JP,Consumer Confidence JUL,29.5,28.4,,26 +Friday,07/31/20,7:30,US,Personal Income MoM JUN,-0.011,-4.40%,-0.005,-0.003 +Friday,07/31/20,7:30,US,Personal Spending MoM JUN,0.056,8.50%,0.055,0.053 +Sunday,08/02/20,20:45,CN,Caixin Manufacturing PMI JUL,52.8,51.2,51.3,51.6 +Wednesday,08/05/20,7:30,CA,Balance of Trade JUN,-3.19B,-1.33B,-0.9B, -1B +Wednesday,08/05/20,7:30,US,Balance of Trade JUN,-50.7B,-54.8B,-50.1B,-50.7B +Friday,08/07/20,7:30,US,Non Farm Payrolls JUL,1763K,4800K,1600K,1620K +Friday,08/07/20,9:00,CA,Ivey PMI s.a JUL,68.5,58.2,57.5,57.9 +Sunday,08/09/20,20:30,CN,Inflation Rate YoY JUL,0.027,2.50%,0.026,0.027 +Tuesday,08/11/20,1:00,GB,Claimant Count Change JUL,94.4K,-28.1K,10K,5K +Wednesday,08/12/20,1:00,GB,Balance of Trade JUN,5.3B,7.7B,,2.8B +Wednesday,08/12/20,7:30,US,Core Inflation Rate YoY JUL,0.016,1.20%,0.011,0.01 +Wednesday,08/12/20,7:30,US,Inflation Rate YoY JUL,0.01,0.60%,0.008,0.007 +Friday,08/14/20,7:30,US,Retail Sales MoM JUL,0.012,8.40%,0.019,0.02 +Tuesday,08/18/20,18:50,JP,Balance of Trade JUL,11.6B,-269.3B,-77.6B,-120B +Wednesday,08/19/20,1:00,GB,Inflation Rate YoY JUL,0.01,0.60%,0.006,0.007 +Wednesday,08/19/20,7:30,CA,Inflation Rate YoY JUL,0.001,0.70%,0.005,0.005 +Wednesday,08/19/20,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385 +Thursday,08/20/20,18:01,GB,Gfk Consumer Confidence AUG,-27,-27,-25,-24 +Thursday,08/20/20,18:30,JP,Inflation Rate YoY JUL,0.003,0.10%,,0.001 +Wednesday,08/26/20,7:30,US,Durable Goods Orders MoM JUL,0.112,7.70%,0.043,0.039 +Friday,08/28/20,7:30,US,Personal Income MoM JUL,0.004,-1%,-0.002,-0.004 +Friday,08/28/20,7:30,US,Personal Spending MoM JUL,0.019,6.20%,0.015,0.012 +Sunday,08/30/20,20:00,CN,NBS Manufacturing PMI AUG,51,51.1,51.2,51.3 +Monday,08/31/20,0:00,JP,Consumer Confidence AUG,29.3,29.5,,29 +Monday,08/31/20,20:45,CN,Caixin Manufacturing PMI AUG,53.1,52.8,52.6,52.4 +Thursday,09/03/20,7:30,CA,Balance of Trade JUL,-2.45B,-1.59B,-2.5B, -2.3B +Thursday,09/03/20,7:30,US,Balance of Trade JUL,-63.6B,-53.5B,-58B, -59B +Friday,09/04/20,7:30,US,Non Farm Payrolls AUG,1371K,1734K,1400K,1490K +Friday,09/04/20,9:00,CA,Ivey PMI s.a AUG,67.8,68.5,,68.7 +Tuesday,09/08/20,20:30,CN,Inflation Rate YoY AUG,0.024,2.70%,0.024,0.025 +Friday,09/11/20,1:00,GB,Balance of Trade JUL,1.1B,3.9B,,1.2B +Friday,09/11/20,7:30,US,Core Inflation Rate YoY AUG,0.017,1.60%,0.016,0.015 +Friday,09/11/20,7:30,US,Inflation Rate YoY AUG,0.013,1%,0.012,0.011 +Friday,09/11/20,,EA,Eurogroup Meeting,,,, +Tuesday,09/15/20,1:00,GB,Claimant Count Change AUG,73.7K,69.9K,100K,51K +Tuesday,09/15/20,18:50,JP,Balance of Trade AUG,248.3B,10.9B,-37.5B,-50B +Wednesday,09/16/20,1:00,GB,Inflation Rate YoY AUG,0.002,1%,0,0.001 +Wednesday,09/16/20,7:30,CA,Inflation Rate YoY AUG,0.001,0.10%,0.004,0.003 +Wednesday,09/16/20,7:30,US,Retail Sales MoM AUG,0.006,0.90%,0.01,0.01 +Thursday,09/17/20,18:30,JP,Inflation Rate YoY AUG,0.002,0.30%,,0.001 +Sunday,09/20/20,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,0.0385,0.0385 +Thursday,09/24/20,6:30,GB,Winter Economy Plan,,,, +Thursday,09/24/20,18:01,GB,Gfk Consumer Confidence SEP,-25,-27,-27,-26 +Friday,09/25/20,7:30,US,Durable Goods Orders MoM AUG,0.004,11.70%,0.015,0.02 +Tuesday,09/29/20,20:00,CN,NBS Manufacturing PMI SEP,51.5,51,51.2,51.4 +Tuesday,09/29/20,20:45,CN,Caixin Manufacturing PMI SEP,53,53.1,53.1,53.4 +Wednesday,09/30/20,18:50,JP,Tankan Large Manufacturers Index Q3,-27,-34,-23,-26 +Thursday,10/01/20,7:30,US,Personal Income MoM AUG,-0.027,0.50%,-0.024,-0.02 +Thursday,10/01/20,7:30,US,Personal Spending MoM AUG,0.01,1.50%,0.008,0.008 +Friday,10/02/20,0:00,JP,Consumer Confidence SEP,32.7,29.3,,32 +Friday,10/02/20,7:30,US,Non Farm Payrolls SEP,661K,1489K,850K,915K +Monday,10/05/20,,EA,Eurogroup Video Conference,,,, +Tuesday,10/06/20,7:30,CA,Balance of Trade AUG,-2.45B,-2.53B,-2B, -2.1B +Tuesday,10/06/20,7:30,US,Balance of Trade AUG,-67.1B,-63.4B,-66.1B, -66.5B +Wednesday,10/07/20,9:00,CA,Ivey PMI s.a SEP,54.3,67.8,,68 +Friday,10/09/20,1:00,GB,Balance of Trade AUG,1.4B,1.7B,,0.6B +Tuesday,10/13/20,1:00,GB,Claimant Count Change SEP,28K,39.5K,78.8K,72K +Tuesday,10/13/20,7:30,US,Core Inflation Rate YoY SEP,0.017,1.70%,0.018,0.017 +Tuesday,10/13/20,7:30,US,Inflation Rate YoY SEP,0.014,1.30%,0.014,0.015 +Wednesday,10/14/20,20:30,CN,Inflation Rate YoY SEP,0.017,2.40%,0.018,0.02 +Friday,10/16/20,7:30,US,Retail Sales MoM SEP,0.019,0.60%,0.007,0.005 +Sunday,10/18/20,18:50,JP,Balance of Trade SEP,675B,248.6B,989.8B, 900B +Monday,10/19/20,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,0.0385,0.0385 +Wednesday,10/21/20,1:00,GB,Inflation Rate YoY SEP,0.005,0.20%,0.005,0.004 +Wednesday,10/21/20,7:30,CA,Inflation Rate YoY SEP,0.005,0.10%,0.004,0.003 +Thursday,10/22/20,18:01,GB,Gfk Consumer Confidence OCT,-31,-30,-28,-26 +Thursday,10/22/20,18:30,JP,Inflation Rate YoY SEP,0,0.20%,,0.001 +Tuesday,10/27/20,7:30,US,Durable Goods Orders MoM SEP,0.019,0.40%,0.005,0.004 +Thursday,10/29/20,0:00,JP,Consumer Confidence OCT,33.6,32.7,,34.8 +Friday,10/30/20,7:30,US,Personal Income MoM SEP,0.009,-2.50%,0.004,0.004 +Friday,10/30/20,7:30,US,Personal Spending MoM SEP,0.014,1%,0.01,0.008 +Friday,10/30/20,20:00,CN,NBS Manufacturing PMI OCT,51.4,51.5,51.3,51.4 +Sunday,11/01/20,20:45,CN,Caixin Manufacturing PMI OCT,53.6,53,53,52.8 +Monday,11/02/20,,US,Presidential Election,,,, +Tuesday,11/03/20,,EA,Eurogroup Video Conference,,,, +Wednesday,11/04/20,8:30,CA,Balance of Trade SEP,-3.25B,-3.21B,-2.6B, -2.6B +Wednesday,11/04/20,8:30,US,Balance of Trade SEP,-63.9B,-67B,-63.8B, -63.1B +Friday,11/06/20,8:30,US,Non Farm Payrolls OCT,638K,672K,600K,510K +Friday,11/06/20,10:00,CA,Ivey PMI s.a OCT,54.5,54.3,51.5,52 +Monday,11/09/20,20:30,CN,Inflation Rate YoY OCT,0.005,1.70%,0.008,0.01 +Tuesday,11/10/20,2:00,GB,Claimant Count Change OCT,-29.8K,-40.2K,50K,36K +Thursday,11/12/20,2:00,GB,Balance of Trade SEP,0.6B,2.9B,,-1.0B +Thursday,11/12/20,8:30,US,Core Inflation Rate YoY OCT,0.016,1.70%,0.018,0.018 +Thursday,11/12/20,8:30,US,Inflation Rate YoY OCT,0.012,1.40%,0.013,0.015 +Tuesday,11/17/20,8:30,US,Retail Sales MoM OCT,0.003,1.60%,0.005,0.004 +Tuesday,11/17/20,18:50,JP,Balance of Trade OCT,872.9B,687.8B,250B,210B +Wednesday,11/18/20,2:00,GB,Inflation Rate YoY OCT,0.007,0.50%,0.006,0.007 +Wednesday,11/18/20,8:30,CA,Inflation Rate YoY OCT,0.007,0.50%,0.004,0.003 +Thursday,11/19/20,18:30,JP,Inflation Rate YoY OCT,-0.004,0%,-0.003,-0.002 +Thursday,11/19/20,19:01,GB,GfK Consumer Confidence NOV,-33,-31,-34,-33 +Thursday,11/19/20,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385 +Wednesday,11/25/20,8:30,US,Durable Goods Orders MoM OCT,0.013,2.10%,0.009,0.008 +Wednesday,11/25/20,10:00,US,Personal Income MoM OCT,-0.007,0.70%,0,0.002 +Wednesday,11/25/20,10:00,US,Personal Spending MoM OCT,0.005,1.20%,0.004,0.005 +Sunday,11/29/20,20:00,CN,NBS Manufacturing PMI NOV,52.1,51.4,51.5,51 +Monday,11/30/20,20:45,CN,Caixin Manufacturing PMI NOV,54.9,53.6,53.5,53.2 +Monday,11/30/20,,EA,Eurogroup Video Conference,,,, +Wednesday,12/02/20,0:00,JP,Consumer Confidence NOV,33.7,33.6,,33 +Friday,12/04/20,8:30,CA,Balance of Trade OCT,-3.76B,-3.8B,-3B,-3.5B +Friday,12/04/20,8:30,US,Balance of Trade OCT,-63.1B,-62.1B,-64.8B,-65B +Friday,12/04/20,8:30,US,Non Farm Payrolls NOV,245K,610K,469K,500K +Monday,12/07/20,10:00,CA,Ivey PMI s.a NOV,52.7,54.5,54.7,54 +Tuesday,12/08/20,20:30,CN,Inflation Rate YoY NOV,-0.005,0.50%,0,0.001 +Thursday,12/10/20,2:00,GB,Balance of Trade OCT,-1.7B,0.6B,,0.5B +Thursday,12/10/20,8:30,US,Core Inflation Rate YoY NOV,0.016,1.60%,0.016,0.016 +Thursday,12/10/20,8:30,US,Inflation Rate YoY NOV,0.012,1.20%,0.011,0.012 +Sunday,12/13/20,18:50,JP,Tankan Large Manufacturers Index Q4,-10,-27,-15,-17 +Tuesday,12/15/20,2:00,GB,Claimant Count Change NOV,64.3K,-29.8K,,30K +Tuesday,12/15/20,18:50,JP,Balance of Trade NOV,366.8B,871.7B,529.8B,510B +Wednesday,12/16/20,2:00,GB,Inflation Rate YoY NOV,0.003,0.70%,0.006,0.008 +Wednesday,12/16/20,8:30,CA,Inflation Rate YoY NOV,0.01,0.70%,0.008,0.008 +Wednesday,12/16/20,8:30,US,Retail Sales MoM NOV,-0.011,-0.10%,-0.003,-0.003 +Wednesday,12/16/20,,EA,Eurogroup Video Conference,,,, +Thursday,12/17/20,18:30,JP,Inflation Rate YoY NOV,-0.009,-0.40%,,-0.005 +Thursday,12/17/20,19:01,GB,GfK Consumer Confidence DEC,-26,-33,-31,-30 +Sunday,12/20/20,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,0.0385,0.0385 +Wednesday,12/23/20,8:30,US,Durable Goods Orders MoM NOV,0.009,1.80%,0.006,0.006 +Wednesday,12/23/20,8:30,US,Personal Income MoM NOV,-0.011,-0.60%,-0.003,-0.004 +Wednesday,12/23/20,8:30,US,Personal Spending MoM NOV,-0.004,0.30%,-0.002,-0.004 +Wednesday,12/30/20,20:00,CN,NBS Manufacturing PMI DEC,51.9,52.1,52,51.5 +Sunday,01/03/21,20:45,CN,Caixin Manufacturing PMI DEC,53,54.9,54.8,54.6 +Wednesday,01/06/21,0:00,JP,Consumer Confidence DEC,31.8,33.7,,35 +Thursday,01/07/21,8:30,CA,Balance of Trade NOV,-3.34B,-3.73B,-3.5B,-3.2B +Thursday,01/07/21,8:30,US,Balance of Trade NOV,-68.1B,-63.1B,-65.2B,-67.6B +Thursday,01/07/21,10:00,CA,Ivey PMI s.a DEC,46.7,52.7,,53.2 +Friday,01/08/21,8:30,US,Non Farm Payrolls DEC,-140K,336K,71K,112K +Sunday,01/10/21,20:30,CN,Inflation Rate YoY DEC,0.002,-0.50%,0.001,0 +Wednesday,01/13/21,8:30,US,Core Inflation Rate YoY DEC,0.016,1.60%,0.016,0.016 +Wednesday,01/13/21,8:30,US,Inflation Rate YoY DEC,0.014,1.20%,0.013,0.012 +Friday,01/15/21,2:00,GB,Balance of Trade NOV,-5B,-2.3B,,-1.2B +Friday,01/15/21,8:30,US,Retail Sales MoM DEC,-0.007,-1.40%,0,-0.002 +Tuesday,01/19/21,10:00,US,Treasury Secretary Yellen Senate Confirmation Hearing,,,, +Tuesday,01/19/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385 +Wednesday,01/20/21,2:00,GB,Inflation Rate YoY DEC,0.006,0.30%,0.005,0.006 +Wednesday,01/20/21,8:30,CA,Inflation Rate YoY DEC,0.007,1%,0.01,0.01 +Wednesday,01/20/21,18:50,JP,Balance of Trade DEC,751B,366.8B,942.8B,800B +Thursday,01/21/21,18:30,JP,Inflation Rate YoY DEC,-0.012,-0.90%,,-0.01 +Thursday,01/21/21,19:01,GB,Gfk Consumer Confidence JAN,-28,-26,-29,-28 +Tuesday,01/26/21,2:00,GB,Claimant Count Change DEC,7K,38.1K,35K,40K +Wednesday,01/27/21,8:30,US,Durable Goods Orders MoM DEC,0.002,1.20%,0.009,0.008 +Wednesday,01/27/21,14:30,US,Fed Press Conference,,,, +Friday,01/29/21,0:00,JP,Consumer Confidence JAN,29.6,31.8,,31.2 +Friday,01/29/21,8:30,US,Personal Income MoM DEC,0.006,-1.30%,0.001,0.001 +Friday,01/29/21,8:30,US,Personal Spending MoM DEC,-0.002,-0.70%,-0.004,-0.006 +Saturday,01/30/21,20:00,CN,NBS Manufacturing PMI JAN,51.3,51.9,51.6,51.5 +Sunday,01/31/21,20:45,CN,Caixin Manufacturing PMI JAN,51.5,53,52.7,52.5 +Friday,02/05/21,8:30,CA,Balance of Trade DEC,-1.67B,-3.56B,-3B, -3.2B +Friday,02/05/21,8:30,US,Balance of Trade DEC,-66.6B,-69B,-65.7B,-70B +Friday,02/05/21,8:30,US,Non Farm Payrolls JAN,49K,-227K,50K,45K +Friday,02/05/21,10:00,CA,Ivey PMI s.a JAN,48.4,46.7,,47 +Tuesday,02/09/21,20:30,CN,Inflation Rate YoY JAN,-0.003,0.20%,0,-0.002 +Wednesday,02/10/21,8:30,US,Core Inflation Rate YoY JAN,0.014,1.60%,0.015,0.016 +Wednesday,02/10/21,8:30,US,Inflation Rate YoY JAN,0.014,1.40%,0.015,0.014 +Friday,02/12/21,2:00,GB,Balance of Trade DEC,-6.2B,-6.6B,,-4.2B +Tuesday,02/16/21,18:50,JP,Balance of Trade JAN,-323.9B,749.6B,-600B,-430B +Wednesday,02/17/21,2:00,GB,Inflation Rate YoY JAN,0.007,0.60%,0.006,0.004 +Wednesday,02/17/21,8:30,CA,Inflation Rate YoY JAN,0.01,0.70%,0.009,0.008 +Wednesday,02/17/21,8:30,US,Retail Sales MoM JAN,0.053,-1%,0.011,0.009 +Wednesday,02/17/21,14:00,US,FOMC Minutes,,,, +Thursday,02/18/21,18:30,JP,Inflation Rate YoY JAN,-0.006,-1.20%,,-0.01 +Thursday,02/18/21,19:01,GB,Gfk Consumer Confidence FEB,-23,-28,-27,-26 +Friday,02/19/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385 +Tuesday,02/23/21,2:00,GB,Claimant Count Change JAN,-20K,-20.4K,,25K +Thursday,02/25/21,8:30,US,Durable Goods Orders MoM JAN,0.034,1.20%,0.011,0.012 +Friday,02/26/21,8:30,US,Personal Income MoM JAN,0.1,0.60%,0.095,0.085 +Friday,02/26/21,8:30,US,Personal Spending MoM JAN,0.024,-0.40%,0.025,0.019 +Sunday,02/28/21,3:00,CN,NBS Manufacturing PMI FEB,50.6,51.3,51.1,51 +Sunday,02/28/21,20:45,CN,Caixin Manufacturing PMI FEB,50.9,51.5,51.5,51.2 +Thursday,03/04/21,0:00,JP,Consumer Confidence FEB,33.8,29.6,,30.8 +Thursday,03/04/21,,CN,National People's Congress,,,, +Thursday,03/04/21,,CN,Premier Li Keqiang Speech ,,,, +Friday,03/05/21,8:30,CA,Balance of Trade JAN,1.41B,-1.98B,-1.4B, -1.6B +Friday,03/05/21,8:30,US,Balance of Trade JAN,-68.2B,-67B,-67.5B,-67.5B +Friday,03/05/21,8:30,US,Non Farm Payrolls FEB,379K,166K,182K,170K +Friday,03/05/21,10:00,CA,Ivey PMI s.a FEB,60,48.4,,49 +Tuesday,03/09/21,20:30,CN,Inflation Rate YoY FEB,-0.002,-0.30%,-0.004,-0.003 +Wednesday,03/10/21,8:30,US,Core Inflation Rate YoY FEB,0.013,1.40%,0.014,0.014 +Wednesday,03/10/21,8:30,US,Inflation Rate YoY FEB,0.017,1.40%,0.017,0.016 +Friday,03/12/21,2:00,GB,Balance of Trade JAN,-1.6B,-6.2B,,-4.8B +Tuesday,03/16/21,7:30,US,Retail Sales MoM FEB,-0.03,7.60%,-0.005,-0.006 +Tuesday,03/16/21,18:50,JP,Balance of Trade FEB,217.4B,-325.4B,420B,450B +Wednesday,03/17/21,7:30,CA,Inflation Rate YoY FEB,0.011,1%,0.013,0.011 +Wednesday,03/17/21,13:30,US,Fed Press Conference,,,, +Thursday,03/18/21,18:30,JP,Inflation Rate YoY FEB,-0.004,-0.60%,,-0.004 +Thursday,03/18/21,19:01,GB,Gfk Consumer Confidence MAR,-16,-23,-20,-20 +Tuesday,03/23/21,2:00,GB,Claimant Count Change FEB,86.6K,-20.8K,,-17K +Wednesday,03/24/21,2:00,GB,Inflation Rate YoY FEB,0.004,0.70%,0.008,0.008 +Wednesday,03/24/21,7:30,US,Durable Goods Orders MoM FEB,-0.011,3.50%,0.008,0.011 +Friday,03/26/21,7:30,US,Personal Income MoM FEB,-0.071,10.10%,-0.073,-0.08 +Friday,03/26/21,7:30,US,Personal Spending MoM FEB,-0.01,3.40%,-0.007,-0.007 +Tuesday,03/30/21,20:00,CN,NBS Manufacturing PMI MAR,51.9,50.6,51,51.1 +Tuesday,03/30/21,,US,President Biden Speech on Recovery Package ,,,, +Wednesday,03/31/21,18:50,JP,Tankan Large Manufacturers Index Q1,5,-10,0,-2 +Wednesday,03/31/21,20:45,CN,Caixin Manufacturing PMI MAR,50.6,50.9,51.3,51.2 +Friday,04/02/21,7:30,US,Non Farm Payrolls MAR,916K,468K,647K,680K +Wednesday,04/07/21,7:30,CA,Balance of Trade FEB,1.04B,1.21B,1B,1.5B +Wednesday,04/07/21,7:30,US,Balance of Trade FEB,-71.1B,-67.8B,-70.5B,-69.8B +Wednesday,04/07/21,9:00,CA,Ivey PMI s.a MAR,72.9,60,60.5,62 +Wednesday,04/07/21,13:00,US,FOMC Minutes,,,, +Thursday,04/08/21,0:00,JP,Consumer Confidence MAR,36.1,33.8,,36 +Thursday,04/08/21,20:30,CN,Inflation Rate YoY MAR,0.004,-0.20%,0.003,0.002 +Tuesday,04/13/21,1:00,GB,Balance of Trade FEB,-7.1B,-3.4B,,-2.2B +Tuesday,04/13/21,7:30,US,Core Inflation Rate YoY MAR,0.016,1.30%,0.015,0.016 +Tuesday,04/13/21,7:30,US,Inflation Rate YoY MAR,0.026,1.70%,0.025,0.026 +Thursday,04/15/21,7:30,US,Retail Sales MoM MAR,0.098,-2.70%,0.059,0.045 +Sunday,04/18/21,18:50,JP,Balance of Trade MAR,663.7B,215.9B,490B, 300B +Monday,04/19/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,0.0385,0.0385 +Tuesday,04/20/21,1:00,GB,Claimant Count Change MAR,10.1K,86.6K,,150K +Wednesday,04/21/21,1:00,GB,Inflation Rate YoY MAR,0.007,0.40%,0.008,0.008 +Wednesday,04/21/21,7:30,CA,Inflation Rate YoY MAR,0.022,1.10%,0.023,0.021 +Thursday,04/22/21,18:01,GB,Gfk Consumer Confidence APR,-15,-16,-12,-12 +Thursday,04/22/21,18:30,JP,Inflation Rate YoY MAR,-0.002,-0.40%,,-0.001 +Monday,04/26/21,7:30,US,Durable Goods Orders MoM MAR,0.005,-0.90%,0.025,0.017 +Wednesday,04/28/21,13:30,US,Fed Press Conference,,,, +Thursday,04/29/21,20:00,CN,NBS Manufacturing PMI APR,51.1,51.9,51.7,52.1 +Thursday,04/29/21,20:45,CN,Caixin Manufacturing PMI APR,51.9,50.6,50.8,50.9 +Friday,04/30/21,0:00,JP,Consumer Confidence APR,34.7,36.1,,35.5 +Friday,04/30/21,7:30,US,Personal Income MoM MAR,0.211,-7%,0.203,0.205 +Friday,04/30/21,7:30,US,Personal Spending MoM MAR,0.042,-1%,0.041,0.046 +Tuesday,05/04/21,7:30,CA,Balance of Trade MAR,-1.14B,1.42B,0.7B,0.5B +Tuesday,05/04/21,7:30,US,Balance of Trade MAR,-74.4B,-70.5B,-74.5B,-73.4B +Tuesday,05/04/21,7:30,US,Non Farm Payrolls APR,266K,770K,978K,950K +Tuesday,05/04/21,9:00,CA,Ivey PMI s.a APR,60.6,72.9,,67 +Tuesday,05/04/21,20:30,CN,Inflation Rate YoY APR,0.009,0.40%,0.01,0.011 +Wednesday,05/12/21,1:00,GB,Balance of Trade MAR,-2B,-0.9B,,-6.1B +Wednesday,05/12/21,7:30,US,Core Inflation Rate YoY APR,0.03,1.60%,0.023,0.022 +Wednesday,05/12/21,7:30,US,Inflation Rate YoY APR,0.042,2.60%,0.036,0.038 +Wednesday,05/12/21,7:30,US,Retail Sales MoM APR,0,10.70%,0.01,0.003 +Tuesday,05/18/21,1:00,GB,Claimant Count Change APR,-15.1K,-19.4K,,25K +Wednesday,05/19/21,1:00,GB,Inflation Rate YoY APR,0.015,0.70%,0.014,0.014 +Wednesday,05/19/21,7:30,CA,Inflation Rate YoY APR,0.034,2.20%,0.032,0.032 +Wednesday,05/19/21,13:00,US,FOMC Minutes,,,, +Wednesday,05/19/21,18:50,JP,Balance of Trade APR,255.3B,662.2B,140B,150B +Wednesday,05/19/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385 +Thursday,05/20/21,18:01,GB,Gfk Consumer Confidence 05,-9,-15,-12,-14 +Thursday,05/20/21,18:30,JP,Inflation Rate YoY APR,-0.004,-0.20%,,0.001 +Thursday,05/27/21,7:30,US,Durable Goods Orders MoM APR,-0.013,1.30%,0.007,0.007 +Thursday,05/27/21,7:30,US,Personal Income MoM APR,-0.131,20.90%,-0.141,-0.14 +Thursday,05/27/21,7:30,US,Personal Spending MoM APR,0.005,4.70%,0.005,0.005 +Thursday,05/27/21,20:00,CN,NBS Manufacturing PMI 05,51,51.1,51.1,51.2 +Thursday,05/27/21,0:00,JP,Consumer Confidence 05,34.1,34.7,,34 +Thursday,05/27/21,20:45,CN,Caixin Manufacturing PMI 05,52,51.9,51.9,51.7 +Friday,06/04/21,7:30,US,Non Farm Payrolls 05,559K,278K,650K,610K +Friday,06/04/21,9:00,CA,Ivey PMI s.a 05,64.7,60.6,,65 +Tuesday,06/08/21,7:30,CA,Balance of Trade APR,0.59B,-1.35B,-0.7B,-0.9B +Tuesday,06/08/21,7:30,US,Balance of Trade APR,-68.9B,-75B,-69B,-69B +Tuesday,06/08/21,20:30,CN,Inflation Rate YoY 05,0.013,0.90%,0.016,0.015 +Thursday,06/10/21,7:30,US,Core Inflation Rate YoY 05,0.038,3%,0.034,0.032 +Thursday,06/10/21,7:30,US,Inflation Rate YoY 05,0.05,4.20%,0.047,0.047 +Friday,06/11/21,1:00,GB,Balance of Trade APR,-0.9B,-2B,,-3.2B +Tuesday,06/15/21,1:00,GB,Claimant Count Change 05,-92.6K,-55.8K,,-62K +Tuesday,06/15/21,7:30,US,Retail Sales MoM 05,-0.013,0.90%,-0.008,-0.003 +Tuesday,06/15/21,18:50,JP,Balance of Trade 05,-187.1B,253.1B,-91.2B,-78B +Wednesday,06/16/21,1:00,GB,Inflation Rate YoY 05,0.021,1.50%,0.018,0.018 +Wednesday,06/16/21,7:30,CA,Inflation Rate YoY 05,0.036,3.40%,0.035,0.036 +Wednesday,06/16/21,13:30,US,Fed Press Conference,,,, +Thursday,06/17/21,18:30,JP,Inflation Rate YoY 05,-0.001,-0.40%,,-0.003 +Sunday,06/20/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385 +Thursday,06/24/21,7:30,US,Durable Goods Orders MoM 05,0.023,-0.80%,0.028,0.02 +Thursday,06/24/21,18:01,GB,Gfk Consumer Confidence JUN,-9,-9,-7,-7 +Friday,06/25/21,7:30,US,Personal Income MoM 05,-0.02,-13.10%,-0.025,-0.03 +Friday,06/25/21,7:30,US,Personal Spending MoM 05,0,0.90%,0.004,0.004 +Tuesday,06/29/21,20:00,CN,NBS Manufacturing PMI JUN,50.9,51,50.8,50.9 +Wednesday,06/30/21,0:00,JP,Consumer Confidence JUN,37.4,34.1,,33 +Wednesday,06/30/21,18:50,JP,Tankan Large Manufacturers Index Q2,14,5,15,15 +Wednesday,06/30/21,20:45,CN,Caixin Manufacturing PMI JUN,51.3,52,51.8,51.9 +Friday,07/02/21,7:30,CA,Balance of Trade 05,-1.39B,0.46B,0.37B,-0.3B +Friday,07/02/21,7:30,US,Balance of Trade 05,-71.2B,-69.1B,-71.4B,-71.6B +Friday,07/02/21,7:30,US,Non Farm Payrolls JUN,850K,583K,700K,650K +Wednesday,07/07/21,9:00,CA,Ivey PMI s.a JUN,71.9,64.7,,65 +Wednesday,07/07/21,13:00,US,FOMC Minutes,,,, +Thursday,07/08/21,20:30,CN,Inflation Rate YoY JUN,0.011,1.30%,0.013,0.015 +Friday,07/09/21,6:00,GB,Balance of Trade 05,0.9B,-1.6B,,-1.4B +Tuesday,07/13/21,7:30,US,Core Inflation Rate YoY JUN,0.045,3.80%,0.04,0.039 +Tuesday,07/13/21,7:30,US,Inflation Rate YoY JUN,0.054,5%,0.049,0.049 +Wednesday,07/14/21,1:00,GB,Inflation Rate YoY JUN,0.025,2.10%,0.022,0.023 +Thursday,07/15/21,1:00,GB,Claimant Count Change JUN,-114.8K,-92.6K,,-120K +Friday,07/16/21,7:30,US,Retail Sales MoM JUN,0.006,-1.70%,-0.004,-0.005 +Monday,07/19/21,18:30,JP,Inflation Rate YoY JUN,0.002,-0.10%,,0 +Monday,07/19/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385 +Tuesday,07/20/21,18:50,JP,Balance of Trade JUN,383.2B,-189.4B,460B, 400B +Thursday,07/22/21,18:01,GB,Gfk Consumer Confidence JUL,-7,-9,-8,-7 +Tuesday,07/27/21,7:30,US,Durable Goods Orders MoM JUN,0.008,3.20%,0.021,0.019 +Wednesday,07/28/21,7:30,CA,Inflation Rate YoY JUN,0.031,3.60%,0.032,0.031 +Wednesday,07/28/21,13:30,US,Fed Press Conference,,,, +Friday,07/30/21,7:30,US,Personal Income MoM JUN,0.001,-2.20%,-0.003,-0.003 +Friday,07/30/21,7:30,US,Personal Spending MoM JUN,0.01,-0.10%,0.007,0.005 +Friday,07/30/21,20:00,CN,NBS Manufacturing PMI JUL,50.4,50.9,50.8,50.8 +Sunday,08/01/21,20:45,CN,Caixin Manufacturing PMI JUL,50.3,51.3,51,51 +Monday,08/02/21,0:00,JP,Consumer Confidence JUL,37.5,37.4,,37 +Thursday,08/05/21,7:30,CA,Balance of Trade JUN,3.23B,-1.58B,-0.68B, -0.7B +Thursday,08/05/21,7:30,US,Balance of Trade JUN,-75.7B,-71B,-73.9B,-74.3B +Friday,08/06/21,7:30,US,Non Farm Payrolls JUL,943K,938K,870K,900K +Friday,08/06/21,9:00,CA,Ivey PMI s.a JUL,56.4,71.9,,70 +Sunday,08/08/21,20:30,CN,Inflation Rate YoY JUL,0.01,1.10%,0.008,0.009 +Wednesday,08/11/21,7:30,US,Core Inflation Rate YoY JUL,0.043,4.50%,0.043,0.044 +Wednesday,08/11/21,7:30,US,Inflation Rate YoY JUL,0.054,5.40%,0.053,0.054 +Thursday,08/12/21,1:00,GB,Balance of Trade JUN,-2.5B,-0.2B,,-2.2B +Tuesday,08/17/21,1:00,GB,Claimant Count Change JUL,-7.8K,-114.8K,,-180K +Tuesday,08/17/21,7:30,US,Retail Sales MoM JUL,-0.011,0.70%,-0.003,-0.003 +Tuesday,08/17/21,18:50,JP,Balance of Trade JUL,441B,384B,202.3B,300B +Wednesday,08/18/21,1:00,GB,Inflation Rate YoY JUL,0.02,2.50%,0.023,0.024 +Wednesday,08/18/21,7:30,CA,Inflation Rate YoY JUL,0.037,3.10%,0.034,0.033 +Wednesday,08/18/21,13:00,US,FOMC Minutes,,,, +Thursday,08/19/21,18:01,GB,Gfk Consumer Confidence AUG,-8,-7,-7,-6 +Thursday,08/19/21,18:30,JP,Inflation Rate YoY JUL,-0.003,-0.50%,,-0.001 +Thursday,08/19/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385 +Wednesday,08/25/21,7:30,US,Durable Goods Orders MoM JUL,-0.001,0.80%,-0.003,-0.002 +Friday,08/27/21,7:30,US,Personal Income MoM JUL,0.011,0.20%,0.002,0.002 +Friday,08/27/21,7:30,US,Personal Spending MoM JUL,0.003,1.10%,0.003,0.005 +Monday,08/30/21,20:00,CN,NBS Manufacturing PMI AUG,50.1,50.4,50.2,50.3 +Tuesday,08/31/21,0:00,JP,Consumer Confidence AUG,36.7,37.5,,37 +Tuesday,08/31/21,20:45,CN,Caixin Manufacturing PMI AUG,49.2,50.3,50.2,50.2 +Thursday,09/02/21,7:30,CA,Balance of Trade JUL,0.78B,2.56B,1.4B,2.5B +Thursday,09/02/21,7:30,US,Balance of Trade JUL,-70B,-73.2B,-71B,-70B +Friday,09/03/21,7:30,US,Non Farm Payrolls AUG,235K,1053K,750K,750K +Wednesday,09/08/21,9:00,CA,Ivey PMI s.a AUG,66,56.4,,56 +Wednesday,09/08/21,20:30,CN,Inflation Rate YoY AUG,0.008,1.00%,0.01,0.01 +Friday,09/10/21,1:00,GB,Balance of Trade JUL,-3.1B,-2.5B,,-2B +Tuesday,09/14/21,1:00,GB,Claimant Count Change AUG,-58.6K,-7.8K,,-26K +Tuesday,09/14/21,7:30,US,Core Inflation Rate YoY AUG,0.04,4.30%,0.042,0.043 +Tuesday,09/14/21,7:30,US,Inflation Rate YoY AUG,0.053,5.40%,0.053,0.053 +Wednesday,09/15/21,1:00,GB,Inflation Rate YoY AUG,0.032,2%,0.029,0.029 +Wednesday,09/15/21,7:30,CA,Inflation Rate YoY AUG,0.041,3.70%,0.039,0.037 +Wednesday,09/15/21,18:50,JP,Balance of Trade AUG,-635.4B,439.4B,-47.7B,-60B +Thursday,09/16/21,7:30,US,Retail Sales MoM AUG,0.007,-1.80%,-0.008,-0.007 +Tuesday,09/21/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385 +Wednesday,09/22/21,13:30,US,Fed Press Conference,,,, +Thursday,09/23/21,18:01,GB,Gfk Consumer Confidence SEP,-13,-8,-8,-8 +Thursday,09/23/21,18:30,JP,Inflation Rate YoY AUG,-0.004,-0.30%,,-0.001 +Monday,09/27/21,7:30,US,Durable Goods Orders MoM AUG,0.018,0.50%,0.007,0.004 +Wednesday,09/29/21,20:00,CN,NBS Manufacturing PMI SEP,49.6,50.1,50.1,50.4 +Wednesday,09/29/21,20:45,CN,Caixin Manufacturing PMI SEP,50,49.2,49.5,49.9 +Thursday,09/30/21,18:50,JP,Tankan Large Manufacturers Index Q3,18,14,13,12 +Friday,10/01/21,0:00,JP,Consumer Confidence SEP,37.8,36.7,,37 +Friday,10/01/21,4:00,EA,Inflation Rate YoY Flash SEP,0.034,3%,0.033,0.031 +Friday,10/01/21,7:30,US,Personal Income MoM AUG,0.002,1.10%,0.003,0.002 +Friday,10/01/21,7:30,US,Personal Spending MoM AUG,0.008,-0.10%,0.006,0.003 +Friday,10/01/21,9:00,US,ISM Manufacturing PMI SEP,61.1,59.9,59.6,59 +Tuesday,10/05/21,7:30,CA,Balance of Trade AUG,1.94B,0.74B,0.43B,0.6B +Tuesday,10/05/21,7:30,US,Balance of Trade AUG,-73.3B,-70.3B,-70.5B,-70.8B +Thursday,10/07/21,9:00,CA,Ivey PMI s.a SEP,70.4,66,,64.2 +Friday,10/08/21,7:30,US,Non Farm Payrolls SEP,194K,366K,500K,475K +Tuesday,10/12/21,1:00,GB,Claimant Count Change SEP,-51.1K,-58.6K,,-46K +Tuesday,10/12/21,9:00,US,JOLTs Job Openings AUG,10.439M,11.098M,10.925M,10.8M +Tuesday,10/12/21,22:00,CN,Exports YoY SEP,0.281,25.60%,0.21,0.21 +Tuesday,10/12/21,22:00,CN,Imports YoY SEP,0.176,33.10%,0.2,0.21 +Wednesday,10/13/21,1:00,GB,Balance of Trade AUG,-3.7B,-2.9B,,-2.8B +Wednesday,10/13/21,7:30,US,Core Inflation Rate YoY SEP,0.04,4%,0.04,0.04 +Wednesday,10/13/21,7:30,US,Inflation Rate YoY SEP,0.054,5.30%,0.053,0.053 +Wednesday,10/13/21,13:00,US,FOMC Minutes,,,, +Wednesday,10/13/21,20:30,CN,Inflation Rate YoY SEP,0.007,0.80%,0.009,0.008 +Friday,10/15/21,7:30,US,Retail Sales MoM SEP,0.007,0.90%,-0.002,-0.001 +Friday,10/15/21,9:00,US,Michigan Consumer Sentiment Prel OCT,71.4,72.8,73.1,75 +Sunday,10/17/21,21:00,CN,Industrial Production YoY SEP,0.031,5.30%,0.045,0.044 +Sunday,10/17/21,21:00,CN,Retail Sales YoY SEP,0.044,2.50%,0.033,0.023 +Tuesday,10/19/21,7:30,US,Building Permits SEP,1.589M,1.721M,1.68M,1.69M +Tuesday,10/19/21,18:50,JP,Balance of Trade SEP,-622.8B,-637.2B,-519.2B, -500B +Tuesday,10/19/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385 +Wednesday,10/20/21,1:00,GB,Inflation Rate YoY SEP,0.031,3.20%,0.032,0.032 +Wednesday,10/20/21,7:30,CA,Inflation Rate YoY SEP,0.044,4.10%,0.043,0.044 +Thursday,10/21/21,18:01,GB,Gfk Consumer Confidence OCT,-17,-13,-16,-14 +Thursday,10/21/21,18:30,JP,Inflation Rate YoY SEP,0.002,-0.40%,,-0.003 +Friday,10/22/21,1:00,GB,Retail Sales MoM SEP,-0.002,-0.60%,0.005,0.005 +Friday,10/22/21,3:00,EA,Markit Composite PMI Flash OCT,54.3,56.2,55.2,55.4 +Friday,10/22/21,3:30,GB,Markit/CIPS Composite PMI Flash OCT,56.8,54.9,54,54.2 +Wednesday,10/27/21,6:30,GB,Autumn Budget,,,, +Wednesday,10/27/21,7:30,US,Durable Goods Orders MoM SEP,-0.004,1.30%,-0.011,-0.008 +Friday,10/29/21,0:00,JP,Consumer Confidence OCT,39.2,37.8,,39 +Friday,10/29/21,4:00,EA,Inflation Rate YoY Flash OCT,0.041,3.40%,0.037,0.036 +Friday,10/29/21,7:30,US,Personal Income MoM SEP,-0.01,0.20%,-0.002,0.002 +Friday,10/29/21,7:30,US,Personal Spending MoM SEP,0.006,1%,0.005,0.006 +Saturday,10/30/21,20:00,CN,NBS Manufacturing PMI OCT,49.2,49.6,49.7,50 +Sunday,10/31/21,20:45,CN,Caixin Manufacturing PMI OCT,50.6,50,50,50 +Monday,11/01/21,9:00,US,ISM Manufacturing PMI OCT,60.8,61.1,60.5,60.3 +Wednesday,11/03/21,13:30,US,Fed Press Conference,,,, +Thursday,11/04/21,7:30,CA,Balance of Trade SEP,1.86B,1.51B,1.55B, 2.1B +Thursday,11/04/21,7:30,US,Balance of Trade SEP,-80.9B,-72.8B,-80.5B, -75B +Friday,11/05/21,7:30,US,Non Farm Payrolls OCT,531K,312K,450K,400K +Friday,11/05/21,9:00,CA,Ivey PMI s.a OCT,59.3,70.4,,65 +Saturday,11/06/21,22:00,CN,Exports YoY OCT,0.271,28.10%,0.245,0.25 +Saturday,11/06/21,22:00,CN,Imports YoY OCT,0.206,17.60%,0.25,0.26 +Tuesday,11/09/21,8:30,US,PPI MoM OCT,0.006,0.50%,0.006,0.006 +Tuesday,11/09/21,20:30,CN,Inflation Rate YoY OCT,0.015,0.70%,0.014,0.012 +Wednesday,11/10/21,8:30,US,Core Inflation Rate YoY OCT,0.046,4%,0.043,0.041 +Wednesday,11/10/21,8:30,US,Inflation Rate YoY OCT,0.062,5.40%,0.058,0.057 +Thursday,11/11/21,2:00,GB,Balance of Trade SEP,-2.8B,-1.9B,,-3.4B +Thursday,11/11/21,5:00,EA,ECB Macroeconomic Projections,,,, +Friday,11/12/21,10:00,US,JOLTs Job Openings SEP,10.438M,10.629M,10.3M,10.1M +Friday,11/12/21,10:00,US,Michigan Consumer Sentiment Prel NOV,66.8,71.7,72.4,71 +Sunday,11/14/21,21:00,CN,Industrial Production YoY OCT,0.035,3.10%,0.03,0.029 +Sunday,11/14/21,21:00,CN,Retail Sales YoY OCT,0.049,4.40%,0.035,0.036 +Sunday,11/14/21,,US,President Biden and President Xi Jinping Virtual Meeting,,,, +Tuesday,11/16/21,2:00,GB,Claimant Count Change OCT,-14.9K,-51.1K,,-30K +Tuesday,11/16/21,8:30,US,Retail Sales MoM OCT,0.017,0.80%,0.014,0.012 +Tuesday,11/16/21,18:50,JP,Balance of Trade OCT,-67.4B,-624.1B,-310B,-460B +Wednesday,11/17/21,2:00,GB,Inflation Rate YoY OCT,0.042,3.10%,0.039,0.037 +Wednesday,11/17/21,8:30,CA,Inflation Rate YoY OCT,0.047,4.40%,0.047,0.049 +Wednesday,11/17/21,8:30,US,Building Permits OCT,1.65M,1.586M,1.638M,1.661M +Thursday,11/18/21,18:30,JP,Inflation Rate YoY OCT,0.001,0.20%,,0.001 +Thursday,11/18/21,19:01,GB,GfK Consumer Confidence NOV,-14,-17,-18,-16 +Friday,11/19/21,2:00,GB,Retail Sales MoM OCT,0.008,0%,0.005,0.007 +Sunday,11/21/21,20:30,CN,Loan Prime Rate 1Y,0.0385,3.85%,,0.0385 +Tuesday,11/23/21,4:00,EA,Markit Composite PMI Flash NOV,55.8,54.2,53.2,53.7 +Tuesday,11/23/21,4:30,GB,Markit/CIPS Composite PMI Flash NOV,57.7,57.8,57.5,57.3 +Tuesday,11/23/21,9:45,US,Markit Manufacturing PMI Flash NOV,59.1,58.4,59,58.8 +Tuesday,11/23/21,9:45,US,Markit Services PMI Flash NOV,57,58.7,59,59 +Wednesday,11/24/21,8:30,US,Durable Goods Orders MoM OCT,-0.005,-0.40%,0.002,0.003 +Wednesday,11/24/21,10:00,US,Personal Income MoM OCT,0.005,-1%,0.002,0.001 +Wednesday,11/24/21,10:00,US,Personal Spending MoM OCT,0.013,0.60%,0.01,0.007 +Wednesday,11/24/21,14:00,US,FOMC Minutes,,,, +Monday,11/29/21,15:05,US,Fed Chair Powell Speech ,,,, +Monday,11/29/21,20:00,CN,NBS Manufacturing PMI NOV,50.1,49.2,49.6,49.8 +Tuesday,11/30/21,5:00,EA,Inflation Rate YoY Flash NOV,0.049,4.10%,0.045,0.045 +Tuesday,11/30/21,10:00,US,Fed Chair Powell Testimony,,,, +Tuesday,11/30/21,20:45,CN,Caixin Manufacturing PMI NOV,49.9,50.6,50.5,50.2 +Wednesday,12/01/21,10:00,US,ISM Manufacturing PMI NOV,61.1,60.8,61,61.2 +Thursday,12/02/21,0:00,JP,Consumer Confidence NOV,39.2,39.2,,40 +Friday,12/03/21,8:30,US,Non Farm Payrolls NOV,210K,546K,550K,550K +Friday,12/03/21,10:00,US,ISM Non-Manufacturing PMI NOV,69.1,66.7,65,65 +Monday,12/06/21,22:00,CN,Exports YoY NOV,0.22,27.10%,0.19,0.16 +Monday,12/06/21,22:00,CN,Imports YoY NOV,0.317,20.60%,0.198,0.21 +Tuesday,12/07/21,8:30,CA,Balance of Trade OCT,2.1B,1.4B,2B,3B +Tuesday,12/07/21,8:30,US,Balance of Trade OCT,-67.1B,-81.4B,-66.8B,-66B +Tuesday,12/07/21,10:00,CA,Ivey PMI s.a NOV,61.2,59.3,,58.7 +Wednesday,12/08/21,10:00,US,JOLTs Job Openings OCT,11M,10.602M,10.369M,10.4M +Wednesday,12/08/21,20:30,CN,Inflation Rate YoY NOV,0.023,1.50%,0.025,0.026 +Friday,12/10/21,2:00,GB,Balance of Trade OCT,-2.027B,-2.8B,,-3.2B +Friday,12/10/21,2:00,GB,GDP MoM OCT,0.001,0.60%,0.004,0.004 +Friday,12/10/21,2:00,GB,GDP YoY OCT,0.046,5.30%,0.049,0.051 +Friday,12/10/21,8:30,US,Core Inflation Rate YoY NOV,0.049,4.60%,0.049,0.049 +Friday,12/10/21,8:30,US,Inflation Rate YoY NOV,0.068,6.20%,0.068,0.069 +Friday,12/10/21,10:00,US,Michigan Consumer Sentiment Prel DEC,70.4,67.4,67.1,67 +Sunday,12/12/21,18:50,JP,Tankan Large Manufacturers Index Q4,18,18,19,20 +Tuesday,12/14/21,2:00,GB,Claimant Count Change NOV,-49.8K,-14.9K,,-20K +Tuesday,12/14/21,21:00,CN,Industrial Production YoY NOV,0.038,3.50%,0.036,0.034 +Tuesday,12/14/21,21:00,CN,Retail Sales YoY NOV,0.039,4.90%,0.046,0.048 +Wednesday,12/15/21,2:00,GB,Inflation Rate YoY NOV,0.051,4.20%,0.047,0.05 +Wednesday,12/15/21,8:30,CA,Inflation Rate YoY NOV,0.047,4.70%,0.047,0.049 +Wednesday,12/15/21,8:30,US,Retail Sales MoM NOV,0.003,1.80%,0.008,0.01 +Wednesday,12/15/21,14:30,US,Fed Press Conference,,,, +Wednesday,12/15/21,18:50,JP,Balance of Trade NOV,-954.8B,-68.5B,-675B,-700B +Thursday,12/16/21,4:00,EA,Markit Composite PMI Flash DEC,53.4,55.4,54,54.2 +Thursday,12/16/21,4:30,GB,Markit/CIPS Composite PMI Flash DEC,53.2,57.6,56.4,56.5 +Thursday,12/16/21,7:00,GB,BoE Quantitative Easing,875B,875B,875B,875B +Thursday,12/16/21,8:30,US,Building Permits NOV,1.712M,1.653M,1.663M,1.63M +Thursday,12/16/21,9:45,US,Markit Manufacturing PMI Flash DEC,57.8,58.3,58.5,58.5 +Thursday,12/16/21,9:45,US,Markit Services PMI Flash DEC,57.5,58,58.5,58.2 +Thursday,12/16/21,19:01,GB,GfK Consumer Confidence DEC,-15,-14,,-16 +Friday,12/17/21,2:00,GB,Retail Sales MoM NOV,0.014,1.10%,0.008,0.01 +Sunday,12/19/21,20:30,CN,Loan Prime Rate 1Y,0.038,3.85%,,0.0385 +Thursday,12/23/21,8:30,US,Durable Goods Orders MoM NOV,0.025,0.10%,0.016,0.011 +Thursday,12/23/21,8:30,US,Personal Income MoM NOV,0.004,0.50%,0.004,0.003 +Thursday,12/23/21,8:30,US,Personal Spending MoM NOV,0.006,1.40%,0.006,0.005 +Thursday,12/23/21,18:30,JP,Inflation Rate YoY NOV,0.006,0.10%,,0.004 +Thursday,12/30/21,20:00,CN,NBS Manufacturing PMI DEC,50.3,50.1,50,50.5 +Monday,01/03/22,20:45,CN,Caixin Manufacturing PMI DEC,50.9,49.9,50,50.1 +Tuesday,01/04/22,10:00,US,ISM Manufacturing PMI DEC,58.7,61.1,60,60.2 +Tuesday,01/04/22,10:00,US,JOLTs Job Openings NOV,10.562M,11.033M,11.075M,10.8M +Wednesday,01/05/22,0:00,JP,Consumer Confidence DEC,39.1,39.2,,39.8 +Wednesday,01/05/22,14:00,US,FOMC Minutes,,,, +Thursday,01/06/22,8:30,CA,Balance of Trade NOV,3.13B,2.26B,2.03B,1.8B +Thursday,01/06/22,8:30,US,Balance of Trade NOV,-80.2B,-67.2B,-77.1B,-81.8B +Thursday,01/06/22,10:00,US,ISM Non-Manufacturing PMI DEC,62,69.1,66.9,67.5 +Friday,01/07/22,5:00,EA,Inflation Rate YoY Flash DEC,0.05,4.90%,0.047,0.051 +Friday,01/07/22,8:30,US,Non Farm Payrolls DEC,199K,249K,400K,425K +Friday,01/07/22,10:00,CA,Ivey PMI s.a DEC,45,61.2,,61 +Tuesday,01/11/22,10:00,US,Fed Chair Powell Testimony,,,, +Tuesday,01/11/22,20:30,CN,Inflation Rate YoY DEC,0.015,2.30%,0.018,0.02 +Wednesday,01/12/22,8:30,US,Core Inflation Rate YoY DEC,0.055,4.90%,0.054,0.054 +Wednesday,01/12/22,8:30,US,Inflation Rate YoY DEC,0.07,6.80%,0.07,0.071 +Thursday,01/13/22,22:00,CN,Exports YoY DEC,0.209,22%,0.2,0.21 +Thursday,01/13/22,22:00,CN,Imports YoY DEC,0.195,31.70%,0.263,0.27 +Friday,01/14/22,2:00,GB,Balance of Trade NOV,0.626B,0.151B,,-2.7B +Friday,01/14/22,2:00,GB,GDP MoM NOV,0.009,0.20%,0.004,0.003 +Friday,01/14/22,8:30,US,Retail Sales MoM DEC,-0.019,0.20%,0,0.003 +Friday,01/14/22,10:00,US,Michigan Consumer Sentiment Prel JAN,68.8,70.6,70,70.4 +Sunday,01/16/22,21:00,CN,Industrial Production YoY DEC,0.043,3.80%,0.036,0.037 +Sunday,01/16/22,21:00,CN,Retail Sales YoY DEC,0.017,3.90%,0.037,0.037 +Tuesday,01/18/22,2:00,GB,Claimant Count Change DEC,-43.3K,-95.1K,,-36K +Wednesday,01/19/22,2:00,GB,Inflation Rate YoY DEC,0.054,5.10%,0.052,0.052 +Wednesday,01/19/22,8:30,CA,Inflation Rate YoY DEC,0.048,4.70%,0.048,0.048 +Wednesday,01/19/22,8:30,US,Building Permits DEC,1.873M,1.717M,1.701M,1.72M +Wednesday,01/19/22,18:50,JP,Balance of Trade DEC,-582.4B,-955.6B,-784.1B, -700B +Wednesday,01/19/22,20:15,CN,Loan Prime Rate 1Y,0.037,3.80%,,0.038 +Thursday,01/20/22,18:30,JP,Inflation Rate YoY DEC,0.008,0.60%,,0.007 +Thursday,01/20/22,19:01,GB,Gfk Consumer Confidence JAN,-19,-15,-15,-18 +Friday,01/21/22,2:00,GB,Retail Sales MoM DEC,-0.037,1%,-0.006,-0.006 +Sunday,01/23/22,19:30,JP,Jibun Bank Composite PMI Flash JAN,48.8,52.5,,52.1 +Monday,01/24/22,4:00,EA,Markit Composite PMI Flash JAN,52.4,53.3,52.6,52.6 +Monday,01/24/22,4:30,GB,Markit/CIPS Composite PMI Flash JAN,53.4,53.6,55,54 +Monday,01/24/22,9:45,US,Markit Composite PMI Flash JAN,50.8,57,,56.7 +Wednesday,01/26/22,10:00,CA,BoC Monetary Policy Report,,,, +Wednesday,01/26/22,14:30,US,Fed Press Conference,,,, +Thursday,01/27/22,8:30,US,Durable Goods Orders MoM DEC,-0.009,3.20%,-0.005,-0.002 +Friday,01/28/22,8:30,US,Personal Income MoM DEC,0.003,0.50%,0.005,0.005 +Friday,01/28/22,8:30,US,Personal Spending MoM DEC,-0.006,0.40%,-0.006,-0.003 +Saturday,01/29/22,20:45,CN,Caixin Manufacturing PMI JAN,49.1,50.9,50.4,50.6 +Saturday,01/29/22,20:45,CN,NBS Manufacturing PMI JAN,50.1,50.3,50,50.1 +Monday,01/31/22,0:00,JP,Consumer Confidence JAN,36.7,39.1,,39.5 +Tuesday,02/01/22,10:00,US,ISM Manufacturing PMI JAN,57.6,58.8,57.5,58 +Tuesday,02/01/22,10:00,US,JOLTs Job Openings DEC,10.925M,10.775M,10.3M,10.52M +Wednesday,02/02/22,5:00,EA,Inflation Rate YoY Flash JAN,0.051,5%,0.044,0.045 +Thursday,02/03/22,10:00,US,ISM Non-Manufacturing PMI JAN,59.9,62.3,59.5,61 +Friday,02/04/22,8:30,US,Non Farm Payrolls JAN,467K,510K,150K,30K +Friday,02/04/22,10:00,CA,Ivey PMI s.a JAN,50.7,45,,50 +Tuesday,02/08/22,8:30,CA,Balance of Trade DEC,-0.14B,2.47B,2.5B, 1.5B +Tuesday,02/08/22,8:30,US,Balance of Trade DEC,-80.7B,-79.3B,-83B,-83.2B +Thursday,02/10/22,8:30,US,Core Inflation Rate YoY JAN,0.06,5.50%,0.059,0.057 +Thursday,02/10/22,8:30,US,Inflation Rate YoY JAN,0.075,7%,0.073,0.071 +Friday,02/11/22,2:00,GB,Balance of Trade DEC,-2.34B,-2.59B,, -3.1B +Friday,02/11/22,2:00,GB,GDP MoM DEC,-0.002,0.70%,-0.006,-0.002 +Friday,02/11/22,2:00,GB,GDP YoY DEC,0.06,7.50%,0.063,0.067 +Friday,02/11/22,10:00,US,Michigan Consumer Sentiment Prel FEB,61.7,67.2,67.5,67.5 +Tuesday,02/15/22,2:00,GB,Claimant Count Change JAN,-31.9K,-43.3K,-28K,-27K +Tuesday,02/15/22,20:30,CN,Inflation Rate YoY JAN,0.009,1.50%,0.01,0.014 +Wednesday,02/16/22,2:00,GB,Inflation Rate YoY JAN,0.055,5.40%,0.054,0.055 +Wednesday,02/16/22,8:30,CA,Inflation Rate YoY JAN,0.051,4.80%,0.048,0.05 +Wednesday,02/16/22,8:30,US,Retail Sales MoM JAN,0.038,-2.50%,0.02,0.015 +Wednesday,02/16/22,14:00,US,FOMC Minutes,,,, +Wednesday,02/16/22,18:50,JP,Balance of Trade JAN,-2191.1B,-583.3B,-1607B,-1800B +Thursday,02/17/22,8:30,US,Building Permits JAN,1.899M,1.885M,1.76M,1.79M +Thursday,02/17/22,18:30,JP,Inflation Rate YoY JAN,0.005,0.80%,,0.009 +Friday,02/18/22,2:00,GB,Retail Sales MoM JAN,0.019,-4%,0.01,0.009 +Sunday,02/20/22,20:15,CN,Loan Prime Rate 1Y,0.037,3.70%,0.037,0.037 +Monday,02/21/22,4:30,GB,Markit/CIPS Manufacturing PMI Flash FEB,57.3,57.3,57.2,57.6 +Monday,02/21/22,4:30,GB,Markit/CIPS UK Services PMI Flash FEB,60.8,54.1,55.5,55 +Thursday,02/24/22,19:01,GB,Gfk Consumer Confidence FEB,-26,-19,-18,-16 +Friday,02/25/22,8:30,US,Durable Goods Orders MoM JAN,0.016,1.20%,0.008,0.004 +Friday,02/25/22,8:30,US,Personal Income MoM JAN,0,0.40%,-0.003,0.001 +Friday,02/25/22,8:30,US,Personal Spending MoM JAN,0.021,-0.80%,0.015,0.007 +Monday,02/28/22,20:30,CN,NBS Manufacturing PMI FEB,50.2,50.1,49.9,50.4 +Monday,02/28/22,20:45,CN,Caixin Manufacturing PMI FEB,50.4,49.1,49.3,49.3 +Tuesday,03/01/22,10:00,US,ISM Manufacturing PMI FEB,58.6,57.6,58,58.1 +Wednesday,03/02/22,5:00,EA,Inflation Rate YoY Flash FEB,0.058,5.10%,0.054,0.052 +Thursday,03/03/22,0:00,JP,Consumer Confidence FEB,35.3,36.7,,36 +Thursday,03/03/22,10:00,US,Fed Chair Powell Testimony,,,, +Thursday,03/03/22,10:00,US,ISM Non-Manufacturing PMI FEB,56.5,59.9,61,61 +Friday,03/04/22,8:30,US,Non Farm Payrolls FEB,678K,481K,400K,350K +Friday,03/04/22,10:00,CA,Ivey PMI s.a FEB,60.6,50.7,,52 +Sunday,03/06/22,22:00,CN,Balance of Trade JAN-FEB,115.95B,94.46B,99.5B,120B +Tuesday,03/08/22,8:30,CA,Balance of Trade JAN,2.62B,-1.58B,1.6B,1.3B +Tuesday,03/08/22,8:30,US,Balance of Trade JAN,-89.7B,-82B,-87.1B,-84B +Tuesday,03/08/22,20:30,CN,Inflation Rate YoY FEB,0.009,0.90%,0.009,0.009 +Wednesday,03/09/22,10:00,US,JOLTs Job Openings JAN,11.263M,11.448M,10.925M,10.8M +Thursday,03/10/22,8:30,US,Core Inflation Rate YoY FEB,0.064,6%,0.064,0.064 +Thursday,03/10/22,8:30,US,Inflation Rate YoY FEB,0.079,7.50%,0.079,0.079 +Friday,03/11/22,2:00,GB,GDP MoM JAN,0.008,-0.20%,0.002,0.003 +Friday,03/11/22,10:00,US,Michigan Consumer Sentiment Prel MAR,59.7,62.8,61.4,62 +Monday,03/14/22,21:00,CN,Industrial Production YoY JAN-FEB,0.075,4.30%,0.039,0.038 +Tuesday,03/15/22,2:00,GB,Claimant Count Change FEB,-48.1K,-67.3K,,-25K +Tuesday,03/15/22,7:30,US,PPI MoM FEB,0.008,1.20%,0.009,0.011 +Tuesday,03/15/22,18:50,JP,Balance of Trade FEB,-668.3B,-2193.5B,-112.6B,-150B +Wednesday,03/16/22,7:30,CA,Inflation Rate YoY FEB,0.057,5.10%,0.055,0.054 +Wednesday,03/16/22,7:30,US,Retail Sales MoM FEB,0.003,4.90%,0.004,0.007 +Wednesday,03/16/22,13:30,US,Fed Press Conference,,,, +Thursday,03/17/22,7:30,US,Building Permits FEB,1.859M,1.895M,1.85M,1.86M +Thursday,03/17/22,18:30,JP,Inflation Rate YoY FEB,0.009,0.50%,,0.007 +Wednesday,03/23/22,2:00,GB,Inflation Rate YoY FEB,0.062,5.50%,0.059,0.061 +Thursday,03/24/22,4:30,GB,Markit/CIPS Manufacturing PMI Flash MAR,55.5,58,56.7,57.1 +Thursday,03/24/22,4:30,GB,Markit/CIPS UK Services PMI Flash MAR,61,60.5,58,58.8 +Thursday,03/24/22,7:30,US,Durable Goods Orders MoM FEB,-0.022,1.60%,-0.005,-0.005 +Thursday,03/24/22,19:01,GB,Gfk Consumer Confidence MAR,-31,-26,-30,-35 +Friday,03/25/22,2:00,GB,Retail Sales MoM FEB,-0.003,1.90%,0.006,0.007 +Tuesday,03/29/22,9:00,US,JOLTs Job Openings FEB,11.266M,11.283M,11M,11.1M +Wednesday,03/30/22,20:30,CN,NBS Manufacturing PMI MAR,49.5,50.2,49.9,49.1 +Thursday,03/31/22,7:30,US,Personal Income MoM FEB,0.005,0.10%,0.005,0.006 +Thursday,03/31/22,7:30,US,Personal Spending MoM FEB,0.002,2.70%,0.005,0.004 +Thursday,03/31/22,18:50,JP,Tankan Large Manufacturers Index Q1,14,18,12,13 +Thursday,03/31/22,20:45,CN,Caixin Manufacturing PMI MAR,48.1,50.4,50,49.1 +Friday,04/01/22,4:00,EA,Inflation Rate YoY Flash MAR,0.075,5.90%,0.066,0.069 +Friday,04/01/22,7:30,US,Non Farm Payrolls MAR,431K,750K,490K,460K +Friday,04/01/22,9:00,US,ISM Manufacturing PMI MAR,57.1,58.6,59,58.5 +Tuesday,04/05/22,7:30,CA,Balance of Trade FEB,2.66B,3.12B,2.9B,2.4B +Tuesday,04/05/22,7:30,US,Balance of Trade FEB,-89.2B,-89.2B,-88.5B,-88B +Tuesday,04/05/22,9:00,US,ISM Non-Manufacturing PMI MAR,58.3,56.5,58.4,58.1 +Wednesday,04/06/22,9:00,CA,Ivey PMI s.a MAR,74.2,60.6,60,61 +Wednesday,04/06/22,13:00,US,FOMC Minutes,,,, +Friday,04/08/22,0:00,JP,Consumer Confidence MAR,32.8,35.3,,34 +Sunday,04/10/22,20:30,CN,Inflation Rate YoY MAR,0.015,0.90%,0.012,0.012 +Monday,04/11/22,1:00,GB,GDP MoM FEB,0.001,0.80%,0.003,0.005 +Tuesday,04/12/22,1:00,GB,Claimant Count Change MAR,-46.9K,-58K,,-31K +Tuesday,04/12/22,7:30,US,Core Inflation Rate YoY MAR,0.065,6.40%,0.066,0.067 +Tuesday,04/12/22,7:30,US,Inflation Rate YoY MAR,0.085,7.90%,0.084,0.083 +Tuesday,04/12/22,23:30,CN,Balance of Trade MAR,47.38B,115.95B,22.4B,25B +Wednesday,04/13/22,1:00,GB,Inflation Rate YoY MAR,0.07,6.20%,0.067,0.07 +Wednesday,04/13/22,7:30,US,PPI MoM MAR,0.014,0.90%,0.011,0.01 +Wednesday,04/13/22,9:00,CA,BoC Monetary Policy Report,,,, +Thursday,04/14/22,7:30,US,Retail Sales MoM MAR,0.005,0.80%,0.006,0.004 +Thursday,04/14/22,9:00,US,Michigan Consumer Sentiment Prel APR,65.7,59.4,59,58.8 +Sunday,04/17/22,21:00,CN,Industrial Production YoY MAR,0.05,7.50%,0.045,0.042 +Tuesday,04/19/22,7:30,US,Building Permits MAR,1.873M,1.865M,1.825M,1.81M +Tuesday,04/19/22,18:50,JP,Balance of Trade MAR,-412.4B,-669.7B,-100.8B, -100B +Wednesday,04/20/22,7:30,CA,Inflation Rate YoY MAR,0.067,5.70%,0.061,0.06 +Thursday,04/21/22,18:30,JP,Inflation Rate YoY MAR,0.012,0.90%,,0.011 +Thursday,04/21/22,21:10,GB,Gfk Consumer Confidence APR,-38,-31,-33,-33 +Friday,04/22/22,1:00,GB,Retail Sales MoM MAR,-0.014,-0.50%,-0.003,-0.001 +Friday,04/22/22,3:30,GB,S&P Global/CIPS Manufacturing PMI Flash APR,55.3,55.2,54,54.8 +Friday,04/22/22,3:30,GB,S&P Global/CIPS UK Services PMI Flash APR,58.3,62.6,60,58.9 +Tuesday,04/26/22,7:30,US,Durable Goods Orders MoM MAR,0.008,-1.70%,0.01,0.011 +Friday,04/29/22,4:00,EA,Inflation Rate YoY Flash APR,0.075,7.40%,0.075,0.074 +Friday,04/29/22,7:30,US,Personal Income MoM MAR,0.005,0.70%,0.004,0.004 +Friday,04/29/22,7:30,US,Personal Spending MoM MAR,0.011,0.60%,0.007,0.005 +Friday,04/29/22,20:30,CN,NBS Manufacturing PMI APR,47.4,49.5,48,49.1 +Friday,04/29/22,20:45,CN,Caixin Manufacturing PMI APR,46,48.1,47,47.9 +Friday,04/29/22,0:00,JP,Consumer Confidence APR,33,32.8,,31.7 +Friday,04/29/22,9:00,US,ISM Manufacturing PMI APR,55.4,57.1,57.6,57.5 +Tuesday,05/03/22,9:00,US,JOLTs Job Openings MAR,11.549M,11.344M,11M,11.27M +Wednesday,05/04/22,7:30,CA,Balance of Trade MAR,2.49B,3.08B,3.9B,2.3B +Wednesday,05/04/22,7:30,US,Balance of Trade MAR,-109.8B,-89.8B,-107B, -92B +Wednesday,05/04/22,9:00,US,ISM Non-Manufacturing PMI APR,57.1,58.3,58.5,58.5 +Wednesday,05/04/22,13:30,US,Fed Press Conference,,,, +Wednesday,05/04/22,7:30,US,Non Farm Payrolls APR,428K,428K,391K,415K +Wednesday,05/04/22,9:00,CA,Ivey PMI s.a APR,66.3,74.2,,73.8 +Wednesday,05/04/22,23:00,CN,Balance of Trade APR,51.12B,47.38B,50.65B,53B +Tuesday,05/10/22,20:30,CN,Inflation Rate YoY APR,0.021,1.50%,0.018,0.018 +Wednesday,05/11/22,7:30,US,Core Inflation Rate YoY APR,0.062,6.50%,0.06,0.062 +Wednesday,05/11/22,7:30,US,Inflation Rate YoY APR,0.083,8.50%,0.081,0.082 +Thursday,05/12/22,1:00,GB,GDP MoM MAR,-0.001,0%,0,0.001 +Thursday,05/12/22,7:30,US,PPI MoM APR,0.005,1.60%,0.005,0.005 +Thursday,05/12/22,9:00,US,Michigan Consumer Sentiment Prel 05,59.1,65.2,64,63.5 +Thursday,05/12/22,21:00,CN,Industrial Production YoY APR,-0.029,5%,0.004,0.004 +Thursday,05/12/22,,EA,European Commission Spring Forecasts,,,, +Tuesday,05/17/22,1:00,GB,Claimant Count Change APR,-56.9K,-81.6K,-42.5K,-42K +Tuesday,05/17/22,7:30,US,Retail Sales MoM APR,0.009,1.40%,0.009,0.006 +Tuesday,05/17/22,13:00,US,Fed Chair Powell Speech ,,,, +Wednesday,05/18/22,1:00,GB,Inflation Rate YoY APR,0.09,7%,0.091,0.089 +Wednesday,05/18/22,7:30,CA,Inflation Rate YoY APR,0.068,6.70%,0.067,0.066 +Wednesday,05/18/22,7:30,US,Building Permits APR,1.819M,1.879M,1.812M,1.82M +Wednesday,05/18/22,18:50,JP,Balance of Trade APR,-839.2B,-414.1B,-1150B,-1000B +Thursday,05/19/22,18:01,GB,Gfk Consumer Confidence 05,-40,-38,-39,-40 +Thursday,05/19/22,18:30,JP,Inflation Rate YoY APR,0.025,1.20%,,0.015 +Thursday,05/19/22,1:00,GB,Retail Sales MoM APR,0.014,-1.20%,-0.002,-0.002 +Tuesday,05/24/22,3:30,GB,S&P Global/CIPS Manufacturing PMI Flash 05,54.6,55.8,55,55.2 +Tuesday,05/24/22,3:30,GB,S&P Global/CIPS UK Services PMI Flash 05,51.8,58.9,57,58.5 +Wednesday,05/25/22,7:30,US,Durable Goods Orders MoM APR,0.004,0.60%,0.006,0.004 +Wednesday,05/25/22,13:00,US,FOMC Minutes,,,, +Wednesday,05/25/22,7:30,US,Personal Income MoM APR,0.004,0.50%,0.005,0.006 +Wednesday,05/25/22,7:30,US,Personal Spending MoM APR,0.009,1.40%,0.007,0.008 +Wednesday,05/25/22,20:30,CN,NBS Manufacturing PMI 05,49.6,47.4,,48.9 +Tuesday,05/31/22,0:00,JP,Consumer Confidence 05,34.1,33,,33.5 +Tuesday,05/31/22,4:00,EA,Inflation Rate YoY Flash 05,0.081,7.40%,0.077,0.076 +Tuesday,05/31/22,20:45,CN,Caixin Manufacturing PMI 05,48.1,46,48,48 +Wednesday,06/01/22,9:00,US,ISM Manufacturing PMI 05,56.1,55.4,54.5,54.8 +Wednesday,06/01/22,9:00,US,JOLTs Job Openings APR,11.4M,11.855M,11.4M,11.4M +Friday,06/03/22,7:30,US,Non Farm Payrolls 05,390K,436K,325K,320K +Friday,06/03/22,9:00,US,ISM Non-Manufacturing PMI 05,55.9,57.1,56.4,55 +Tuesday,06/07/22,7:30,CA,Balance of Trade APR,1.5B,2.28B,2.9B,2.8B +Tuesday,06/07/22,7:30,US,Balance of Trade APR,-87.1B,-107.7B,-89.5B,-91B +Tuesday,06/07/22,9:00,CA,Ivey PMI s.a 05,72,66.3,,64 +Wednesday,06/08/22,22:00,CN,Balance of Trade 05,78.76B,51.12B,58B,50B +Thursday,06/09/22,20:30,CN,Inflation Rate YoY 05,0.021,2.10%,0.022,0.02 +Friday,06/10/22,7:30,US,Core Inflation Rate YoY 05,0.06,6.20%,0.059,0.06 +Friday,06/10/22,7:30,US,Inflation Rate YoY 05,0.086,8.30%,0.083,0.083 +Friday,06/10/22,9:00,US,Michigan Consumer Sentiment Prel JUN,50.2,58.4,58,59 +Monday,06/13/22,1:00,GB,GDP MoM APR,-0.003,-0.10%,0.001,0 +Tuesday,06/14/22,1:00,GB,Claimant Count Change 05,-19.7K,-65.5K,-49.4K,-29K +Tuesday,06/14/22,7:30,US,PPI MoM 05,0.008,0.40%,0.008,0.007 +Tuesday,06/14/22,21:00,CN,Industrial Production YoY 05,0.007,-2.90%,-0.007,-0.008 +Tuesday,06/14/22,,EA,ECB Unscheduled Meeting to Discuss Markets,,,, +Wednesday,06/15/22,7:30,US,Retail Sales MoM 05,-0.003,0.70%,0.002,0.003 +Wednesday,06/15/22,13:30,US,Fed Press Conference,,,, +Wednesday,06/15/22,18:50,JP,Balance of Trade 05,-2384.7B,-842.8B,-2022.6B,-1750B +Thursday,06/16/22,7:30,US,Building Permits 05,1.695M,1.823M,1.785M,1.79M +Wednesday,06/22/22,1:00,GB,Inflation Rate YoY 05,0.091,9%,0.091,0.092 +Wednesday,06/22/22,7:30,CA,Inflation Rate YoY 05,0.077,6.80%,0.074,0.07 +Wednesday,06/22/22,8:30,US,Fed Chair Powell Testimony,,,, +Thursday,06/23/22,3:30,GB,S&P Global/CIPS Manufacturing PMI Flash JUN,53.4,54.6,53.7,54.2 +Thursday,06/23/22,9:00,US,Fed Chair Powell Testimony,,,, +Thursday,06/23/22,18:01,GB,Gfk Consumer Confidence JUN,-41,-40,-40,-42 +Thursday,06/23/22,18:30,JP,Inflation Rate YoY 05,0.025,2.50%,,0.023 +Friday,06/24/22,1:00,GB,Retail Sales MoM 05,-0.005,0.40%,-0.007,-0.003 +Sunday,06/26/22,,EA,ECB Forum on Central Banking,,,, +Monday,06/27/22,7:30,US,Durable Goods Orders MoM 05,0.007,0.40%,0.001,-0.003 +Monday,06/27/22,,EA,ECB Forum on Central Banking,,,, +Tuesday,06/28/22,,EA,ECB Forum on Central Banking,,,, +Wednesday,06/29/22,0:00,JP,Consumer Confidence JUN,32.1,34.1,,33 +Wednesday,06/29/22,8:00,EA,ECB President Lagarde Speech ,,,, +Wednesday,06/29/22,8:00,GB,BoE Gov Bailey Speech ,,,, +Wednesday,06/29/22,8:00,US,Fed Chair Powell Speech ,,,, +Wednesday,06/29/22,20:30,CN,NBS Manufacturing PMI JUN,50.2,49.6,50.5,48.3 +Thursday,06/30/22,7:30,US,Personal Income MoM 05,0.005,0.50%,0.005,0.003 +Thursday,06/30/22,7:30,US,Personal Spending MoM 05,0.002,0.60%,0.004,0.008 +Thursday,06/30/22,8:30,EA,ECB President Lagarde Speech ,,,, +Thursday,06/30/22,18:50,JP,Tankan Large Manufacturers Index Q2,9,14,13,10 +Thursday,06/30/22,20:45,CN,Caixin Manufacturing PMI JUN,51.7,48.1,50.1,50.5 +Friday,07/01/22,4:00,EA,Inflation Rate YoY Flash JUN,0.086,8.10%,0.084,0.083 +Friday,07/01/22,9:00,US,ISM Manufacturing PMI JUN,53,56.1,54.9,55 +Tuesday,07/05/22,3:30,GB,S&P Global/CIPS UK Services PMI Final JUN,54.3,53.4,53.4,53.4 +Wednesday,07/06/22,9:00,US,ISM Non-Manufacturing PMI JUN,55.3,55.9,54.3,55.2 +Wednesday,07/06/22,9:00,US,JOLTs Job Openings 05,11.254M,11.681M,11M,11.3M +Wednesday,07/06/22,13:00,US,FOMC Minutes,,,, +Thursday,07/07/22,7:30,CA,Balance of Trade 05,5.32B,2.17B,2.4B,1.9B +Thursday,07/07/22,7:30,US,Balance of Trade 05,-85.5B,-86.7B,-84.9B,-86B +Thursday,07/07/22,9:00,CA,Ivey PMI s.a JUN,62.2,72,,64 +Friday,07/08/22,7:30,US,Non Farm Payrolls JUN,372K,384K,268K,300K +Friday,07/08/22,20:30,CN,Inflation Rate YoY JUN,0.025,2.10%,0.024,0.023 +Wednesday,07/13/22,1:00,GB,GDP MoM 05,0.005,-0.20%,0,-0.001 +Wednesday,07/13/22,1:30,CN,Balance of Trade JUN,97.94B,78.76B,75.7B,76B +Wednesday,07/13/22,7:30,US,Core Inflation Rate YoY JUN,0.059,6%,0.057,0.058 +Wednesday,07/13/22,7:30,US,Inflation Rate YoY JUN,0.091,8.60%,0.088,0.088 +Wednesday,07/13/22,9:00,CA,BoC Monetary Policy Report,,,, +Thursday,07/14/22,7:30,US,PPI MoM JUN,0.011,0.90%,0.008,0.009 +Thursday,07/14/22,21:00,CN,Industrial Production YoY JUN,0.039,0.70%,0.041,0.031 +Friday,07/15/22,7:30,US,Retail Sales MoM JUN,0.01,-0.10%,0.008,0.005 +Friday,07/15/22,9:00,US,Michigan Consumer Sentiment Prel JUL,51.1,50,49.9,49.3 +Tuesday,07/19/22,1:00,GB,Claimant Count Change JUN,-20.1K,-34.7K,,-25K +Tuesday,07/19/22,7:30,US,Building Permits JUN,1.685M,1.695M,1.65M,1.68M +Wednesday,07/20/22,1:00,GB,Inflation Rate YoY JUN,0.094,9.10%,0.093,0.095 +Wednesday,07/20/22,7:30,CA,Inflation Rate YoY JUN,0.081,7.70%,0.084,0.08 +Wednesday,07/20/22,18:50,JP,Balance of Trade JUN,-1383.8B,-2385.8B,-1509.7B,-2500B +Thursday,07/21/22,18:01,GB,Gfk Consumer Confidence JUL,-41,-41,-42,-44 +Thursday,07/21/22,18:30,JP,Inflation Rate YoY JUN,0.024,2.50%,,0.026 +Friday,07/22/22,1:00,GB,Retail Sales MoM JUN,-0.001,-0.80%,-0.003,-0.002 +Friday,07/22/22,3:30,GB,S&P Global/CIPS Manufacturing PMI Flash JUL,52.2,52.8,52,51.9 +Wednesday,07/27/22,7:30,US,Durable Goods Orders MoM JUN,0.019,0.80%,-0.005,-0.003 +Wednesday,07/27/22,13:30,US,Fed Press Conference,,,, +Friday,07/29/22,0:00,JP,Consumer Confidence JUL,30.2,32.1,,33 +Friday,07/29/22,4:00,EA,Inflation Rate YoY Flash JUL,0.089,8.60%,0.086,0.09 +Friday,07/29/22,7:30,US,Personal Income MoM JUN,0.006,0.60%,0.005,0.005 +Friday,07/29/22,7:30,US,Personal Spending MoM JUN,0.011,0.30%,0.009,0.006 +Saturday,07/30/22,20:30,CN,NBS Manufacturing PMI JUL,49,50.2,50.4,50.9 +Sunday,07/31/22,20:45,CN,Caixin Manufacturing PMI JUL,50.4,51.7,51.5,52 +Monday,08/01/22,9:00,US,ISM Manufacturing PMI JUL,52.8,53,52,52.2 +Tuesday,08/02/22,9:00,US,JOLTs Job Openings JUN,10.698M,11.303M,11M,11M +Wednesday,08/03/22,3:30,GB,S&P Global/CIPS UK Services PMI Final JUL,52.6,54.3,53.3,53.3 +Wednesday,08/03/22,9:00,US,ISM Non-Manufacturing PMI JUL,56.7,55.3,53.5,52.5 +Thursday,08/04/22,7:30,CA,Balance of Trade JUN,5.05B,4.77B,4.8B,6B +Thursday,08/04/22,7:30,US,Balance of Trade JUN,-79.6B,-84.9B,-80.1B, -83B +Friday,08/05/22,7:30,US,Non Farm Payrolls JUL,528K,398K,250K,290K +Friday,08/05/22,9:00,CA,Ivey PMI s.a JUL,49.6,62.2,,61 +Saturday,08/06/22,22:00,CN,Balance of Trade JUL,101.26B,97.94B,90B,99B +Tuesday,08/09/22,20:30,CN,Inflation Rate YoY JUL,0.027,2.50%,0.029,0.025 +Wednesday,08/10/22,7:30,US,Core Inflation Rate YoY JUL,0.059,5.90%,0.061,0.059 +Wednesday,08/10/22,7:30,US,Inflation Rate YoY JUL,0.085,9.10%,0.087,0.091 +Thursday,08/11/22,7:30,US,PPI MoM JUL,-0.005,1%,0.002,0.004 +Friday,08/12/22,1:00,GB,GDP MoM JUN,-0.006,0.40%,-0.013,-0.013 +Friday,08/12/22,9:00,US,Michigan Consumer Sentiment Prel AUG,55.1,51.5,52.5,51.3 +Sunday,08/14/22,21:00,CN,Industrial Production YoY JUL,0.038,3.90%,0.046,0.05 +Tuesday,08/16/22,1:00,GB,Claimant Count Change JUL,-10.5K,-26.8K,,-10K +Tuesday,08/16/22,7:30,CA,Inflation Rate YoY JUL,0.076,8.10%,0.076,0.076 +Tuesday,08/16/22,7:30,US,Building Permits JUL,1.674M,1.696M,1.65M,1.67M +Tuesday,08/16/22,18:50,JP,Balance of Trade JUL,-1436.8B,-1398.5B,-1405B,-1300B +Wednesday,08/17/22,1:00,GB,Inflation Rate YoY JUL,0.101,9.40%,0.098,0.099 +Wednesday,08/17/22,7:30,US,Retail Sales MoM JUL,0,0.80%,0.001,0.002 +Wednesday,08/17/22,13:00,US,FOMC Minutes,,,, +Thursday,08/18/22,18:01,GB,Gfk Consumer Confidence AUG,-44,-41,-42,-43 +Thursday,08/18/22,18:30,JP,Inflation Rate YoY JUL,0.026,2.40%,,0.022 +Friday,08/19/22,1:00,GB,Retail Sales MoM JUL,0.003,-0.20%,-0.002,-0.001 +Tuesday,08/23/22,3:30,GB,S&P Global/CIPS Manufacturing PMI Flash AUG,46,52.1,51.1,51.3 +Wednesday,08/24/22,7:30,US,Durable Goods Orders MoM JUL,0,2.20%,0.006,0.008 +Friday,08/26/22,7:30,US,Personal Income MoM JUL,0.002,0.70%,0.006,0.005 +Friday,08/26/22,7:30,US,Personal Spending MoM JUL,0.001,1%,0.004,0.002 +Friday,08/26/22,9:00,US,Fed Chair Powell Speech ,,,, +Tuesday,08/30/22,9:00,US,JOLTs Job Openings JUL,11.239M,11.040M,10.45M,10.5M +Tuesday,08/30/22,20:30,CN,NBS Manufacturing PMI AUG,49.4,49,49.2,48.5 +Wednesday,08/31/22,0:00,JP,Consumer Confidence AUG,32.5,30.2,,31 +Wednesday,08/31/22,4:00,EA,Inflation Rate YoY Flash AUG,0.091,8.90%,0.09,0.091 +Wednesday,08/31/22,20:45,CN,Caixin Manufacturing PMI AUG,49.5,50.4,50.2,50 +Thursday,09/01/22,9:00,US,ISM Manufacturing PMI AUG,52.8,52.8,52,52 +Friday,09/02/22,7:30,US,Non Farm Payrolls AUG,315K,526K,300K,310K +Monday,09/05/22,3:30,GB,S&P Global/CIPS UK Services PMI Final AUG,50.9,52.6,52.5,52.5 +Tuesday,09/06/22,9:00,US,ISM Non-Manufacturing PMI AUG,56.9,56.7,55.1,55 +Tuesday,09/06/22,22:00,CN,Balance of Trade AUG,79.39B,101.26B,92.7B,90B +Wednesday,09/07/22,7:30,CA,Balance of Trade JUL,4.05B,4.88B,3.8B,4.7B +Wednesday,09/07/22,7:30,US,Balance of Trade JUL,-70.7B,-80.9B,-70.3B,-70B +Wednesday,09/07/22,9:00,CA,Ivey PMI s.a AUG,60.9,49.6,,48.8 +Thursday,09/08/22,20:30,CN,Inflation Rate YoY AUG,0.025,2.70%,0.028,0.029 +Monday,09/12/22,1:00,GB,GDP MoM JUL,0.002,-0.60%,0.004,0.001 +Tuesday,09/13/22,1:00,GB,Claimant Count Change AUG,6.3K,-10.5K,,-4K +Tuesday,09/13/22,7:30,US,Core Inflation Rate YoY AUG,0.063,5.90%,0.061,0.059 +Tuesday,09/13/22,7:30,US,Inflation Rate YoY AUG,0.083,8.50%,0.081,0.081 +Wednesday,09/14/22,1:00,GB,Inflation Rate YoY AUG,0.099,10.10%,0.102,0.106 +Wednesday,09/14/22,7:30,US,PPI MoM AUG,-0.001,-0.40%,-0.001,0.001 +Wednesday,09/14/22,18:50,JP,Balance of Trade AUG,-2817.3B,-1436.8B,-2398.2B, +Thursday,09/15/22,7:30,US,Retail Sales MoM AUG,0.003,-0.40%,0,0.001 +Thursday,09/15/22,21:00,CN,Industrial Production YoY AUG,0.042,3.80%,0.038,0.039 +Friday,09/16/22,1:00,GB,Retail Sales MoM AUG,-0.016,0.40%,-0.005,-0.004 +Friday,09/16/22,9:00,US,Michigan Consumer Sentiment Prel SEP,59.5,58.2,60,58.6 +Monday,09/19/22,18:30,JP,Inflation Rate YoY AUG,0.03,2.60%,,0.026 +Tuesday,09/20/22,7:30,CA,Inflation Rate YoY AUG,0.07,7.60%,0.073,0.075 +Tuesday,09/20/22,7:30,US,Building Permits AUG,1.517M,1.685M,1.61M,1.63M +Wednesday,09/21/22,13:30,US,Fed Press Conference,,,, +Thursday,09/22/22,18:01,GB,Gfk Consumer Confidence SEP,-49,-44,-42,-35 +Tuesday,09/27/22,6:00,GB,BoE Pill Speech ,,,, +Tuesday,09/27/22,7:30,US,Durable Goods Orders MoM AUG,-0.002,-0.10%,-0.004,-0.009 +Thursday,09/29/22,20:30,CN,NBS Manufacturing PMI SEP,50.1,49.4,49.6,49.8 +Thursday,09/29/22,20:45,CN,Caixin Manufacturing PMI SEP,48.1,49.5,49.5,49.8 +Friday,09/30/22,0:00,JP,Consumer Confidence SEP,30.8,32.5,,34 +Friday,09/30/22,4:00,EA,Inflation Rate YoY Flash SEP,0.1,9.10%,0.097,0.097 +Friday,09/30/22,7:30,US,Personal Income MoM AUG,0.003,0.30%,0.003,0.002 +Friday,09/30/22,7:30,US,Personal Spending MoM AUG,0.004,-0.20%,0.002,0.002 +Sunday,10/02/22,18:50,JP,Tankan Large Manufacturers Index Q3,8,9,11,10 +Monday,10/03/22,9:00,US,ISM Manufacturing PMI SEP,50.9,52.8,52.2,52.9 +Tuesday,10/04/22,9:00,US,JOLTs Job Openings AUG,10.053M,11.17M,10.775M,11.1M +Wednesday,10/05/22,7:30,CA,Balance of Trade AUG,1.52B,2.37B,3.45B,3.9B +Wednesday,10/05/22,7:30,US,Balance of Trade AUG,-67.4B,-70.5B,-67.7B,-68B +Wednesday,10/05/22,9:00,US,ISM Non-Manufacturing PMI SEP,56.7,56.9,56,56.4 +Thursday,10/06/22,9:00,CA,Ivey PMI s.a SEP,59.5,60.9,,55 +Friday,10/07/22,7:30,US,Non Farm Payrolls SEP,263K,315K,250K,290K +Tuesday,10/11/22,1:00,GB,Claimant Count Change SEP,25.5K,6.3K,,10K +Wednesday,10/12/22,1:00,GB,GDP MoM AUG,-0.003,0.10%,0,0.001 +Wednesday,10/12/22,7:30,US,PPI MoM SEP,0.004,-0.20%,0.002,0 +Wednesday,10/12/22,13:00,US,FOMC Minutes,,,, +Thursday,10/13/22,7:30,US,Core Inflation Rate YoY SEP,0.066,6.30%,0.065,0.064 +Thursday,10/13/22,7:30,US,Inflation Rate YoY SEP,0.082,8.30%,0.081,0.082 +Thursday,10/13/22,20:30,CN,Inflation Rate YoY SEP,0.028,2.50%,0.028,0.027 +Friday,10/14/22,7:30,US,Retail Sales MoM SEP,0,0.40%,0.002,0.002 +Friday,10/14/22,8:30,GB,PM Liz Truss Speech ,,,, +Friday,10/14/22,9:00,US,Michigan Consumer Sentiment Prel OCT,59.8,58.6,59,58.3 +Saturday,10/15/22,,CN,20th National Congress of the Chinese Communist Party,,,, +Sunday,10/16/22,,CN,20th National Congress of the Chinese Communist Party,,,, +Monday,10/17/22,5:15,GB,Chancellor Jeremy Hunt Statement,,,, +Monday,10/17/22,,CN,20th National Congress of the Chinese Communist Party,,,, +Tuesday,10/18/22,,CN,20th National Congress of the Chinese Communist Party,,,, +Wednesday,10/19/22,1:00,GB,Inflation Rate YoY SEP,0.101,9.90%,0.1,0.099 +Wednesday,10/19/22,7:30,CA,Inflation Rate YoY SEP,0.069,7%,0.068,0.068 +Wednesday,10/19/22,7:30,US,Building Permits SEP,1.564M,1.542M,1.53M,1.487M +Wednesday,10/19/22,18:50,JP,Balance of Trade SEP,-2094B,-2820B,-2167.4B,-2100B +Wednesday,10/19/22,,CN,20th National Congress of the Chinese Communist Party,,,, +Thursday,10/20/22,18:01,GB,Gfk Consumer Confidence OCT,-47,-49,-52,-53 +Thursday,10/20/22,18:30,JP,Inflation Rate YoY SEP,0.03,3%,,0.032 +Thursday,10/20/22,,CN,20th National Congress of the Chinese Communist Party,,,, +Friday,10/21/22,1:00,GB,Retail Sales MoM SEP,-0.014,-1.70%,-0.005,-0.003 +Friday,10/21/22,,CN,20th National Congress of the Chinese Communist Party,,,, +Sunday,10/23/22,20:45,CN,Industrial Production YoY SEP,0.063,4.20%,0.045,0.044 +Sunday,10/23/22,21:00,CN,Balance of Trade SEP,84.74B,79.39B,81B,80B +Wednesday,10/26/22,9:00,CA,BoC Monetary Policy Report,,,, +Thursday,10/27/22,7:30,US,Durable Goods Orders MoM SEP,0.004,0.20%,0.006,0.002 +Friday,10/28/22,7:30,US,Personal Income MoM SEP,0.004,0.40%,0.003,0.002 +Friday,10/28/22,7:30,US,Personal Spending MoM SEP,0.006,0.60%,0.004,0.003 +Sunday,10/30/22,20:30,CN,NBS Manufacturing PMI OCT,49.2,50.1,50,50 +Monday,10/31/22,0:00,JP,Consumer Confidence OCT,29.9,30.8,,30 +Monday,10/31/22,5:00,EA,Inflation Rate YoY Flash OCT,0.107,9.90%,0.102,0.104 +Monday,10/31/22,20:45,CN,Caixin Manufacturing PMI OCT,49.2,48.1,49,48.4 +Tuesday,11/01/22,9:00,US,ISM Manufacturing PMI OCT,50.2,50.9,50,50.1 +Tuesday,11/01/22,9:00,US,JOLTs Job Openings SEP,10.717M,10.28M,10M,10.2M +Wednesday,11/02/22,13:30,US,Fed Press Conference,,,, +Thursday,11/03/22,7:30,CA,Balance of Trade SEP,1.14B,0.55B,1.34B, 3.6B +Thursday,11/03/22,7:30,US,Balance of Trade SEP,-73.3B,-65.7B,-72.2B,-72B +Thursday,11/03/22,9:00,US,ISM Non-Manufacturing PMI OCT,54.4,56.7,55.5,54.5 +Friday,11/04/22,7:30,US,Non Farm Payrolls OCT,261K,315K,200K,240K +Friday,11/04/22,9:00,CA,Ivey PMI s.a OCT,50.1,59.5,,57 +Sunday,11/06/22,22:00,CN,Balance of Trade OCT,85.15B,84.74B,95.95B,91B +Tuesday,11/08/22,20:30,CN,Inflation Rate YoY OCT,0.021,2.80%,0.024,0.026 +Thursday,11/10/22,8:30,US,Core Inflation Rate YoY OCT,0.063,6.60%,0.065,0.067 +Thursday,11/10/22,8:30,US,Inflation Rate YoY OCT,0.077,8.20%,0.08,0.081 +Friday,11/11/22,2:00,GB,GDP MoM SEP,-0.006,-0.10%,-0.004,-0.005 +Friday,11/11/22,10:00,US,Michigan Consumer Sentiment Prel NOV,54.7,59.9,59.5,59.3 +Monday,11/14/22,21:00,CN,Industrial Production YoY OCT,0.05,6.30%,0.052,0.056 +Tuesday,11/15/22,2:00,GB,Claimant Count Change OCT,3.3K,3.9K,,27K +Tuesday,11/15/22,8:30,US,PPI MoM OCT,0.002,0.20%,0.004,0.003 +Wednesday,11/16/22,2:00,GB,Inflation Rate YoY OCT,0.111,10.10%,0.107,0.11 +Wednesday,11/16/22,8:30,CA,Inflation Rate YoY OCT,0.069,6.90%,0.069,0.07 +Wednesday,11/16/22,8:30,US,Retail Sales MoM OCT,0.013,0%,0.01,0.009 +Wednesday,11/16/22,18:50,JP,Balance of Trade OCT,-2162.3B,-2094.3B,-1610B,-1400B +Thursday,11/17/22,7:00,GB,UK Autumn Statement,,,, +Thursday,11/17/22,8:30,US,Building Permits Prel OCT,1.526M,1.564M,,1.465M +Thursday,11/17/22,18:30,JP,Inflation Rate YoY OCT,0.037,3%,,0.032 +Thursday,11/17/22,19:01,GB,GfK Consumer Confidence NOV,-44,-47,,-51 +Friday,11/18/22,2:00,GB,Retail Sales MoM OCT,0.006,-1.50%,0.003,-0.001 +Wednesday,11/23/22,8:30,US,Durable Goods Orders MoM OCT,0.01,0.30%,0.004,0.003 +Wednesday,11/23/22,14:00,US,FOMC Minutes,,,, +Tuesday,11/29/22,20:30,CN,NBS Manufacturing PMI NOV,48,49.2,49,49 +Wednesday,11/30/22,5:00,EA,Inflation Rate YoY Flash NOV,0.1,10.60%,0.104,0.103 +Wednesday,11/30/22,10:00,US,JOLTs Job Openings OCT,10.334M,10.687M,10.3M,10.4M +Wednesday,11/30/22,13:30,US,Fed Chair Powell Speech ,,,, +Wednesday,11/30/22,20:45,CN,Caixin Manufacturing PMI NOV,49.4,49.2,48.9,48.4 +Thursday,12/01/22,0:00,JP,Consumer Confidence NOV,28.6,29.9,,29.1 +Thursday,12/01/22,8:30,US,Personal Income MoM OCT,0.007,0.40%,0.004,0.003 +Thursday,12/01/22,8:30,US,Personal Spending MoM OCT,0.008,0.60%,0.008,0.006 +Thursday,12/01/22,10:00,US,ISM Manufacturing PMI NOV,49,50.2,49.8,50 +Friday,12/02/22,8:30,US,Non Farm Payrolls NOV,263K,284K,200K,210K +Monday,12/05/22,10:00,US,ISM Non-Manufacturing PMI NOV,56.5,54.4,53.3,53 +Tuesday,12/06/22,8:30,CA,Balance of Trade OCT,1.21B,0.61B,1.2B,3.4B +Tuesday,12/06/22,8:30,US,Balance of Trade OCT,-78.2B,-74.1B,-80B,-73B +Tuesday,12/06/22,10:00,CA,Ivey PMI s.a NOV,51.4,50.1,,49 +Tuesday,12/06/22,22:00,CN,Balance of Trade NOV,69.84B,85.15B,78.1B,81B +Thursday,12/08/22,20:30,CN,Inflation Rate YoY NOV,0.016,2.10%,0.016,0.018 +Friday,12/09/22,8:30,US,PPI MoM NOV,0.003,0.30%,0.002,0.003 +Friday,12/09/22,10:00,US,Michigan Consumer Sentiment Prel DEC,59.1,56.8,56.9,56.4 +Monday,12/12/22,2:00,GB,GDP MoM OCT,0.005,-0.60%,0.004,0.004 +Tuesday,12/13/22,2:00,GB,Claimant Count Change NOV,30.5K,-6.4K,3.5K,8K +Tuesday,12/13/22,8:30,US,Core Inflation Rate YoY NOV,0.06,6.30%,0.061,0.062 +Tuesday,12/13/22,8:30,US,Inflation Rate YoY NOV,0.071,7.70%,0.073,0.076 +Tuesday,12/13/22,18:50,JP,Tankan Large Manufacturers Index Q4,7,8,6,6 +Wednesday,12/14/22,2:00,GB,Inflation Rate YoY NOV,0.107,11.10%,0.109,0.11 +Wednesday,12/14/22,14:00,US,Fed Interest Rate Decision,0.045,4%,0.045,0.045 +Wednesday,12/14/22,14:30,US,Fed Press Conference,,,, +Wednesday,12/14/22,18:50,JP,Balance of Trade NOV,-2027.4B,-2166.2B,-1680.3B,-1800B +Wednesday,12/14/22,21:00,CN,Industrial Production YoY NOV,0.022,5%,0.036,0.04 +Thursday,12/15/22,7:00,GB,BoE Interest Rate Decision,0.035,3%,0.035,0.035 +Thursday,12/15/22,8:15,EA,Deposit Facility Rate,0.02,1.50%,0.02,0.02 +Thursday,12/15/22,8:15,EA,ECB Interest Rate Decision,0.025,2%,0.025,0.025 +Thursday,12/15/22,8:30,US,Retail Sales MoM NOV,-0.006,1.30%,-0.001,0.002 +Thursday,12/15/22,19:01,GB,GfK Consumer Confidence DEC,-42,-44,-43,-43 +Friday,12/16/22,2:00,GB,Retail Sales MoM NOV,-0.004,0.90%,0.003,0.003 +Monday,12/19/22,22:00,JP,BoJ Interest Rate Decision,-0.001,-0.10%,-0.001,-0.001 +Tuesday,12/20/22,8:30,US,Building Permits Prel NOV,1.342M,1.512M,1.485M,1.48M +Wednesday,12/21/22,8:30,CA,Inflation Rate YoY NOV,0.068,6.90%,0.067,0.067 +Thursday,12/22/22,18:30,JP,Inflation Rate YoY NOV,0.038,3.70%,,0.039 +Friday,12/23/22,8:30,US,Durable Goods Orders MoM NOV,-0.021,0.70%,-0.006,-0.005 +Friday,12/23/22,8:30,US,Personal Income MoM NOV,0.004,0.70%,0.003,0.003 +Friday,12/23/22,8:30,US,Personal Spending MoM NOV,0.001,0.90%,0.002,0.003 +Friday,12/30/22,20:30,CN,NBS Manufacturing PMI DEC,47,48,48,49.5 +Monday,01/02/23,20:45,CN,Caixin Manufacturing PMI DEC,49,49.4,48.8,48 +Wednesday,01/04/23,10:00,US,ISM Manufacturing PMI DEC,48.4,49,48.5,49 +Wednesday,01/04/23,10:00,US,JOLTs Job Openings NOV,10.458M,10.512M,10M,10.1M +Wednesday,01/04/23,14:00,US,FOMC Minutes,,,, +Thursday,01/05/23,0:00,JP,Consumer Confidence DEC,30.3,28.6,,29 +Thursday,01/05/23,8:30,CA,Balance of Trade NOV,-0.04B,0.13B,0.61B,1.3B +Thursday,01/05/23,8:30,US,Balance of Trade NOV,-61.5B,-77.8B,-73B,-72B +Friday,01/06/23,5:00,EA,Inflation Rate YoY Flash DEC,0.092,10.10%,0.097,0.098 +Friday,01/06/23,8:30,US,Non Farm Payrolls DEC,223K,256K,200K,220K +Friday,01/06/23,8:30,US,Unemployment Rate DEC,0.035,3.60%,0.037,0.037 +Friday,01/06/23,10:00,CA,Ivey PMI s.a DEC,33.4,51.4,,51 +Friday,01/06/23,10:00,US,ISM Non-Manufacturing PMI DEC,49.6,56.5,55,53 +Wednesday,01/11/23,20:30,CN,Inflation Rate YoY DEC,0.018,1.60%,0.018,0.02 +Thursday,01/12/23,8:30,US,Core Inflation Rate YoY DEC,0.057,6%,0.057,0.058 +Thursday,01/12/23,8:30,US,Inflation Rate YoY DEC,0.065,7.10%,0.065,0.067 +Thursday,01/12/23,22:00,CN,Balance of Trade DEC,78B,69.25B,76.2B, 80B +Friday,01/13/23,2:00,GB,GDP MoM NOV,0.001,0.50%,-0.002,-0.002 +Friday,01/13/23,10:00,US,Michigan Consumer Sentiment Prel JAN,64.6,59.7,60.5,59 +Monday,01/16/23,21:00,CN,GDP Growth Rate YoY Q4,0.029,3.90%,0.018,0.015 +Monday,01/16/23,21:00,CN,Industrial Production YoY DEC,0.013,2.20%,0.002,0.008 +Tuesday,01/17/23,2:00,GB,Claimant Count Change DEC,19.7K,16.1K,,16K +Tuesday,01/17/23,2:00,GB,Unemployment Rate NOV,0.037,3.70%,0.037,0.037 +Tuesday,01/17/23,8:30,CA,Inflation Rate YoY DEC,0.063,6.80%,0.064,0.064 +Tuesday,01/17/23,22:00,JP,BoJ Interest Rate Decision,-0.001,-0.10%,,-0.001 +Wednesday,01/18/23,2:00,GB,Inflation Rate YoY DEC,0.105,10.70%,0.105,0.105 +Wednesday,01/18/23,8:30,US,PPI MoM DEC,-0.005,0.20%,-0.001,-0.001 +Wednesday,01/18/23,8:30,US,Retail Sales MoM DEC,-0.011,-1%,-0.008,-0.004 +Wednesday,01/18/23,18:50,JP,Balance of Trade DEC,-1448.5B,-2029B,-1652.8B, -1900B +Thursday,01/19/23,8:30,US,Building Permits Prel DEC,1.33M,1.351M,1.37M,1.4M +Thursday,01/19/23,18:30,JP,Inflation Rate YoY DEC,0.04,3.80%,,0.04 +Thursday,01/19/23,19:01,GB,Gfk Consumer Confidence JAN,-45,-42,-40,-38 +Friday,01/20/23,2:00,GB,Retail Sales MoM DEC,-0.01,-0.50%,0.005,0.003 +Wednesday,01/25/23,10:00,CA,BoC Interest Rate Decision,0.045,4.25%,0.045,0.045 +Wednesday,01/25/23,10:00,CA,BoC Monetary Policy Report,,,, +Thursday,01/26/23,8:30,US,Durable Goods Orders MoM DEC,0.056,-1.70%,0.025,0.022 +Thursday,01/26/23,8:30,US,GDP Growth Rate QoQ Adv Q4,0.029,3.20%,0.026,0.027 +Friday,01/27/23,8:30,US,Core PCE Price Index MoM DEC,0.003,0.20%,0.003,0.001 +Friday,01/27/23,8:30,US,Personal Income MoM DEC,0.002,0.30%,0.002,0.003 +Friday,01/27/23,8:30,US,Personal Spending MoM DEC,-0.002,-0.10%,-0.001,-0.001 +Monday,01/30/23,20:30,CN,NBS Manufacturing PMI JAN,50.1,47,49.8,49.5 +Tuesday,01/31/23,0:00,JP,Consumer Confidence JAN,31,30.3,30.5,30 +Tuesday,01/31/23,5:00,EA,GDP Growth Rate QoQ Flash Q4,0.001,0.30%,-0.001,0 +Tuesday,01/31/23,5:00,EA,GDP Growth Rate YoY Flash Q4,0.019,2.30%,0.018,0.016 +Tuesday,01/31/23,20:45,CN,Caixin Manufacturing PMI JAN,49.2,49,49.5,50 +Wednesday,02/01/23,5:00,EA,Inflation Rate YoY Flash JAN,0.085,9.20%,0.09,0.089 +Wednesday,02/01/23,5:00,EA,Unemployment Rate DEC,0.066,6.60%,0.065,0.065 +Wednesday,02/01/23,10:00,US,ISM Manufacturing PMI JAN,47.4,48.4,48,48 +Wednesday,02/01/23,10:00,US,JOLTs Job Openings DEC,11.012M,10.44M,10.25M,9.5M +Wednesday,02/01/23,14:00,US,Fed Interest Rate Decision,0.0475,4.50%,0.0475,0.0475 +Wednesday,02/01/23,14:30,US,Fed Press Conference,,,, +Thursday,02/02/23,7:00,GB,BoE Interest Rate Decision,0.04,3.50%,0.04,0.04 +Thursday,02/02/23,8:15,EA,Deposit Facility Rate,0.025,2%,0.025,0.025 +Thursday,02/02/23,8:15,EA,ECB Interest Rate Decision,0.03,2.50%,0.03,0.03 +Thursday,02/02/23,8:45,EA,ECB Press Conference,,,, +Friday,02/03/23,8:30,US,Non Farm Payrolls JAN,517K,260K,185K,190K +Friday,02/03/23,8:30,US,Unemployment Rate JAN,0.034,3.50%,0.036,0.036 +Friday,02/03/23,10:00,US,ISM Non-Manufacturing PMI JAN,55.2,49.2,50.4,50.6 +Monday,02/06/23,10:00,CA,Ivey PMI s.a JAN,60.1,49.3,42.3,40 +Tuesday,02/07/23,8:30,CA,Balance of Trade DEC,-0.16B,-0.22B,-0.5B,-0.4B +Tuesday,02/07/23,8:30,US,Balance of Trade DEC,-67.4B,-61B,-68.5B,-68.8B +Thursday,02/09/23,20:30,CN,Inflation Rate YoY JAN,0.021,1.80%,0.022,0.02 +Friday,02/10/23,2:00,GB,GDP Growth Rate QoQ Prel Q4,0,-0.20%,0,0.001 +Friday,02/10/23,2:00,GB,GDP Growth Rate YoY Prel Q4,0.004,1.90%,0.004,0.002 +Friday,02/10/23,2:00,GB,GDP MoM DEC,-0.005,0.10%,-0.003,-0.001 +Friday,02/10/23,8:30,CA,Unemployment Rate JAN,0.05,5%,0.051,0.052 +Friday,02/10/23,10:00,US,Michigan Consumer Sentiment Prel FEB,66.4,64.9,65,65 +Monday,02/13/23,18:50,JP,GDP Growth Annualized Prel Q4,0.006,-1%,0.02,0.016 +Monday,02/13/23,18:50,JP,GDP Growth Rate QoQ Prel Q4,0.002,-0.30%,0.005,0.004 +Tuesday,02/14/23,2:00,GB,Claimant Count Change JAN,-12.9K,-3.2K,,25.0K +Tuesday,02/14/23,2:00,GB,Unemployment Rate DEC,0.037,3.70%,0.037,0.038 +Tuesday,02/14/23,8:30,US,Core Inflation Rate YoY JAN,0.056,5.70%,0.055,0.054 +Tuesday,02/14/23,8:30,US,Inflation Rate YoY JAN,0.064,6.50%,0.062,0.063 +Wednesday,02/15/23,2:00,GB,Inflation Rate YoY JAN,0.101,10.50%,0.103,0.103 +Wednesday,02/15/23,8:30,US,Retail Sales MoM JAN,0.03,-1.10%,0.018,0.012 +Wednesday,02/15/23,18:50,JP,Balance of Trade JAN,-3496.6B,-1451.8B,-3871.5B,-2200.0B +Thursday,02/16/23,8:30,US,Building Permits Prel JAN,1.339M,1.337M,1.35M,1.374M +Thursday,02/16/23,8:30,US,PPI MoM JAN,0.007,-0.20%,0.004,0.002 +Friday,02/17/23,2:00,GB,Retail Sales MoM JAN,0.005,-1.20%,-0.003,-0.008 +Tuesday,02/21/23,8:30,CA,Inflation Rate YoY JAN,0.059,6.30%,0.061,0.059 +Wednesday,02/22/23,14:00,US,FOMC Minutes,,,, +Thursday,02/23/23,18:30,JP,Inflation Rate YoY JAN,0.043,4%,,0.042 +Thursday,02/23/23,19:01,GB,Gfk Consumer Confidence FEB,-38,-45,-43,-42 +Friday,02/24/23,8:30,US,Core PCE Price Index MoM JAN,0.006,0.40%,0.004,0.003 +Friday,02/24/23,8:30,US,Personal Income MoM JAN,0.006,0.30%,0.01,0.007 +Friday,02/24/23,8:30,US,Personal Spending MoM JAN,0.018,-0.10%,0.013,0.011 +Monday,02/27/23,8:30,US,Durable Goods Orders MoM JAN,-0.045,5.10%,-0.04,-0.035 +Tuesday,02/28/23,8:30,CA,GDP Growth Rate QoQ Q4,0,0.60%,,0.004 +Tuesday,02/28/23,20:30,CN,NBS Manufacturing PMI FEB,52.6,50.1,50.5,50.8 +Tuesday,02/28/23,20:45,CN,Caixin Manufacturing PMI FEB,51.6,49.2,50.2,50.3 +Wednesday,03/01/23,10:00,US,ISM Manufacturing PMI FEB,47.7,47.4,48,48 +Thursday,03/02/23,0:00,JP,Consumer Confidence FEB,31.1,31,32,32 +Thursday,03/02/23,5:00,EA,Inflation Rate YoY Flash FEB,0.085,8.60%,0.082,0.084 +Thursday,03/02/23,5:00,EA,Unemployment Rate JAN,0.067,6.70%,0.066,0.066 +Friday,03/03/23,10:00,US,ISM Non-Manufacturing PMI FEB,55.1,55.2,54.5,54.6 +Monday,03/06/23,10:00,CA,Ivey PMI s.a FEB,51.6,60.1,55.9,55 +Monday,03/06/23,23:30,CN,Balance of Trade JAN-FEB,116.88B,78B,81.8B,78.2B +Tuesday,03/07/23,10:00,US,Fed Chair Powell Testimony,,,, +Wednesday,03/08/23,8:30,CA,Balance of Trade JAN,1.92B,1.19B,-0.06B,0.1B +Wednesday,03/08/23,8:30,US,Balance of Trade JAN,-68.3B,-67.2B,-68.9B,-69.0B +Wednesday,03/08/23,10:00,CA,BoC Interest Rate Decision,0.045,4.50%,0.045,0.045 +Wednesday,03/08/23,10:00,US,Fed Chair Powell Testimony,,,, +Wednesday,03/08/23,10:00,US,JOLTs Job Openings JAN,10.824M,11.234M,10.5M,10.6M +Wednesday,03/08/23,20:30,CN,Inflation Rate YoY FEB,0.01,2.10%,0.019,0.023 +Thursday,03/09/23,22:00,JP,BoJ Interest Rate Decision,-0.001,-0.10%,-0.001,-0.001 +Friday,03/10/23,2:00,GB,GDP MoM JAN,0.003,-0.50%,0.001,0 +Friday,03/10/23,8:30,CA,Unemployment Rate FEB,0.05,5%,0.051,0.052 +Friday,03/10/23,8:30,US,Non Farm Payrolls FEB,311K,504K,205K,210.0K +Friday,03/10/23,8:30,US,Unemployment Rate FEB,0.036,3.40%,0.034,0.034 +Monday,03/13/23,8:00,US,President Biden Speech on Banking System ,,,, +Monday,03/13/23,10:30,US,Closed-door Fed Emergency Meeting,,,, +Tuesday,03/14/23,2:00,GB,Claimant Count Change FEB,-11.2K,-30.3K,,-27.0K +Tuesday,03/14/23,2:00,GB,Unemployment Rate JAN,0.037,3.70%,0.038,0.038 +Tuesday,03/14/23,7:30,US,Core Inflation Rate YoY FEB,0.055,5.60%,0.055,0.056 +Tuesday,03/14/23,7:30,US,Inflation Rate YoY FEB,0.06,6.40%,0.06,0.061 +Tuesday,03/14/23,21:00,CN,Industrial Production YoY JAN-FEB,0.024,1.30%,0.026,0.025 +Wednesday,03/15/23,7:30,US,PPI MoM FEB,-0.001,0.30%,0.003,0.004 +Wednesday,03/15/23,7:30,US,Retail Sales MoM FEB,-0.004,3.20%,-0.003,-0.002 +Wednesday,03/15/23,18:50,JP,Balance of Trade FEB,-897.7B,-3498.6B,-1069.4B,-1300.0B +Thursday,03/16/23,7:30,US,Building Permits Prel FEB,1.524M,1.339M,1.34M,1.33M +Thursday,03/16/23,8:15,EA,Deposit Facility Rate,0.03,2.50%,0.03,0.03 +Thursday,03/16/23,8:15,EA,ECB Interest Rate Decision,0.035,3%,0.035,0.035 +Thursday,03/16/23,8:45,EA,ECB Press Conference,,,, +Friday,03/17/23,9:00,US,Michigan Consumer Sentiment Prel MAR,63.4,67,67,68 +Tuesday,03/21/23,7:30,CA,Inflation Rate YoY FEB,0.052,5.90%,0.054,0.052 +Wednesday,03/22/23,2:00,GB,Inflation Rate YoY FEB,0.104,10.10%,0.099,0.097 +Wednesday,03/22/23,13:00,US,Fed Interest Rate Decision,0.05,4.75%,0.05,0.05 +Wednesday,03/22/23,13:30,US,Fed Press Conference,,,, +Thursday,03/23/23,7:00,GB,BoE Interest Rate Decision,0.0425,4%,0.0425,0.0425 +Thursday,03/23/23,18:30,JP,Inflation Rate YoY FEB,0.033,4.30%,,0.033 +Thursday,03/23/23,19:01,GB,Gfk Consumer Confidence MAR,-36,-38,-36,-36 +Friday,03/24/23,2:00,GB,Retail Sales MoM FEB,0.012,0.90%,0.002,0.003 +Friday,03/24/23,7:30,US,Durable Goods Orders MoM FEB,-0.01,-5%,0.006,0.007 +Thursday,03/30/23,20:30,CN,NBS Manufacturing PMI MAR,51.9,52.6,51.5,51.2 +Friday,03/31/23,4:00,EA,Inflation Rate YoY Flash MAR,0.069,8.50%,0.071,0.074 +Friday,03/31/23,4:00,EA,Unemployment Rate FEB,0.066,6.60%,0.067,0.067 +Friday,03/31/23,7:30,US,Core PCE Price Index MoM FEB,0.003,0.50%,0.004,0.006 +Friday,03/31/23,7:30,US,Personal Income MoM FEB,0.003,0.60%,0.002,0.004 +Friday,03/31/23,7:30,US,Personal Spending MoM FEB,0.002,2%,0.003,0.005 +Sunday,04/02/23,18:50,JP,Tankan Large Manufacturers Index Q1,1,7,3,1 +Sunday,04/02/23,20:45,CN,Caixin Manufacturing PMI MAR,50,51.6,51.7,52.2 +Monday,04/03/23,9:00,US,ISM Manufacturing PMI MAR,46.3,47.7,47.5,49 +Tuesday,04/04/23,9:00,US,JOLTs Job Openings FEB,9.931M,10.563M,10.4M,10.8M +Wednesday,04/05/23,7:30,CA,Balance of Trade FEB,0.42B,1.2B,1.8B,1.4B +Wednesday,04/05/23,7:30,US,Balance of Trade FEB,-70.5B,-68.7B,-69B,-69.0B +Wednesday,04/05/23,9:00,US,ISM Non-Manufacturing PMI MAR,51.2,55.1,54.5,54 +Thursday,04/06/23,7:30,CA,Unemployment Rate MAR,0.05,5%,0.051,0.052 +Thursday,04/06/23,9:00,CA,Ivey PMI s.a MAR,58.2,51.6,56.1,49 +Friday,04/07/23,7:30,US,Non Farm Payrolls MAR,236K,326K,239K,250.0K +Friday,04/07/23,7:30,US,Unemployment Rate MAR,0.035,3.60%,0.036,0.035 +Monday,04/10/23,0:00,JP,Consumer Confidence MAR,33.9,31.1,31.9,35 +Monday,04/10/23,20:30,CN,Inflation Rate YoY MAR,0.007,1%,0.01,0.02 +Wednesday,04/12/23,7:30,US,Core Inflation Rate YoY MAR,0.056,5.50%,0.056,0.055 +Wednesday,04/12/23,7:30,US,Inflation Rate MoM MAR,0.001,0.40%,0.002,0.003 +Wednesday,04/12/23,7:30,US,Inflation Rate YoY MAR,0.05,6%,0.052,0.053 +Wednesday,04/12/23,9:00,CA,BoC Monetary Policy Report,,,, +Wednesday,04/12/23,13:00,US,FOMC Minutes,,,, +Wednesday,04/12/23,22:00,CN,Balance of Trade MAR,88.19B,116.88B,39.2B, 52.0B +Thursday,04/13/23,1:00,GB,GDP MoM FEB,0,0.40%,0.001,0.001 +Thursday,04/13/23,7:30,US,PPI MoM MAR,-0.005,0%,0,0.001 +Friday,04/14/23,7:30,US,Retail Sales MoM MAR,-0.01,-0.20%,-0.004,-0.009 +Friday,04/14/23,9:00,US,Michigan Consumer Sentiment Prel APR,63.5,62,62,62.4 +Monday,04/17/23,21:00,CN,GDP Growth Rate YoY Q1,0.045,2.90%,0.04,0.032 +Monday,04/17/23,21:00,CN,Industrial Production YoY MAR,0.039,2.40%,0.04,0.027 +Tuesday,04/18/23,1:00,GB,Claimant Count Change MAR,28.2K,-18.8K,,-9.5K +Tuesday,04/18/23,1:00,GB,Unemployment Rate FEB,0.038,3.70%,0.037,0.038 +Tuesday,04/18/23,7:30,CA,Inflation Rate YoY MAR,0.043,5.20%,0.043,0.041 +Tuesday,04/18/23,7:30,US,Building Permits Prel MAR,1.413M,1.55M,1.45M,1.45M +Wednesday,04/19/23,1:00,GB,Inflation Rate YoY MAR,0.101,10.40%,0.098,0.102 +Wednesday,04/19/23,18:50,JP,Balance of Trade MAR,-754.5B,-898.1B,-1294.8B, -1100.0B +Thursday,04/20/23,18:01,GB,Gfk Consumer Confidence APR,-30,-36,-35,-34 +Thursday,04/20/23,18:30,JP,Inflation Rate YoY MAR,0.032,3.30%,,0.032 +Friday,04/21/23,1:00,GB,Retail Sales MoM MAR,-0.009,1.10%,-0.005,-0.005 +Wednesday,04/26/23,7:30,US,Durable Goods Orders MoM MAR,0.032,-1.20%,0.007,0.006 +Thursday,04/27/23,7:30,US,GDP Growth Rate QoQ Adv Q1,0.011,2.60%,0.02,0.023 +Thursday,04/27/23,23:00,JP,BoJ Interest Rate Decision,-0.001,-0.10%,-0.001,-0.001 +Friday,04/28/23,4:00,EA,GDP Growth Rate QoQ Flash Q1,0.001,0%,0.002,0.001 +Friday,04/28/23,4:00,EA,GDP Growth Rate YoY Flash Q1,0.013,1.80%,0.014,0.01 +Friday,04/28/23,7:30,US,Core PCE Price Index MoM MAR,0.003,0.30%,0.003,0.004 +Friday,04/28/23,7:30,US,Personal Income MoM MAR,0.003,0.30%,0.002,0.004 +Friday,04/28/23,7:30,US,Personal Spending MoM MAR,0,0.10%,-0.001,-0.002 +Saturday,04/29/23,20:30,CN,NBS Manufacturing PMI APR,49.2,51.9,51.4,51.5 +Saturday,04/29/23,0:00,JP,Consumer Confidence APR,35.4,33.9,,32 +Saturday,04/29/23,9:00,US,ISM Manufacturing PMI APR,47.1,46.3,46.8,46.5 +Tuesday,05/02/23,4:00,EA,Inflation Rate YoY Flash APR,0.07,6.90%,0.07,0.069 +Tuesday,05/02/23,9:00,US,JOLTs Job Openings MAR,9.59M,9.974M,9.775M,9.7M +Wednesday,05/03/23,4:00,EA,Unemployment Rate MAR,0.065,6.60%,0.066,0.066 +Wednesday,05/03/23,9:00,US,ISM Services PMI APR,51.9,51.2,51.8,51.5 +Wednesday,05/03/23,13:00,US,Fed Interest Rate Decision,0.0525,5%,0.0525,0.0525 +Wednesday,05/03/23,13:30,US,Fed Press Conference,,,, +Wednesday,05/03/23,20:45,CN,Caixin Manufacturing PMI APR,49.5,50,50.3,50.4 +Thursday,05/04/23,7:15,EA,Deposit Facility Rate,0.0325,3%,0.0325,0.0325 +Thursday,05/04/23,7:15,EA,ECB Interest Rate Decision,0.0375,3.50%,0.0375,0.0375 +Thursday,05/04/23,7:30,CA,Balance of Trade MAR,0.97B,-0.49B,0.2B,0.3B +Thursday,05/04/23,7:30,US,Balance of Trade MAR,-64.2B,-70.6B,-63.3B,-63.1B +Thursday,05/04/23,7:45,EA,ECB Press Conference,,,, +Thursday,05/04/23,9:00,CA,Ivey PMI s.a APR,56.8,58.2,59,53 +Thursday,05/04/23,7:30,CA,Unemployment Rate APR,0.05,5%,0.051,0.052 +Thursday,05/04/23,7:30,US,Non Farm Payrolls APR,253K,165K,180K,190.0K +Thursday,05/04/23,7:30,US,Unemployment Rate APR,0.034,3.50%,0.036,0.036 +Thursday,05/04/23,22:00,CN,Balance of Trade APR,90.21B,88.19B,71.6B,76.0B +Wednesday,05/10/23,7:30,US,Core Inflation Rate YoY APR,0.055,5.60%,0.055,0.056 +Wednesday,05/10/23,7:30,US,Inflation Rate MoM APR,0.004,0.10%,0.004,0.003 +Wednesday,05/10/23,7:30,US,Inflation Rate YoY APR,0.049,5%,0.05,0.049 +Wednesday,05/10/23,20:30,CN,Inflation Rate YoY APR,0.001,0.70%,0.004,0.004 +Thursday,05/11/23,6:00,GB,BoE Interest Rate Decision,0.045,4.25%,0.045,0.045 +Thursday,05/11/23,7:30,US,PPI MoM APR,0.002,-0.40%,0.003,0.001 +Thursday,05/11/23,1:00,GB,GDP Growth Rate QoQ Prel Q1,0.001,0.10%,0.001,0.001 +Thursday,05/11/23,1:00,GB,GDP Growth Rate YoY Prel Q1,0.002,0.60%,0.002,0.003 +Thursday,05/11/23,1:00,GB,GDP MoM MAR,-0.003,0%,0,0.001 +Thursday,05/11/23,9:00,US,Michigan Consumer Sentiment Prel 05,57.7,63.5,63,64 +Thursday,05/11/23,21:00,CN,Industrial Production YoY APR,0.056,3.90%,0.109,0.098 +Tuesday,05/16/23,1:00,GB,Claimant Count Change APR,46.7K,26.5K,,-15.0K +Tuesday,05/16/23,1:00,GB,Unemployment Rate MAR,0.039,3.80%,0.038,0.038 +Tuesday,05/16/23,7:30,CA,Inflation Rate YoY APR,0.044,4.30%,0.041,0.039 +Tuesday,05/16/23,7:30,US,Retail Sales MoM APR,0.004,-0.70%,0.008,0.007 +Tuesday,05/16/23,18:50,JP,GDP Growth Annualized Prel Q1,0.016,-0.10%,0.007,0.008 +Tuesday,05/16/23,18:50,JP,GDP Growth Rate QoQ Prel Q1,0.004,0%,0.001,0.002 +Wednesday,05/17/23,7:30,US,Building Permits Prel APR,1.416M,1.437M,1.437M,1.43M +Wednesday,05/17/23,18:50,JP,Balance of Trade APR,-432.4B,-755.1B,-613.8B,-690B +Thursday,05/18/23,18:01,GB,Gfk Consumer Confidence 05,-27,-30,-27,-32 +Thursday,05/18/23,18:30,JP,Inflation Rate YoY APR,0.035,3.20%,0.025,0.032 +Thursday,05/18/23,10:00,US,Fed Chair Powell Speech ,,,, +Wednesday,05/24/23,1:00,GB,Inflation Rate YoY APR,0.087,10.10%,0.082,0.085 +Wednesday,05/24/23,13:00,US,FOMC Minutes,,,, +Wednesday,05/24/23,1:00,GB,Retail Sales MoM APR,0.005,-1.20%,0.003,0.003 +Wednesday,05/24/23,7:30,US,Core PCE Price Index MoM APR,0.004,0.30%,0.003,0.003 +Wednesday,05/24/23,7:30,US,Durable Goods Orders MoM APR,0.011,3.30%,-0.01,-0.011 +Wednesday,05/24/23,7:30,US,Personal Income MoM APR,0.004,0.30%,0.004,0.003 +Wednesday,05/24/23,7:30,US,Personal Spending MoM APR,0.008,0.10%,0.004,0.003 +Tuesday,05/30/23,20:30,CN,NBS Manufacturing PMI 05,48.8,49.2,49.4,49.8 +Wednesday,05/31/23,0:00,JP,Consumer Confidence 05,36,35.4,36.1,36 +Wednesday,05/31/23,7:30,CA,GDP Growth Rate QoQ Q1,0.008,0%,0.004,0.005 +Wednesday,05/31/23,9:00,US,JOLTs Job Openings APR,10.103M,9.745M,9.375M,9.2M +Wednesday,05/31/23,20:45,CN,Caixin Manufacturing PMI 05,50.9,49.5,49.5,49.6 +Thursday,06/01/23,4:00,EA,Inflation Rate YoY Flash 05,0.061,7%,0.063,0.065 +Thursday,06/01/23,4:00,EA,Unemployment Rate APR,0.065,6.60%,0.065,0.065 +Thursday,06/01/23,9:00,US,ISM Manufacturing PMI 05,46.9,47.1,47,48 +Friday,06/02/23,7:30,US,Non Farm Payrolls 05,339K,294K,190K,180.0K +Friday,06/02/23,7:30,US,Unemployment Rate 05,0.037,3.40%,0.035,0.035 +Monday,06/05/23,9:00,US,ISM Services PMI 05,50.3,51.9,52.2,52.4 +Tuesday,06/06/23,9:00,CA,Ivey PMI s.a 05,53.5,56.8,57.2,56.5 +Tuesday,06/06/23,22:00,CN,Balance of Trade 05,65.81B,90.21B,92B,91.0B +Wednesday,06/07/23,7:30,US,Balance of Trade APR,-74.6B,-60.6B,-75.2B,-78.2B +Thursday,06/08/23,20:30,CN,Inflation Rate YoY 05,0.002,0.10%,0.003,0.002 +Friday,06/09/23,7:30,CA,Unemployment Rate 05,0.052,5%,0.051,0.051 +Tuesday,06/13/23,1:00,GB,Claimant Count Change 05,-13.6K,23.4K,,22.0K +Tuesday,06/13/23,1:00,GB,Unemployment Rate APR,0.038,3.90%,0.04,0.039 +Tuesday,06/13/23,7:30,US,Core Inflation Rate YoY 05,0.053,5.50%,0.053,0.054 +Tuesday,06/13/23,7:30,US,Inflation Rate MoM 05,0.001,0.40%,0.002,0.003 +Tuesday,06/13/23,7:30,US,Inflation Rate YoY 05,0.04,4.90%,0.041,0.043 +Wednesday,06/14/23,1:00,GB,GDP MoM APR,0.002,-0.30%,0.002,0.002 +Wednesday,06/14/23,7:30,US,PPI MoM 05,-0.003,0.20%,-0.001,0.001 +Wednesday,06/14/23,13:00,US,Fed Interest Rate Decision,0.0525,5.25%,0.0525,0.0525 +Wednesday,06/14/23,13:30,US,Fed Press Conference,,,, +Wednesday,06/14/23,18:50,JP,Balance of Trade 05,-1372.5B,-432.3B,-1331.9B,-1310.0B +Wednesday,06/14/23,21:00,CN,Industrial Production YoY 05,0.035,5.60%,0.036,0.05 +Thursday,06/15/23,7:15,EA,Deposit Facility Rate,0.035,3.25%,0.035,0.035 +Thursday,06/15/23,7:15,EA,ECB Interest Rate Decision,0.04,3.75%,0.04,0.04 +Thursday,06/15/23,7:30,US,Retail Sales MoM 05,0.003,0.40%,-0.001,0.002 +Thursday,06/15/23,7:45,EA,ECB Press Conference,,,, +Thursday,06/15/23,22:00,JP,BoJ Interest Rate Decision,-0.001,-0.10%,-0.001,-0.001 +Friday,06/16/23,9:00,US,Michigan Consumer Sentiment Prel JUN,63.9,59.2,60,60.8 +Tuesday,06/20/23,7:30,US,Building Permits Prel 05,1.491M,1.417M,1.42M,1.425M +Wednesday,06/21/23,1:00,GB,Inflation Rate YoY 05,0.087,8.70%,0.084,0.085 +Wednesday,06/21/23,9:00,US,Fed Chair Powell Testimony,,,, +Thursday,06/22/23,6:00,GB,BoE Interest Rate Decision,0.05,4.50%,0.0475,0.0475 +Thursday,06/22/23,9:00,US,Fed Chair Powell Testimony,,,, +Thursday,06/22/23,18:01,GB,Gfk Consumer Confidence JUN,-24,-27,-26,-27 +Thursday,06/22/23,18:30,JP,Inflation Rate YoY 05,0.032,3.50%,0.041,0.032 +Friday,06/23/23,1:00,GB,Retail Sales MoM 05,0.003,0.50%,-0.002,-0.003 +Sunday,06/25/23,,EA,ECB Forum on Central Banking,,,, +Monday,06/26/23,12:30,EA,ECB President Lagarde Speech ,,,, +Monday,06/26/23,,EA,ECB Forum on Central Banking,,,, +Tuesday,06/27/23,3:00,EA,ECB President Lagarde Speech ,,,, +Tuesday,06/27/23,7:30,CA,Inflation Rate YoY 05,0.034,4.40%,0.034,0.036 +Tuesday,06/27/23,7:30,US,Durable Goods Orders MoM 05,0.017,1.20%,-0.01,-0.009 +Tuesday,06/27/23,,EA,ECB Forum on Central Banking,,,, +Wednesday,06/28/23,8:30,US,Fed Chair Powell Speech ,,,, +Thursday,06/29/23,0:00,JP,Consumer Confidence JUN,36.2,36,36.2,38 +Thursday,06/29/23,1:30,US,Fed Chair Powell Speech ,,,, +Thursday,06/29/23,20:30,CN,NBS Manufacturing PMI JUN,49,48.8,49,51 +Friday,06/30/23,4:00,EA,Inflation Rate YoY Flash JUN,0.055,6.10%,0.056,0.056 +Friday,06/30/23,4:00,EA,Unemployment Rate 05,0.065,6.50%,0.065,0.065 +Friday,06/30/23,7:30,US,Core PCE Price Index MoM 05,0.003,0.40%,0.003,0.003 +Friday,06/30/23,7:30,US,Personal Income MoM 05,0.004,0.30%,0.003,0.003 +Friday,06/30/23,7:30,US,Personal Spending MoM 05,0.001,0.60%,0.002,0.004 +Sunday,07/02/23,18:50,JP,Tankan Large Manufacturers Index Q2,5,1,3,3 +Sunday,07/02/23,20:45,CN,Caixin Manufacturing PMI JUN,50.5,50.9,50.2,50.4 +Monday,07/03/23,9:00,US,ISM Manufacturing PMI JUN,46,46.9,47,48 +Wednesday,07/05/23,13:00,US,FOMC Minutes,,,, +Thursday,07/06/23,9:00,US,ISM Services PMI JUN,53.9,50.3,51,50 +Thursday,07/06/23,9:00,US,JOLTs Job Openings 05,9.8M,10.32M,9.935M,9.9M +Friday,07/07/23,7:30,CA,Unemployment Rate JUN,0.054,5.20%,0.053,0.054 +Friday,07/07/23,7:30,US,Non Farm Payrolls JUN,209K,306K,225K,250.0K +Friday,07/07/23,7:30,US,Unemployment Rate JUN,0.036,3.70%,0.036,0.037 +Friday,07/07/23,9:00,CA,Ivey PMI s.a JUN,50.2,53.5,,52.3 +Sunday,07/09/23,20:30,CN,Inflation Rate YoY JUN,0,0.20%,0.002,0.001 +Tuesday,07/11/23,1:00,GB,Unemployment Rate 05,0.04,3.80%,0.038,0.039 +Wednesday,07/12/23,7:30,US,Core Inflation Rate MoM JUN,0.002,0.40%,0.003,0.003 +Wednesday,07/12/23,7:30,US,Core Inflation Rate YoY JUN,0.048,5.30%,0.05,0.05 +Wednesday,07/12/23,7:30,US,Inflation Rate MoM JUN,0.002,0.10%,0.003,0.002 +Wednesday,07/12/23,7:30,US,Inflation Rate YoY JUN,0.03,4%,0.031,0.032 +Wednesday,07/12/23,9:00,CA,BoC Interest Rate Decision,0.05,4.75%,0.05,0.05 +Wednesday,07/12/23,9:00,CA,BoC Monetary Policy Report,,,, +Wednesday,07/12/23,22:00,CN,Balance of Trade JUN,70.62B,65.81B,74.8B, 90.0B +Thursday,07/13/23,1:00,GB,GDP MoM 05,-0.001,0.20%,-0.003,-0.002 +Thursday,07/13/23,7:30,US,PPI MoM JUN,0.001,-0.40%,0.002,0.001 +Friday,07/14/23,9:00,US,Michigan Consumer Sentiment Prel JUL,72.6,64.4,65.5,64.5 +Sunday,07/16/23,21:00,CN,GDP Growth Rate YoY Q2,0.063,4.50%,0.073,0.071 +Sunday,07/16/23,21:00,CN,Industrial Production YoY JUN,0.044,3.50%,0.027,0.024 +Tuesday,07/18/23,7:30,CA,Inflation Rate YoY JUN,0.028,3.40%,0.03,0.03 +Tuesday,07/18/23,7:30,US,Retail Sales MoM JUN,0.002,0.50%,0.005,0.003 +Wednesday,07/19/23,1:00,GB,Inflation Rate YoY JUN,0.079,8.70%,0.082,0.083 +Wednesday,07/19/23,7:30,US,Building Permits Prel JUN,1.44M,1.496M,1.49M,1.462M +Wednesday,07/19/23,18:50,JP,Balance of Trade JUN,43B,-1381.9B,-46.7B, -48B +Thursday,07/20/23,18:30,JP,Inflation Rate YoY JUN,0.033,3.20%,0.035,0.033 +Friday,07/21/23,1:00,GB,Retail Sales MoM JUN,0.007,0.10%,0.002,0.001 +Wednesday,07/26/23,13:00,US,Fed Interest Rate Decision,0.055,5.25%,0.055,0.055 +Wednesday,07/26/23,13:30,US,Fed Press Conference,,,, +Thursday,07/27/23,7:15,EA,ECB Interest Rate Decision,0.0425,4%,0.0425,0.0425 +Thursday,07/27/23,7:30,US,Durable Goods Orders MoM JUN,0.047,2%,0.01,0.006 +Thursday,07/27/23,7:30,US,GDP Growth Rate QoQ Adv Q2,0.024,2%,0.018,0.018 +Thursday,07/27/23,7:45,EA,ECB Press Conference,,,, +Thursday,07/27/23,22:00,JP,BoJ Interest Rate Decision,-0.001,-0.10%,-0.001,-0.001 +Friday,07/28/23,7:30,US,Core PCE Price Index MoM JUN,0.002,0.30%,0.002,0.002 +Friday,07/28/23,7:30,US,Personal Income MoM JUN,0.003,0.50%,0.005,0.004 +Friday,07/28/23,7:30,US,Personal Spending MoM JUN,0.005,0.20%,0.004,0.003 +Sunday,07/30/23,20:30,CN,NBS Manufacturing PMI JUL,49.3,49,49.2,48.9 +Monday,07/31/23,4:00,EA,GDP Growth Rate QoQ Flash Q2,0.003,0%,0.002,0.003 +Monday,07/31/23,4:00,EA,GDP Growth Rate YoY Flash Q2,0.006,1.10%,0.005,0.006 +Monday,07/31/23,4:00,EA,Inflation Rate YoY Flash JUL,0.053,5.50%,0.053,0.052 +Monday,07/31/23,20:45,CN,Caixin Manufacturing PMI JUL,49.2,50.5,50.3,50.1 +Tuesday,08/01/23,9:00,US,ISM Manufacturing PMI JUL,46.4,46,46.8,48 +Tuesday,08/01/23,9:00,US,JOLTs Job Openings JUN,9.582M,9.616M,9.61M,9.5M +Thursday,08/03/23,6:00,GB,BoE Interest Rate Decision,0.0525,5%,0.0525,0.0525 +Thursday,08/03/23,9:00,US,ISM Services PMI JUL,52.7,53.9,53,52 +Friday,08/04/23,7:30,CA,Unemployment Rate JUL,0.055,5.40%,0.055,0.054 +Friday,08/04/23,7:30,US,Non Farm Payrolls JUL,187K,185K,200K,190K +Friday,08/04/23,7:30,US,Unemployment Rate JUL,0.035,3.60%,0.036,0.036 +Friday,08/04/23,9:00,CA,Ivey PMI s.a JUL,48.6,50.2,52.7,49.7 +Monday,08/07/23,22:00,CN,Balance of Trade JUL,80.6B,70.62B,70.6B,69B +Tuesday,08/08/23,20:30,CN,Inflation Rate YoY JUL,-0.003,0%,-0.004,-0.003 +Thursday,08/10/23,7:30,US,Core Inflation Rate MoM JUL,0.002,0.20%,0.002,0.002 +Thursday,08/10/23,7:30,US,Core Inflation Rate YoY JUL,0.047,4.80%,0.048,0.048 +Thursday,08/10/23,7:30,US,Inflation Rate MoM JUL,0.002,0.20%,0.002,0.002 +Thursday,08/10/23,7:30,US,Inflation Rate YoY JUL,0.032,3%,0.033,0.031 +Friday,08/11/23,1:00,GB,GDP Growth Rate QoQ Prel Q2,0.002,0.10%,0,0.001 +Friday,08/11/23,1:00,GB,GDP Growth Rate YoY Prel Q2,0.004,0.20%,0.002,0.001 +Friday,08/11/23,1:00,GB,GDP MoM JUN,0.005,-0.10%,0.002,0.001 +Friday,08/11/23,7:30,US,PPI MoM JUL,0.003,0%,0.002,0.002 +Friday,08/11/23,9:00,US,Michigan Consumer Sentiment Prel AUG,71.2,71.6,71,71.3 +Monday,08/14/23,18:50,JP,GDP Growth Annualized Prel Q2,0.06,3.70%,0.031,0.032 +Monday,08/14/23,18:50,JP,GDP Growth Rate QoQ Prel Q2,0.015,0.90%,0.008,0.01 +Monday,08/14/23,21:00,CN,Industrial Production YoY JUL,0.037,4.40%,0.044,0.047 +Tuesday,08/15/23,1:00,GB,Unemployment Rate JUN,0.042,4%,0.04,0.04 +Tuesday,08/15/23,7:30,CA,Inflation Rate YoY JUL,0.033,2.80%,0.03,0.031 +Tuesday,08/15/23,7:30,US,Retail Sales MoM JUL,0.007,0.30%,0.004,0.003 +Wednesday,08/16/23,1:00,GB,Inflation Rate YoY JUL,0.068,7.90%,0.068,0.069 +Wednesday,08/16/23,7:30,US,Building Permits Prel JUL,1.442M,1.441M,1.463M,1.457M +Wednesday,08/16/23,13:00,US,FOMC Minutes,,,, +Wednesday,08/16/23,18:50,JP,Balance of Trade JUL,-78.7B,43.1B,24.6B,26B +Thursday,08/17/23,18:30,JP,Inflation Rate YoY JUL,0.033,3.30%,0.025,0.031 +Friday,08/18/23,1:00,GB,Retail Sales MoM JUL,-0.012,0.60%,-0.005,-0.003 +Thursday,08/24/23,7:30,US,Durable Goods Orders MoM JUL,-0.052,4.40%,-0.04,0.005 +Friday,08/25/23,9:05,US,Fed Chair Powell Speech ,,,, +Friday,08/25/23,14:00,EA,ECB President Lagarde Speech ,,,, +Tuesday,08/29/23,9:00,US,JOLTs Job Openings JUL,8.827M,9.165M,9.465M,9.57M +Wednesday,08/30/23,7:30,US,GDP Growth Rate QoQ 2nd Est Q2,0.021,2%,0.024,0.024 +Wednesday,08/30/23,20:30,CN,NBS Manufacturing PMI AUG,49.7,49.3,49.4,49.5 +Thursday,08/31/23,4:00,EA,Inflation Rate YoY Flash AUG,0.053,5.30%,0.051,0.05 +Thursday,08/31/23,7:30,US,Core PCE Price Index MoM JUL,0.002,0.20%,0.002,0.002 +Thursday,08/31/23,7:30,US,Personal Income MoM JUL,0.002,0.30%,0.003,0.003 +Thursday,08/31/23,7:30,US,Personal Spending MoM JUL,0.008,0.50%,0.007,0.004 +Thursday,08/31/23,20:45,CN,Caixin Manufacturing PMI AUG,51,49.2,49.3,49.3 +Friday,09/01/23,7:30,CA,GDP Growth Rate QoQ Q2,0,0.60%,0.003,0.001 +Friday,09/01/23,7:30,US,Non Farm Payrolls AUG,187K,157K,170K,180.0K +Friday,09/01/23,7:30,US,Unemployment Rate AUG,0.038,3.50%,0.035,0.035 +Friday,09/01/23,9:00,US,ISM Manufacturing PMI AUG,47.6,46.4,47,47 +Wednesday,09/06/23,9:00,US,ISM Services PMI AUG,54.5,52.7,52.5,52.4 +Wednesday,09/06/23,22:00,CN,Balance of Trade AUG,68.36B,80.6B,73.9B,81B +Thursday,09/07/23,9:00,CA,Ivey PMI s.a AUG,53.5,48.6,49.2,48 +Friday,09/08/23,7:30,CA,Unemployment Rate AUG,0.055,5.50%,0.056,0.057 +Friday,09/08/23,20:30,CN,Inflation Rate YoY AUG,0.001,-0.30%,0.002,0.001 +Tuesday,09/12/23,1:00,GB,Unemployment Rate JUL,0.043,4.20%,0.043,0.042 +Wednesday,09/13/23,1:00,GB,GDP MoM JUL,-0.005,0.50%,-0.002,-0.003 +Wednesday,09/13/23,7:30,US,Core Inflation Rate MoM AUG,0.003,0.20%,0.002,0.002 +Wednesday,09/13/23,7:30,US,Core Inflation Rate YoY AUG,0.043,4.70%,0.043,0.044 +Wednesday,09/13/23,7:30,US,Inflation Rate MoM AUG,0.006,0.20%,0.006,0.005 +Wednesday,09/13/23,7:30,US,Inflation Rate YoY AUG,0.037,3.20%,0.036,0.035 +Thursday,09/14/23,7:15,EA,ECB Interest Rate Decision,0.045,4.25%,0.0425,0.045 +Thursday,09/14/23,7:30,US,PPI MoM AUG,0.007,0.40%,0.004,0.004 +Thursday,09/14/23,7:30,US,Retail Sales MoM AUG,0.006,0.50%,0.002,0.004 +Thursday,09/14/23,7:45,EA,ECB Press Conference,,,, +Thursday,09/14/23,21:00,CN,Industrial Production YoY AUG,0.045,3.70%,0.039,0.035 +Thursday,09/14/23,21:00,CN,Retail Sales YoY AUG,0.046,2.50%,0.03,0.026 +Friday,09/15/23,9:00,US,Michigan Consumer Sentiment Prel SEP,67.7,69.5,69.1,70 +Tuesday,09/19/23,7:30,CA,Inflation Rate YoY AUG,0.04,3.30%,0.038,0.039 +Tuesday,09/19/23,7:30,US,Building Permits Prel AUG,1.543M,1.443M,1.443M,1.43M +Tuesday,09/19/23,18:50,JP,Balance of Trade AUG,-930.5B,-66.3B,-659.1B,-950.0B +Wednesday,09/20/23,1:00,GB,Inflation Rate YoY AUG,0.067,6.80%,0.07,0.071 +Wednesday,09/20/23,13:00,US,Fed Interest Rate Decision,0.055,5.50%,0.055,0.055 +Wednesday,09/20/23,13:30,US,Fed Press Conference,,,, +Thursday,09/21/23,6:00,GB,BoE Interest Rate Decision,0.0525,5.25%,0.055,0.055 +Thursday,09/21/23,18:30,JP,Inflation Rate YoY AUG,0.032,3.30%,,0.033 +Thursday,09/21/23,22:00,JP,BoJ Interest Rate Decision,-0.001,-0.10%,-0.001,-0.001 +Friday,09/22/23,1:00,GB,Retail Sales MoM AUG,0.004,-1.10%,0.005,0.004 +Wednesday,09/27/23,7:30,US,Durable Goods Orders MoM AUG,0.002,-5.60%,-0.005,-0.014 +Thursday,09/28/23,7:30,US,GDP Growth Rate QoQ Final Q2,0.021,2.20%,0.021,0.021 +Friday,09/29/23,4:00,EA,Inflation Rate YoY Flash SEP,0.043,5.20%,0.045,0.047 +Friday,09/29/23,7:30,US,Core PCE Price Index MoM AUG,0.001,0.20%,0.002,0.002 +Friday,09/29/23,7:30,US,Personal Income MoM AUG,0.004,0.20%,0.004,0.003 +Friday,09/29/23,7:30,US,Personal Spending MoM AUG,0.004,0.90%,0.004,0.006 +Friday,09/29/23,20:30,CN,NBS Manufacturing PMI SEP,50.2,49.7,50,50.4 +Saturday,09/30/23,20:45,CN,Caixin Manufacturing PMI SEP,50.6,51,51.2,51.2 +Sunday,10/01/23,18:50,JP,Tankan Large Manufacturers Index Q3,9,5,6,7 +Monday,10/02/23,9:00,US,ISM Manufacturing PMI SEP,49,47.6,47.8,48.1 +Tuesday,10/03/23,9:00,US,JOLTs Job Openings AUG,9.61M,8.92M,8.8M,8.6M +Wednesday,10/04/23,9:00,US,ISM Services PMI SEP,53.6,54.5,53.6,53.7 +Thursday,10/05/23,9:00,CA,Ivey PMI s.a SEP,53.1,53.5,50.8,49.6 +Friday,10/06/23,7:30,CA,Unemployment Rate SEP,0.055,5.50%,0.056,0.056 +Friday,10/06/23,7:30,US,Non Farm Payrolls SEP,336K,227K,170K,150.0K +Friday,10/06/23,7:30,US,Unemployment Rate SEP,0.038,3.80%,0.037,0.038 +Wednesday,10/11/23,7:30,US,PPI MoM SEP,0.005,0.70%,0.003,0.004 +Wednesday,10/11/23,13:00,US,FOMC Minutes,,,, +Thursday,10/12/23,1:00,GB,GDP MoM AUG,0.002,-0.60%,0.002,0.001 +Thursday,10/12/23,7:30,US,Core Inflation Rate MoM SEP,0.003,0.30%,0.003,0.003 +Thursday,10/12/23,7:30,US,Core Inflation Rate YoY SEP,0.041,4.30%,0.041,0.041 +Thursday,10/12/23,7:30,US,Inflation Rate MoM SEP,0.004,0.60%,0.003,0.004 +Thursday,10/12/23,7:30,US,Inflation Rate YoY SEP,0.037,3.70%,0.036,0.037 +Thursday,10/12/23,20:30,CN,Inflation Rate YoY SEP,0,0.10%,0.002,0.003 +Thursday,10/12/23,22:00,CN,Balance of Trade SEP,77.71B,68.36B,70B,72.1B +Friday,10/13/23,9:00,US,Michigan Consumer Sentiment Prel OCT,63,68.1,67.2,68 +Tuesday,10/17/23,7:30,CA,Inflation Rate YoY SEP,0.038,4%,0.04,0.045 +Tuesday,10/17/23,7:30,US,Retail Sales MoM SEP,0.007,0.80%,0.003,0.003 +Tuesday,10/17/23,21:00,CN,GDP Growth Rate YoY Q3,0.049,6.30%,0.044,0.046 +Tuesday,10/17/23,21:00,CN,Industrial Production YoY SEP,0.045,4.50%,0.043,0.043 +Tuesday,10/17/23,21:00,CN,Retail Sales YoY SEP,0.055,4.60%,0.049,0.047 +Wednesday,10/18/23,1:00,GB,Inflation Rate YoY SEP,0.067,6.70%,0.066,0.065 +Wednesday,10/18/23,7:30,US,Building Permits Prel SEP,1.473M,1.541M,1.45M,1.46M +Wednesday,10/18/23,18:50,JP,Balance of Trade SEP,62.4B,-937.8B,-425B, -500.0B +Thursday,10/19/23,11:00,US,Fed Chair Powell Speech ,,,, +Thursday,10/19/23,18:30,JP,Inflation Rate YoY SEP,0.03,3.20%,,0.031 +Friday,10/20/23,1:00,GB,Retail Sales MoM SEP,-0.009,0.40%,-0.002,-0.002 +Tuesday,10/24/23,1:00,GB,Unemployment Rate - Adjusted AUG,0.042,,, +Wednesday,10/25/23,9:00,CA,BoC Monetary Policy Report,,,, +Wednesday,10/25/23,15:35,US,Fed Chair Powell Speech ,,,, +Thursday,10/26/23,7:15,EA,ECB Interest Rate Decision,0.045,4.50%,0.045,0.045 +Thursday,10/26/23,7:30,US,Durable Goods Orders MoM SEP,0.047,-0.10%,0.017,0.011 +Thursday,10/26/23,7:30,US,GDP Growth Rate QoQ Adv Q3,0.049,2.10%,0.043,0.04 +Thursday,10/26/23,7:45,EA,ECB Press Conference,,,, +Friday,10/27/23,7:30,US,Core PCE Price Index MoM SEP,0.003,0.10%,0.003,0.002 +Friday,10/27/23,7:30,US,Personal Income MoM SEP,0.003,0.40%,0.004,0.003 +Friday,10/27/23,7:30,US,Personal Spending MoM SEP,0.007,0.40%,0.005,0.005 +Monday,10/30/23,20:30,CN,NBS Manufacturing PMI OCT,49.5,50.2,50.2,50.5 +Monday,10/30/23,22:00,JP,BoJ Interest Rate Decision,-0.001,-0.10%,-0.001,-0.001 +Tuesday,10/31/23,5:00,EA,GDP Growth Rate QoQ Flash Q3,-0.001,0.20%,0,0 +Tuesday,10/31/23,5:00,EA,GDP Growth Rate YoY Flash Q3,0.001,0.50%,0.002,0.001 +Tuesday,10/31/23,5:00,EA,Inflation Rate YoY Flash OCT,0.029,4.30%,0.031,0.033 +Tuesday,10/31/23,20:45,CN,Caixin Manufacturing PMI OCT,49.5,50.6,50.8,50.7 +Wednesday,11/01/23,9:00,US,ISM Manufacturing PMI OCT,46.7,49,49,49.5 +Wednesday,11/01/23,9:00,US,JOLTs Job Openings SEP,9.553M,9.497M,9.25M,9.2M +Wednesday,11/01/23,13:00,US,Fed Interest Rate Decision,0.055,5.50%,0.055,0.055 +Wednesday,11/01/23,13:30,US,Fed Press Conference,,,, +Thursday,11/02/23,7:00,GB,BoE Interest Rate Decision,0.0525,5.25%,0.0525,0.0525 +Friday,11/03/23,7:30,CA,Unemployment Rate OCT,0.057,5.50%,0.056,0.055 +Friday,11/03/23,7:30,US,Non Farm Payrolls OCT,150K,297K,180K,190K +Friday,11/03/23,7:30,US,Unemployment Rate OCT,0.039,3.80%,0.038,0.038 +Friday,11/03/23,9:00,US,ISM Services PMI OCT,51.8,53.6,53,53.7 +Monday,11/06/23,10:00,CA,Ivey PMI s.a OCT,53.4,53.1,54,52.1 +Monday,11/06/23,22:00,CN,Balance of Trade OCT,56.53B,77.71B,82B,81.0B +Wednesday,11/08/23,9:15,US,Fed Chair Powell Speech ,,,, +Wednesday,11/08/23,20:30,CN,Inflation Rate YoY OCT,-0.002,0%,-0.001,0 +Thursday,11/09/23,14:00,US,Fed Chair Powell Speech ,,,, +Friday,11/10/23,2:00,GB,GDP Growth Rate QoQ Prel Q3,0,0.20%,-0.001,0 +Friday,11/10/23,2:00,GB,GDP Growth Rate YoY Prel Q3,0.006,0.60%,0.005,0.006 +Friday,11/10/23,2:00,GB,GDP MoM SEP,0.002,0.10%,0,0 +Friday,11/10/23,7:30,EA,ECB President Lagarde Speech ,,,, +Friday,11/10/23,10:00,US,Michigan Consumer Sentiment Prel NOV,60.4,63.8,63.7,64.2 +Tuesday,11/14/23,2:00,GB,Unemployment Rate SEP,0.042,4.20%,0.043,0.043 +Tuesday,11/14/23,8:30,US,Core Inflation Rate MoM OCT,0.002,0.30%,0.003,0.003 +Tuesday,11/14/23,8:30,US,Core Inflation Rate YoY OCT,0.04,4.10%,0.041,0.04 +Tuesday,11/14/23,8:30,US,Inflation Rate MoM OCT,0,0.40%,0.001,0.001 +Tuesday,11/14/23,8:30,US,Inflation Rate YoY OCT,0.032,3.70%,0.033,0.033 +Tuesday,11/14/23,18:50,JP,GDP Growth Annualized Prel Q3,-0.021,4.50%,-0.006,-0.006 +Tuesday,11/14/23,18:50,JP,GDP Growth Rate QoQ Prel Q3,-0.005,1.10%,-0.001,-0.002 +Tuesday,11/14/23,21:00,CN,Industrial Production YoY OCT,0.046,4.50%,0.044,0.044 +Tuesday,11/14/23,21:00,CN,Retail Sales YoY OCT,0.076,5.50%,0.07,0.067 +Wednesday,11/15/23,2:00,GB,Inflation Rate YoY OCT,0.046,6.70%,0.048,0.049 +Wednesday,11/15/23,8:30,US,PPI MoM OCT,-0.005,0.40%,0.001,0.001 +Wednesday,11/15/23,8:30,US,Retail Sales MoM OCT,-0.001,0.90%,-0.003,0 +Wednesday,11/15/23,18:50,JP,Balance of Trade OCT,-662.5B,72.1B,-735.7B,-500B +Friday,11/17/23,2:00,GB,Retail Sales MoM OCT,-0.003,-1.10%,0.003,0.002 +Friday,11/17/23,8:30,US,Building Permits Prel OCT,1.487M,1.471M,1.45M,1.45M +Tuesday,11/21/23,8:30,CA,Inflation Rate YoY OCT,0.031,3.80%,0.032,0.033 +Tuesday,11/21/23,14:00,US,FOMC Minutes,,,, +Wednesday,11/22/23,8:30,US,Durable Goods Orders MoM OCT,-0.054,4%,-0.031,-0.028 +Wednesday,11/22/23,,GB,Autumn Statement,,,, +Thursday,11/23/23,18:30,JP,Inflation Rate YoY OCT,0.033,3%,,0.032 +Wednesday,11/29/23,8:30,US,GDP Growth Rate QoQ 2nd Est Q3,0.052,2.10%,0.05,0.049 +Wednesday,11/29/23,20:30,CN,NBS Manufacturing PMI NOV,49.4,49.5,49.7,49.9 +Thursday,11/30/23,5:00,EA,Inflation Rate YoY Flash NOV,0.024,2.90%,0.027,0.027 +Thursday,11/30/23,8:30,CA,GDP Growth Rate QoQ Q3,-0.003,0.30%,,0 +Thursday,11/30/23,8:30,US,Core PCE Price Index MoM OCT,0.002,0.30%,0.002,0.003 +Thursday,11/30/23,8:30,US,Personal Income MoM OCT,0.002,0.40%,0.002,0.003 +Thursday,11/30/23,8:30,US,Personal Spending MoM OCT,0.002,0.70%,0.002,0.004 +Thursday,11/30/23,20:45,CN,Caixin Manufacturing PMI NOV,50.7,49.5,49.8,49.8 +Friday,12/01/23,8:30,CA,Unemployment Rate NOV,0.058,5.70%,0.058,0.058 +Friday,12/01/23,10:00,US,ISM Manufacturing PMI NOV,46.7,46.7,47.6,47.2 diff --git a/The Effect of Economic News on Gold Prices Analysis/Dataset/gold_price_19_24.csv b/The Effect of Economic News on Gold Prices Analysis/Dataset/gold_price_19_24.csv new file mode 100644 index 000000000..b0dda1293 --- /dev/null +++ b/The Effect of Economic News on Gold Prices Analysis/Dataset/gold_price_19_24.csv @@ -0,0 +1,1280 @@ +Date,Price,Open,High,Low,Vol_K,Change_percent +12/01/2023,2089.7,2056.5,2095.7,2052.6,241.62,1.58 +11/30/2023,2057.2,2065.4,2067.4,2051.2,151.92,-0.48 +11/29/2023,2067.1,2062,2072.7,2055.9,197.79,0.81 +11/28/2023,2050.5,2025,2054.4,2022.9,1.86,1.35 +11/27/2023,2023.1,2012.9,2027.5,2012.7,1.06,0.47 +11/24/2023,2013.7,2002.5,2014.1,2002,0.52,0.95 +11/23/2023,1994.75,1991.6,1999.4,1990.85,,-0.43 +11/22/2023,2003.4,2010.4,2015,1999.8,0.67,-0.43 +11/21/2023,2012,1994.1,2019.5,1993.2,0.67,1.07 +11/20/2023,1990.7,1997.9,1997.9,1978.1,0.31,0.30 +11/17/2023,1984.7,1984.2,1996.4,1981.1,133.12,-0.13 +11/16/2023,1987.3,1963,1991.1,1959,186.81,1.17 +11/15/2023,1964.3,1966.9,1979.2,1958.8,142.92,-0.11 +11/14/2023,1966.5,1950.3,1975.3,1938.8,180.74,0.84 +11/13/2023,1950.2,1943.4,1953.5,1935.6,183.7,0.65 +11/10/2023,1937.7,1964.1,1965.6,1936.9,229.64,-1.63 +11/09/2023,1969.8,1955.5,1971.5,1948.3,214.08,0.61 +11/08/2023,1957.8,1975.3,1977.5,1953.2,189.36,-0.80 +11/07/2023,1973.5,1984.8,1985.2,1962.8,218.95,-0.76 +11/06/2023,1988.6,1999.4,2000.1,1984.2,146.28,-0.53 +11/03/2023,1999.2,1993.5,2011.9,1989.3,222.19,0.29 +11/02/2023,1993.5,1992,1999.2,1986.3,158.65,0.30 +11/01/2023,1987.5,1993.3,2005.9,1978.2,197.63,-0.34 +10/31/2023,1994.3,2005.6,2017.7,1987.4,214.78,-0.56 +10/30/2023,2005.6,2013.5,2016.8,1999.7,181.34,0.83 +10/27/2023,1989,1987.5,2009.8,1978.5,0.37,0.06 +10/26/2023,1987.9,1981.6,1992.5,1974.4,0.2,0.12 +10/25/2023,1985.5,1972,1988.8,1971,0.16,0.44 +10/24/2023,1976.8,1975.1,1980.3,1958.3,1.23,-0.07 +10/23/2023,1978.2,1977.9,1983.1,1963.6,0.45,-0.81 +10/20/2023,1994.4,1988,2009.2,1983.7,,0.70 +10/19/2023,1980.5,1960.1,1990.2,1957,264.82,0.62 +10/18/2023,1968.3,1936.7,1975.8,1935.9,270.05,1.68 +10/17/2023,1935.7,1933.3,1944.5,1924.6,165.06,0.07 +10/16/2023,1934.3,1941.3,1943,1921.2,182.82,-0.37 +10/13/2023,1941.5,1881.7,1946.2,1881.5,312.99,3.11 +10/12/2023,1883,1888.1,1898.3,1880.6,163.48,-0.23 +10/11/2023,1887.3,1873.7,1890.9,1871.7,169.96,0.64 +10/10/2023,1875.3,1875.4,1879.1,1866.1,157.34,0.59 +10/09/2023,1864.3,1861,1877.3,1857.5,187.8,1.04 +10/06/2023,1845.2,1834.3,1849,1823.5,231.02,0.73 +10/05/2023,1831.8,1837.6,1843.5,1826.2,172.46,-0.16 +10/04/2023,1834.8,1838.7,1846.8,1831.6,195.05,-0.36 +10/03/2023,1841.5,1844.9,1849.3,1830.9,216.78,-0.31 +10/02/2023,1847.2,1864.4,1864.7,1842.7,202.15,-1.01 +09/29/2023,1866.1,1882.3,1896.7,1862.3,245.13,-0.67 +09/28/2023,1878.6,1893.3,1896.8,1874.5,231.42,-0.65 +09/27/2023,1890.9,1918.8,1921.7,1890.3,238.53,-1.51 +09/26/2023,1919.8,1935.1,1935.5,1917.2,212.26,-0.87 +09/25/2023,1936.6,1944.7,1946.8,1933.8,164.26,-0.46 +09/22/2023,1945.6,1939.6,1949.1,1939.6,139.93,0.31 +09/21/2023,1939.6,1952,1952.2,1933.1,225.91,-1.40 +09/20/2023,1967.1,1953,1968.9,1948.6,220.98,0.69 +09/19/2023,1953.7,1955.3,1958.9,1950.9,131.1,0.02 +09/18/2023,1953.4,1945.7,1955.7,1943.8,138.03,0.37 +09/15/2023,1946.2,1932.5,1952.4,1931.2,199.77,0.69 +09/14/2023,1932.8,1930.7,1934.5,1921.7,201.74,0.02 +09/13/2023,1932.5,1935.2,1938.4,1927.2,161,-0.13 +09/12/2023,1935.1,1945.6,1947.5,1929.9,161.99,-0.62 +09/11/2023,1947.2,1943.3,1954.6,1939.5,131.08,0.23 +09/08/2023,1942.7,1943.8,1954,1940.8,138.69,0.01 +09/07/2023,1942.5,1942.2,1947.9,1940.3,117.17,-0.09 +09/06/2023,1944.2,1951.5,1954.5,1940,148.78,-0.43 +09/05/2023,1952.6,1966.7,1972.6,1950.6,192.79,-0.54 +09/04/2023,1963.25,1966.6,1972.55,1962.55,,-0.17 +09/03/2023,1966.65,1966.4,1967.05,1965.5,,-0.02 +09/01/2023,1967.1,1966.4,1980.2,1960.7,160.73,0.06 +08/31/2023,1965.9,1970.2,1974.9,1965.5,133.71,-0.36 +08/30/2023,1973,1966,1977.1,1962.8,142.38,0.40 +08/29/2023,1965.1,1948.1,1966.5,1941.7,174.22,0.94 +08/28/2023,1946.8,1944,1954.2,1940.1,115.55,0.36 +08/25/2023,1939.9,1944.9,1950.4,1931,166.99,-0.37 +08/24/2023,1947.1,1944.9,1951.3,1939.2,137.39,-0.05 +08/23/2023,1948.1,1926.8,1949.7,1926.2,170.04,1.15 +08/22/2023,1926,1924,1933.2,1917.5,131.09,0.16 +08/21/2023,1923,1918.4,1927.9,1913.6,138.11,0.34 +08/18/2023,1916.5,1919.2,1926,1915.9,114.74,0.07 +08/17/2023,1915.2,1922.4,1933.5,1914.2,152.33,-0.68 +08/16/2023,1928.3,1933.1,1938.2,1922,128.61,-0.36 +08/15/2023,1935.2,1939.4,1944.3,1927.5,167.15,-0.45 +08/14/2023,1944,1945.6,1948.2,1934.2,120.98,-0.13 +08/11/2023,1946.6,1944.9,1953.6,1942.7,122.32,-0.12 +08/10/2023,1948.9,1947.7,1963.5,1944.4,168.26,-0.09 +08/09/2023,1950.6,1959.3,1966.1,1947.2,139.26,-0.47 +08/08/2023,1959.9,1971.5,1972.8,1956.5,142.34,-0.51 +08/07/2023,1970,1977.6,1981.7,1966.1,104.41,-0.31 +08/04/2023,1976.1,1969.6,1984.2,1954.5,156.42,0.37 +08/03/2023,1968.8,1970.8,1974.5,1964.5,141.35,-0.31 +08/02/2023,1975,1988.9,1992.2,1969.1,169.66,-0.19 +08/01/2023,1978.8,2004.2,2004.4,1978.3,167.76,-1.51 +07/31/2023,2009.2,1997.9,2010.9,1986.7,139.96,0.47 +07/28/2023,1999.9,1985.3,2002,1983.9,159.6,1.76 +07/27/2023,1965.3,1991.8,2002,1961.4,16.91,-1.23 +07/26/2023,1989.7,1985.9,1999.3,1982.8,11.94,0.33 +07/25/2023,1983.1,1976.1,1986.2,1971.1,8.63,0.08 +07/24/2023,1981.6,1983.2,1988.7,1974.7,6.44,0.76 +07/21/2023,1966.6,1972.1,1975.9,1958.8,156.54,-0.22 +07/20/2023,1970.9,1980,1989.8,1967.7,189.93,-0.50 +07/19/2023,1980.8,1982.5,1984.6,1973.3,159.41,0.00 +07/18/2023,1980.8,1958.3,1988.3,1958.1,264.09,1.25 +07/17/2023,1956.4,1958.6,1963.6,1949,165.83,-0.41 +07/14/2023,1964.4,1965.2,1967.8,1954.7,209.31,0.03 +07/13/2023,1963.8,1962.7,1968.5,1956.6,241.22,0.11 +07/12/2023,1961.7,1938,1965.1,1937.5,270.87,1.27 +07/11/2023,1937.1,1930.8,1944.5,1929.8,189.37,0.32 +07/10/2023,1931,1930.7,1933.7,1918,208.09,-0.08 +07/07/2023,1932.5,1916.6,1941.1,1915.4,214.27,0.89 +07/06/2023,1915.4,1922.4,1934,1908.5,231.51,-0.61 +07/05/2023,1927.1,1929.1,1942.9,1922.1,245.93,-0.35 +07/04/2023,1933.95,1928.85,1938.05,1927.75,,0.23 +07/03/2023,1929.5,1927.8,1939.9,1917.7,152.96,0.01 +06/30/2023,1929.4,1916.4,1930.8,1908.1,180.69,0.60 +06/29/2023,1917.9,1916.5,1921.3,1900.6,205.25,0.24 +06/28/2023,1913.4,1915.2,1916.7,1903.6,0.63,-0.09 +06/27/2023,1915.1,1927.4,1930.2,1912.3,0.23,-0.52 +06/26/2023,1925.1,1926.4,1934.5,1923,0.77,0.21 +06/23/2023,1921,1915,1939.3,1911.3,0.75,0.31 +06/22/2023,1915,1935.9,1935.9,1914,0.37,-1.09 +06/21/2023,1936.1,1939.5,1940.7,1922.2,0.81,-0.14 +06/20/2023,1938.9,1961.7,1961.7,1932.4,0.74,-1.28 +06/19/2023,1964.05,1969.55,1970.85,1959.9,,-0.27 +06/18/2023,1969.45,1970.85,1971.7,1968.65,,0.37 +06/16/2023,1962.2,1961.3,1970.6,1956.7,0.62,0.02 +06/15/2023,1961.8,1948.8,1963.7,1929.6,0.82,-0.36 +06/14/2023,1968.9,1957.2,1973.9,1952.5,199.71,0.53 +06/13/2023,1958.6,1971.4,1985.9,1953,198.4,-0.56 +06/12/2023,1969.7,1975.6,1981.4,1963.1,122.54,-0.38 +06/09/2023,1977.2,1980.5,1987.8,1971,130.41,-0.07 +06/08/2023,1978.6,1956.2,1985.7,1955.2,191.84,1.03 +06/07/2023,1958.4,1980,1986.5,1955.4,189.53,-1.17 +06/06/2023,1981.5,1978,1982.9,1970.3,136,0.36 +06/05/2023,1974.3,1962.3,1980.4,1953.8,179.99,0.24 +06/02/2023,1969.6,1994.6,2000.5,1963.7,209.69,-1.30 +06/01/2023,1995.5,1981.3,2000.7,1970.1,176.91,0.68 +05/31/2023,1982.1,1977.5,1993.1,1971.8,207.75,0.25 +05/30/2023,1977.1,1961.3,1981.9,1949.6,264.37,0.89 +05/29/2023,1959.75,1961.45,1968.15,1958.1,,-0.09 +05/28/2023,1961.5,1964.55,1964.55,1960.05,,-0.08 +05/26/2023,1963.1,1961.8,1975.7,1954.7,130.07,1.03 +05/25/2023,1943.1,1959.5,1965.4,1939,0,-1.00 +05/24/2023,1962.8,1975.4,1975.4,1969.2,0.19,-0.49 +05/23/2023,1972.4,1973.9,1980,1955.8,0,-0.12 +05/22/2023,1974.8,1980.5,1980.5,1980.5,0.01,-0.20 +05/19/2023,1978.7,1960,1976.7,1960,0.11,1.13 +05/18/2023,1956.5,1956.8,1956.8,1956.8,0.02,-1.22 +05/17/2023,1980.7,1983.6,1983.6,1983.6,0.01,-0.39 +05/16/2023,1988.4,2021.3,2022.7,1989.1,0.05,-1.47 +05/15/2023,2018,2013.8,2017.1,2013.8,0,-0.09 +05/12/2023,2019.8,2020.5,2027.8,2005.7,220.5,-0.03 +05/11/2023,2020.5,2036.8,2047.6,2016.7,296.98,-0.81 +05/10/2023,2037.1,2041.6,2056,2028.3,260.81,-0.28 +05/09/2023,2042.9,2028.4,2045.1,2026.4,199.7,0.48 +05/08/2023,2033.2,2024.6,2037.1,2022,182.21,0.41 +05/05/2023,2024.8,2058,2061.3,2007,283.3,-1.50 +05/04/2023,2055.7,2054.7,2085.4,2038.5,311,0.92 +05/03/2023,2037,2026.4,2050,2016,229.67,0.68 +05/02/2023,2023.3,1990.5,2028.8,1986.9,245.64,1.56 +05/01/2023,1992.2,2000.2,2015.4,1985.7,173.02,-0.35 +04/28/2023,1999.1,1997.2,2004.1,1984.4,172.45,0.01 +04/27/2023,1999,1999.8,2013.3,1982,203.9,0.61 +04/26/2023,1986.9,2000,2009.8,1986.6,0.62,-0.41 +04/25/2023,1995.1,1995.4,2005,1979.3,0.85,0.23 +04/24/2023,1990.6,1983.2,1991,1975.3,0.54,0.47 +04/21/2023,1981.3,2005.1,2007,1973,0.62,-1.42 +04/20/2023,2009.8,1996.5,2014.5,1994.2,0.42,0.59 +04/19/2023,1998,2008.5,2009.7,1971.9,0.92,-0.61 +04/18/2023,2010.3,1997.1,2013.4,1994.5,0.22,0.81 +04/17/2023,1994.2,2002.7,2007.6,1983.2,0.55,-0.40 +04/14/2023,2002.2,2041,2047.8,1995,0.72,-1.92 +04/13/2023,2041.3,2015.6,2048.6,2015.6,1.04,1.51 +04/12/2023,2010.9,2005.2,2025.7,2005.2,0.17,0.30 +04/11/2023,2004.8,1991.4,2006.5,1991.4,0.07,0.79 +04/10/2023,1989.1,2000,2006.6,1984,0.65,-1.13 +04/06/2023,2011.9,2022.2,2023.3,2005,0.49,-0.45 +04/05/2023,2020.9,2022.1,2033.8,2013.6,0.53,-0.06 +04/04/2023,2022.2,1984.6,2027.1,1979,0.81,1.93 +04/03/2023,1983.9,1968.1,1991.7,1950,0.74,0.76 +03/31/2023,1969,1981.3,1986.8,1968,0.96,-0.57 +03/30/2023,1980.3,1965.9,1984.4,1954.9,10.12,0.68 +03/29/2023,1966.9,1975.4,1976,1959.5,88.56,-0.33 +03/28/2023,1973.5,1957.8,1977.1,1949.9,183.58,0.10 +03/27/2023,1971.5,2000.3,2001.5,1962.7,107.04,-1.51 +03/24/2023,2001.7,2013.3,2023.9,1995.7,118.69,-0.58 +03/23/2023,2013.3,1992.5,2023.3,1984.4,74.55,2.37 +03/22/2023,1966.6,1959.7,1999.4,1953.7,60.53,0.42 +03/21/2023,1958.3,2000.7,2005.7,1955.9,65.17,-2.07 +03/20/2023,1999.7,2008.6,2031.7,1987,69.06,0.48 +03/17/2023,1990.2,1942.7,2010.4,1939.1,67.46,2.60 +03/16/2023,1939.7,1940.2,1954.6,1928.4,34.77,-0.43 +03/15/2023,1948.1,1924.5,1959.1,1906,84.73,1.95 +03/14/2023,1910.9,1919.4,1919.4,1899.8,261.28,-0.29 +03/13/2023,1916.5,1877.1,1919.5,1875.7,452.33,2.64 +03/10/2023,1867.2,1835.1,1874.3,1830,345.81,1.78 +03/09/2023,1834.6,1818,1839.4,1815.4,228.47,0.88 +03/08/2023,1818.6,1818,1828.7,1813.4,208.29,-0.08 +03/07/2023,1820,1852.6,1856.9,1817.1,248.23,-1.87 +03/06/2023,1854.6,1861,1864.3,1850.6,136.22,0.00 +03/03/2023,1854.6,1842.1,1864.4,1842,158.96,0.77 +03/02/2023,1840.5,1843.8,1845.3,1835.9,139.76,-0.27 +03/01/2023,1845.4,1834,1852.5,1829.6,182.58,0.47 +02/28/2023,1836.7,1823.9,1838.6,1810.8,184.51,0.65 +02/27/2023,1824.9,1818,1827.3,1812,130.43,0.87 +02/24/2023,1809.2,1825.2,1827.1,1808.8,0.4,-0.53 +02/23/2023,1818.8,1823.6,1832.7,1818.3,0.65,-0.79 +02/22/2023,1833.3,1837,1846.4,1825.1,0.57,-0.50 +02/21/2023,1842.5,1850.5,1856.4,1839,210.17,-0.43 +02/20/2023,1850.5,1847.55,1856.35,1846.3,,0.15 +02/19/2023,1847.75,1851.2,1852.15,1847.55,,0.40 +02/17/2023,1840.4,1827.4,1842.2,1818.4,0.04,-0.09 +02/16/2023,1842,1838.6,1843.7,1827.2,0.22,0.43 +02/15/2023,1834.2,1842,1842,1828.2,0.37,-1.07 +02/14/2023,1854,1854.1,1862,1846.2,0.66,0.11 +02/13/2023,1851.9,1859,1861,1850,0.57,-0.59 +02/10/2023,1862.8,1861.6,1863.5,1852.4,0.03,-0.18 +02/09/2023,1866.2,1875.3,1884.6,1859.8,0.22,-0.60 +02/08/2023,1877.4,1872.1,1880.4,1872.1,0.23,0.30 +02/07/2023,1871.7,1870,1875.7,1868,0.3,0.29 +02/06/2023,1866.2,1865.6,1880,1863.4,0.42,0.18 +02/03/2023,1862.9,1912.4,1917,1861.5,0.99,-2.79 +02/02/2023,1916.3,1952.3,1959.1,1911.3,0.75,-0.60 +02/01/2023,1927.8,1927.2,1955,1922,2.29,-0.09 +01/31/2023,1929.5,1923,1930.4,1900.6,1.91,0.34 +01/30/2023,1922.9,1928.3,1933.6,1920.3,27.22,-0.71 +01/27/2023,1936.6,1936.8,1943,1923.7,2.33,-0.05 +01/26/2023,1937.6,1955.3,1957,1926.5,2.1,-0.65 +01/25/2023,1950.3,1946,1956,1928.7,1.27,0.37 +01/24/2023,1943.1,1940.5,1950.6,1926.3,1.08,0.36 +01/23/2023,1936.2,1936.1,1943.7,1920.1,0.97,0.41 +01/20/2023,1928.2,1933.7,1939,1922,165.27,0.22 +01/19/2023,1923.9,1907,1936.9,1902,214.25,0.89 +01/18/2023,1907,1911.1,1929.8,1898.6,218.97,-0.01 +01/17/2023,1907.2,1920.1,1920.1,1905.2,0.71,-0.14 +01/16/2023,1909.9,1923.8,1931.8,1906.2,268.37,-0.52 +01/15/2023,1919.9,1923.25,1923.6,1919.85,,-0.09 +01/13/2023,1921.7,1898.8,1925.3,1895.1,247.88,1.21 +01/12/2023,1898.8,1879.7,1906.5,1872.4,265.17,1.06 +01/11/2023,1878.9,1881.3,1890.9,1870.9,222.25,0.13 +01/10/2023,1876.5,1875.7,1885.2,1872,170.51,-0.07 +01/09/2023,1877.8,1872.8,1886.4,1869.3,204.55,0.43 +01/06/2023,1869.7,1835.9,1875.2,1835.2,215.37,1.58 +01/05/2023,1840.6,1861.2,1864.3,1829.9,188.6,-0.99 +01/04/2023,1859,1845.2,1871.3,1842,198.35,0.70 +01/03/2023,1846.1,1831.8,1856.6,1831.3,212.27,0.56 +01/02/2023,1835.8,1834.55,1837.9,1831.4,,0.53 +12/30/2022,1826.2,1821.8,1832.4,1819.8,107.5,0.01 +12/29/2022,1826,1812.3,1827.3,1811.2,105.99,0.56 +12/28/2022,1815.8,1822.4,1822.8,1804.2,118.08,-0.40 +12/27/2022,1823.1,1808.2,1841.9,1808,159.62,0.74 +12/26/2022,1809.7,1805.8,1811.95,1805.55,,0.30 +12/23/2022,1804.2,1801,1812.2,1798.9,105.46,0.50 +12/22/2022,1795.3,1823.8,1829.3,1792.7,175.77,-1.65 +12/21/2022,1825.4,1827.9,1833.8,1821.3,110.18,0.00 +12/20/2022,1825.4,1796.8,1832.4,1793.7,197.5,1.54 +12/19/2022,1797.7,1801.6,1808.6,1793.2,86.09,-0.14 +12/16/2022,1800.2,1786.9,1804.2,1783.9,128.75,0.69 +12/15/2022,1787.8,1818.7,1819.7,1782,185.32,-1.70 +12/14/2022,1818.7,1822.6,1825.4,1806.2,143.8,-0.37 +12/13/2022,1825.5,1792.3,1836.9,1791.8,230.91,1.85 +12/12/2022,1792.3,1808,1809.3,1789,107.78,-1.02 +12/09/2022,1810.7,1801.9,1819,1800.1,150.94,0.51 +12/08/2022,1801.5,1799.5,1806.9,1793.2,116.27,0.19 +12/07/2022,1798,1783.3,1803.2,1780.5,155.57,0.88 +12/06/2022,1782.4,1780.8,1793.2,1779.1,127.86,0.06 +12/05/2022,1781.3,1810.5,1822.9,1778.1,179.82,-1.56 +12/02/2022,1809.6,1817,1818.7,1791.8,183.72,-0.31 +12/01/2022,1815.2,1783.1,1818.4,1782.9,226.15,3.14 +11/30/2022,1759.9,1763.4,1784.2,1758.2,192.24,-0.22 +11/29/2022,1763.7,1754.6,1773.4,1752.9,127.32,1.34 +11/28/2022,1740.3,1755,1763.5,1738.2,132.77,-0.78 +11/25/2022,1754,1751,1761.2,1745.9,134.3,0.00 +11/24/2022,1754,1751,1761.2,1745.9,134.3,0.48 +11/23/2022,1745.6,1740.8,1754.9,1719,167.77,0.33 +11/22/2022,1739.9,1739.7,1751,1737.6,153.09,0.02 +11/21/2022,1739.6,1752,1755,1733.9,166.08,-0.84 +11/18/2022,1754.4,1763.1,1769.9,1749.2,137.33,-0.49 +11/17/2022,1763,1777,1777.6,1756.6,169.1,-0.72 +11/16/2022,1775.8,1782,1788.2,1773.4,200.76,-0.06 +11/15/2022,1776.8,1774,1791.8,1770.2,283.02,-0.01 +11/14/2022,1776.9,1769.4,1778.4,1755.8,191.35,0.42 +11/11/2022,1769.4,1758.3,1775.6,1750.3,227.04,0.90 +11/10/2022,1753.7,1709.7,1760.6,1705.5,305.72,2.33 +11/09/2022,1713.7,1715.2,1725.8,1705.1,239.65,-0.13 +11/08/2022,1716,1678,1720.4,1667.1,297.62,2.11 +11/07/2022,1680.5,1678.6,1685.6,1670,187.59,0.23 +11/04/2022,1676.6,1631.7,1686.4,1631.1,293.52,2.80 +11/03/2022,1630.9,1639.1,1643.2,1618.3,254.7,-1.16 +11/02/2022,1650,1651.4,1673.1,1637.4,220.93,0.02 +11/01/2022,1649.7,1636.1,1660.3,1633.6,197.98,0.55 +10/31/2022,1640.7,1647.2,1648.5,1634.5,128.41,-0.25 +10/28/2022,1644.8,1667.2,1670.9,1640.7,196.36,-1.25 +10/27/2022,1665.6,1668.8,1674.8,1658.5,189.29,-0.22 +10/26/2022,1669.2,1657.7,1679.4,1653.8,186.93,0.68 +10/25/2022,1658,1654.5,1666.8,1641.2,182.8,0.24 +10/24/2022,1654.1,1662.9,1675.5,1648,171.02,-0.13 +10/21/2022,1656.3,1632.4,1663.1,1621.1,271.1,1.19 +10/20/2022,1636.8,1634.6,1650.3,1626.3,163.73,0.16 +10/19/2022,1634.2,1657.2,1659.8,1632.2,179.25,-1.30 +10/18/2022,1655.8,1655.9,1666,1650.6,163.17,-0.49 +10/17/2022,1664,1649.9,1674.3,1649.1,148.89,0.92 +10/14/2022,1648.9,1672.8,1677.8,1645.6,183.17,-1.68 +10/13/2022,1677,1680.2,1688.9,1648.3,237.01,-0.03 +10/12/2022,1677.5,1673.4,1685.1,1668,131.77,-0.50 +10/11/2022,1686,1675.6,1691.3,1667.5,171.81,0.64 +10/10/2022,1675.2,1703.4,1707.4,1672.5,157.15,-1.99 +10/07/2022,1709.3,1721,1722.8,1698.4,157.45,-0.67 +10/06/2022,1720.8,1725.5,1734.2,1714.8,139.44,0.00 +10/05/2022,1720.8,1734.4,1736.6,1708.8,173.22,-0.56 +10/04/2022,1730.5,1708.4,1738.7,1704,205.08,1.67 +10/03/2022,1702,1670.5,1710.4,1666.5,215.49,1.79 +09/30/2022,1672,1669.5,1684.4,1667.5,179.99,0.20 +09/29/2022,1668.6,1669,1673.1,1649.3,201.96,-0.08 +09/28/2022,1670,1636.5,1671.6,1622.2,279.82,2.07 +09/27/2022,1636.2,1629.2,1650.1,1628.7,197.06,0.17 +09/26/2022,1633.4,1651,1657.2,1627.7,219.86,-1.34 +09/23/2022,1655.6,1680.1,1685,1646.6,243.05,-1.52 +09/22/2022,1681.1,1682.8,1693.5,1663.3,241.28,0.32 +09/21/2022,1675.7,1673.2,1696.9,1661.3,227.94,0.28 +09/20/2022,1671.1,1684.9,1688.8,1668.1,143.93,-0.42 +09/19/2022,1678.2,1685.4,1688.8,1667.6,141.17,-0.31 +09/16/2022,1683.5,1673.7,1689.9,1661.9,217.23,0.37 +09/15/2022,1677.3,1707.2,1707.8,1668.9,268.09,-1.86 +09/14/2022,1709.1,1711.6,1717.3,1703.3,163.29,-0.48 +09/13/2022,1717.4,1736,1742.9,1706.7,232.7,-1.33 +09/12/2022,1740.6,1728.4,1746.4,1722.3,154.37,0.69 +09/09/2022,1728.6,1719.6,1740.5,1719.4,154.71,0.49 +09/08/2022,1720.2,1729.5,1739.4,1713.7,184.18,-0.44 +09/07/2022,1727.8,1712.9,1731.2,1701.7,173.62,1.17 +09/06/2022,1707.9,1719.7,1719.7,1714.2,0.02,-0.29 +09/05/2022,1712.9,1724.2,1737.4,1710.6,206.27,-0.33 +09/04/2022,1718.65,1723.6,1723.75,1718.65,,-0.23 +09/02/2022,1722.6,1707.8,1729.5,1705.9,174.68,0.78 +09/01/2022,1709.3,1723,1723,1699.1,198.62,-0.98 +08/31/2022,1726.2,1735.5,1738,1720.6,176.73,-0.58 +08/30/2022,1736.3,1749.8,1752.8,1732.9,130.66,-0.77 +08/29/2022,1749.7,1748.4,1757.9,1731.4,156.22,-0.01 +08/26/2022,1749.8,1771.8,1772.3,1746.2,176.9,-1.22 +08/25/2022,1771.4,1764.4,1778.8,1763,117.57,0.56 +08/24/2022,1761.5,1761.3,1769.5,1754.8,112.65,0.02 +08/23/2022,1761.2,1750,1767.5,1743.1,145.26,0.73 +08/22/2022,1748.4,1760.6,1762.1,1740.2,142.86,-0.82 +08/19/2022,1762.9,1773.1,1773.3,1759.1,138.7,-0.47 +08/18/2022,1771.2,1777.1,1786.3,1768.8,124.32,-0.31 +08/17/2022,1776.7,1790.8,1796.6,1773.9,137.83,-0.73 +08/16/2022,1789.7,1795.5,1798,1785.4,94.4,-0.47 +08/15/2022,1798.1,1818.9,1818.9,1787.6,137.77,-0.96 +08/12/2022,1815.5,1805.2,1819.1,1799.6,118.65,0.46 +08/11/2022,1807.2,1807.9,1814.9,1798.6,121.26,-0.36 +08/10/2022,1813.7,1811.5,1824.6,1803.3,154.59,0.08 +08/09/2022,1812.3,1805.5,1817,1799.4,120.51,0.39 +08/08/2022,1805.2,1790.3,1806.4,1786.9,103.68,0.78 +08/05/2022,1791.2,1807.7,1811.6,1780.2,168.9,-0.87 +08/04/2022,1806.9,1782.1,1812,1779.4,153.29,1.72 +08/03/2022,1776.4,1777.3,1789.4,1770,151.73,-0.74 +08/02/2022,1789.7,1789.2,1805,1776,174.17,0.11 +08/01/2022,1787.7,1782.5,1792.5,1774.3,133.74,0.33 +07/29/2022,1781.8,1773.1,1784.6,1768.4,136.89,0.71 +07/28/2022,1769.2,1751.4,1774.4,1750.4,192.86,2.91 +07/27/2022,1719.1,1715.2,1739.6,1709.1,144.87,0.08 +07/26/2022,1717.7,1717.9,1726.4,1711.5,147.37,-0.08 +07/25/2022,1719.1,1726.3,1734.6,1712.9,160.72,-0.48 +07/22/2022,1727.4,1717.2,1738.3,1711.7,200.62,0.82 +07/21/2022,1713.4,1693.7,1719.5,1678.4,248.88,0.78 +07/20/2022,1700.2,1709.5,1712.7,1690.1,174.47,-0.61 +07/19/2022,1710.7,1707.2,1716.5,1702.6,131.77,0.03 +07/18/2022,1710.2,1706.4,1722,1704.4,157.54,0.39 +07/15/2022,1703.6,1708.2,1714.2,1696.6,176.8,-0.13 +07/14/2022,1705.8,1733.6,1734.8,1695,266.35,-1.71 +07/13/2022,1735.5,1723.6,1744.3,1704.5,300.55,0.62 +07/12/2022,1724.8,1731.3,1742.2,1721.6,255.17,-0.40 +07/11/2022,1731.7,1741.5,1743,1729,171.9,-0.61 +07/08/2022,1742.3,1738.7,1751.7,1726,189.18,0.15 +07/07/2022,1739.7,1737.2,1748.2,1734.7,151.26,0.18 +07/06/2022,1736.5,1764.2,1771.5,1730.7,258.82,-1.83 +07/05/2022,1768.9,1817,1817,1768.9,1.33,0.28 +07/04/2022,1763.9,1814.4,1815.2,1763,310.37,-2.09 +07/01/2022,1801.5,1808.1,1813.6,1783.4,249.49,-0.32 +06/30/2022,1807.3,1819.2,1826.8,1802.5,208.9,-0.56 +06/29/2022,1817.5,1821.4,1834.9,1810.7,155.54,-0.20 +06/28/2022,1821.2,1823.6,1830.9,1819.1,111.4,-0.20 +06/27/2022,1824.8,1839.6,1842.8,1821.8,143.82,-0.30 +06/24/2022,1830.3,1824.2,1833.7,1817.7,139.72,0.03 +06/23/2022,1829.8,1839.7,1848.9,1823.5,167.07,-0.47 +06/22/2022,1838.4,1834.9,1850.3,1824.5,149.55,-0.02 +06/21/2022,1838.8,1840.6,1848.4,1830.7,176.3,0.00 +06/20/2022,1838.8,1840.6,1848.4,1830.7,176.3,-0.10 +06/17/2022,1840.6,1859.3,1861.5,1836.1,141.72,-0.50 +06/16/2022,1849.9,1835.8,1860.2,1816.3,180.89,1.67 +06/15/2022,1819.6,1809.7,1845.4,1808.4,203.42,0.34 +06/14/2022,1813.5,1820.9,1833.3,1806.1,165.15,-1.00 +06/13/2022,1831.8,1879,1882.5,1819,252.54,-2.33 +06/10/2022,1875.5,1850.4,1879.6,1826.5,267.2,1.23 +06/09/2022,1852.8,1855.1,1857.8,1841.9,131.29,-0.20 +06/08/2022,1856.5,1855,1862.4,1846.6,114.14,0.24 +06/07/2022,1852.1,1843.5,1858.2,1838.5,119.21,0.46 +06/06/2022,1843.7,1853.7,1861.2,1843,103.18,-0.35 +06/03/2022,1850.2,1872.6,1878.6,1849.7,115.34,-1.13 +06/02/2022,1871.4,1849.9,1874.4,1846.5,127.47,1.23 +06/01/2022,1848.7,1840,1853,1830.2,158.04,0.02 +05/31/2022,1848.4,1856.5,1867.9,1837.6,201.8,0.00 +05/30/2022,1848.4,1856.5,1867.9,1837.6,201.8,-0.48 +05/27/2022,1857.3,1855.1,1866.9,1851.9,123.76,0.53 +05/26/2022,1847.6,1851.8,1852.8,1836.3,123.36,0.07 +05/25/2022,1846.3,1865.4,1866.7,1838.7,182.82,-1.02 +05/24/2022,1865.4,1852.3,1869.1,1847.6,174.76,0.95 +05/23/2022,1847.8,1844.4,1864.3,1843.3,163.27,0.31 +05/20/2022,1842.1,1839.6,1847.8,1830.6,143.05,0.05 +05/19/2022,1841.2,1815.1,1848.2,1808.4,175.24,1.39 +05/18/2022,1815.9,1813.2,1822.9,1805,150.35,-0.16 +05/17/2022,1818.9,1823.9,1834.8,1811,137.29,0.27 +05/16/2022,1814,1809.4,1826,1785,159.49,0.32 +05/13/2022,1808.2,1821.4,1827.6,1797.2,179.48,-0.90 +05/12/2022,1824.6,1852.3,1858.8,1820.1,255.61,-1.57 +05/11/2022,1853.7,1836.6,1857.8,1830.6,243.56,0.69 +05/10/2022,1841,1853.9,1864.7,1834.5,260.81,-0.95 +05/09/2022,1858.6,1883.7,1885.6,1851,218.82,-1.29 +05/06/2022,1882.8,1877.5,1894,1865,194.28,0.38 +05/05/2022,1875.7,1884.1,1910.7,1872.3,218.39,0.37 +05/04/2022,1868.8,1868.3,1892,1861.1,161.48,-0.10 +05/03/2022,1870.6,1863.6,1878.4,1849.7,167.43,0.38 +05/02/2022,1863.6,1896.2,1900.4,1853.4,193.83,-2.52 +04/29/2022,1911.7,1895.8,1921.3,1893.5,177.14,1.08 +04/28/2022,1891.3,1886.8,1897.8,1870.9,170.91,0.14 +04/27/2022,1888.7,1907.4,1908.1,1881.6,178.2,-0.81 +04/26/2022,1904.1,1899.8,1912.2,1896.3,166.2,0.43 +04/25/2022,1896,1931.9,1935.5,1891.8,231.49,-1.98 +04/22/2022,1934.3,1953.1,1957.8,1928,176.68,-0.71 +04/21/2022,1948.2,1960,1960.1,1938,154.92,-0.38 +04/20/2022,1955.6,1952.7,1960.9,1941,139.51,-0.17 +04/19/2022,1959,1981.2,1985.1,1945.5,181.44,-1.38 +04/18/2022,1986.4,1978.5,2003,1974.4,138.13,0.58 +04/14/2022,1974.9,1981.6,1984,1962.7,139.42,-0.49 +04/13/2022,1984.7,1970.5,1985.8,1966.3,132.03,0.44 +04/12/2022,1976.1,1957.4,1982.7,1953,172.39,1.43 +04/11/2022,1948.2,1949.6,1974.6,1942.9,184.39,0.13 +04/08/2022,1945.6,1934.3,1952.2,1930.4,142.5,0.40 +04/07/2022,1937.8,1928.1,1941.7,1923.3,122.81,0.76 +04/06/2022,1923.1,1927.6,1937.6,1916.2,153.97,-0.23 +04/05/2022,1927.5,1937.3,1948.9,1920.9,147.26,-0.34 +04/04/2022,1934,1927.1,1941.6,1918.2,108.44,0.54 +04/01/2022,1923.7,1942.4,1944.5,1921.4,135.15,-1.55 +03/31/2022,1954,1937.3,1955,1923,155.3,0.77 +03/30/2022,1939,1924,1943.4,1920.1,136.04,1.40 +03/29/2022,1912.2,1922.4,1929.4,1888.3,128.05,-1.42 +03/28/2022,1939.8,1958.7,1959.8,1915.7,181.37,-0.74 +03/25/2022,1954.2,1957.8,1965.1,1942.6,147.9,-0.41 +03/24/2022,1962.2,1944.1,1967.2,1937.4,181.2,1.29 +03/23/2022,1937.3,1920.9,1948.8,1915.6,153.31,0.82 +03/22/2022,1921.5,1936.1,1939.5,1909.8,153.28,-0.41 +03/21/2022,1929.5,1922.4,1941.8,1917.2,146.41,0.01 +03/18/2022,1929.3,1943.9,1946.2,1918,150.88,-0.72 +03/17/2022,1943.2,1928.4,1951,1924,149.83,1.78 +03/16/2022,1909.2,1920.1,1930.1,1895.2,195.46,-1.06 +03/15/2022,1929.7,1953.7,1956.9,1908.1,220.37,-1.59 +03/14/2022,1960.8,1988.7,1994.8,1952,162.2,-1.22 +03/11/2022,1985,2000.3,2004,1960.6,262.09,-0.77 +03/10/2022,2000.4,1992.8,2015.1,1975,303.27,0.61 +03/09/2022,1988.2,2060.2,2068.5,1981,360.35,-2.70 +03/08/2022,2043.3,2001,2078.8,1985.8,447.65,2.37 +03/07/2022,1995.9,1978.5,2007.5,1964.2,372.19,1.49 +03/04/2022,1966.6,1938.5,1974.9,1931.5,241.53,1.59 +03/03/2022,1935.9,1931.7,1944.6,1923.1,180.21,0.71 +03/02/2022,1922.3,1945.3,1951.4,1916,227.98,-1.11 +03/01/2022,1943.8,1908.4,1952.6,1903,224,2.27 +02/28/2022,1900.7,1921,1935.2,1892.2,249.27,0.69 +02/25/2022,1887.6,1906.5,1925,1884.4,229.78,-2.01 +02/24/2022,1926.3,1911.9,1976.5,1878.6,423.05,0.83 +02/23/2022,1910.4,1901.2,1912.9,1891.1,154.84,0.16 +02/22/2022,1907.4,1903.5,1918.3,1889.7,334.59,0.00 +02/21/2022,1907.4,1903.5,1918.3,1889.7,334.59,0.40 +02/18/2022,1899.8,1901.4,1905,1888,161.75,-0.12 +02/17/2022,1902,1872,1904,1869.7,268.55,1.63 +02/16/2022,1871.5,1855.5,1874.6,1851.8,141.49,0.82 +02/15/2022,1856.2,1873.8,1881.6,1845.4,214.88,-0.71 +02/14/2022,1869.4,1862.2,1876.5,1851.9,231.02,1.48 +02/11/2022,1842.1,1827,1867.4,1821.1,239.09,0.26 +02/10/2022,1837.4,1834,1843.3,1821.8,227.46,0.04 +02/09/2022,1836.6,1827,1837.1,1825.5,136.72,0.48 +02/08/2022,1827.9,1821.5,1829.9,1816,142.41,0.33 +02/07/2022,1821.8,1808,1824.6,1807.5,139.81,0.77 +02/04/2022,1807.8,1805.4,1815.8,1792.1,177.71,0.21 +02/03/2022,1804.1,1807.4,1809.5,1788.5,173.72,-0.34 +02/02/2022,1810.3,1800.8,1812,1794.6,123.02,0.49 +02/01/2022,1801.5,1798.9,1809.7,1796.2,128.88,0.28 +01/31/2022,1796.4,1792.8,1800.9,1785.8,139.42,0.55 +01/28/2022,1786.6,1799.6,1800.3,1780.6,217.15,-0.36 +01/27/2022,1793.1,1819,1821.4,1790.6,196.04,-2.00 +01/26/2022,1829.7,1848,1850.2,1814.1,270.03,-1.23 +01/25/2022,1852.5,1843.6,1854.2,1834.4,197.8,0.59 +01/24/2022,1841.7,1835.2,1844.9,1829.3,244.33,0.54 +01/21/2022,1831.8,1840.6,1843.7,1828.4,225.25,-0.59 +01/20/2022,1842.6,1840.1,1848.5,1836.2,233.86,-0.03 +01/19/2022,1843.2,1812.9,1843.9,1809,318.49,1.60 +01/18/2022,1814.1,1818.7,1824.2,1806.9,0.34,0.09 +01/17/2022,1812.4,1818.7,1822.9,1804.7,362.94,-0.23 +01/14/2022,1816.5,1822.1,1829.3,1814.2,174.94,-0.27 +01/13/2022,1821.4,1825.7,1828.3,1811.8,215.52,-0.32 +01/12/2022,1827.3,1821.3,1828.2,1814.4,192.98,0.48 +01/11/2022,1818.5,1801.3,1823.1,1799.7,184.15,1.10 +01/10/2022,1798.8,1796.4,1802,1789.3,173.04,0.08 +01/07/2022,1797.4,1791,1798.4,1781.3,238.93,0.46 +01/06/2022,1789.2,1810.6,1811.6,1785.4,238.64,-1.97 +01/05/2022,1825.1,1815.2,1830.7,1808.2,173.34,0.58 +01/04/2022,1814.6,1801.1,1817.2,1798.1,167.71,0.81 +01/03/2022,1800.1,1830.1,1833,1798.2,168.31,-1.56 +12/31/2021,1828.6,1817,1831.4,1815.4,106.6,0.80 +12/30/2021,1814.1,1805.6,1818.1,1796.2,113.43,0.46 +12/29/2021,1805.8,1806.6,1808,1789.1,138.69,-0.28 +12/28/2021,1810.9,1812.1,1821.6,1805.5,100.54,0.12 +12/27/2021,1808.8,1810.2,1814.6,1803.6,84.23,-0.16 +12/23/2021,1811.7,1805.6,1812,1799,104.84,0.53 +12/22/2021,1802.2,1789.4,1806.3,1785.8,110.41,0.75 +12/21/2021,1788.7,1791.4,1801.7,1785,134.15,-0.33 +12/20/2021,1794.6,1800.2,1804.6,1789,105.39,-0.57 +12/17/2021,1804.9,1801.5,1815.7,1796.5,156.61,0.37 +12/16/2021,1798.2,1777.9,1800.7,1775.7,167.78,1.91 +12/15/2021,1764.5,1771.9,1781.3,1753,161.1,-0.44 +12/14/2021,1772.3,1787.6,1789.8,1766.1,153.25,-0.89 +12/13/2021,1788.3,1784.2,1792.8,1782.2,106.06,0.20 +12/10/2021,1784.8,1776.3,1791,1770.4,142,0.46 +12/09/2021,1776.7,1784.3,1788.4,1773.3,123.97,-0.49 +12/08/2021,1785.5,1785.1,1794.3,1780.1,109.69,0.04 +12/07/2021,1784.7,1779.5,1789.3,1772.4,129.89,0.29 +12/06/2021,1779.5,1787.7,1789,1776.4,104.48,-0.25 +12/03/2021,1783.9,1769.4,1788,1766,175.18,1.20 +12/02/2021,1762.7,1783.8,1785.2,1762.2,172.72,-1.21 +12/01/2021,1784.3,1777.4,1795.7,1773.7,180.34,0.44 +11/30/2021,1776.5,1786.9,1811.4,1771.2,242.86,-0.49 +11/29/2021,1785.2,1795.2,1801.5,1782,151.37,-0.10 +11/26/2021,1786.9,1788.4,1817.7,1780.5,2.97,-0.07 +11/25/2021,1788.1,1792.3,1819.3,1781.6,180.64,0.21 +11/24/2021,1784.3,1789.8,1796.2,1777.4,203.24,0.03 +11/23/2021,1783.8,1807.1,1812.5,1781.7,311.35,-1.25 +11/22/2021,1806.3,1848.3,1850.4,1802.4,352.86,-2.45 +11/19/2021,1851.6,1860.8,1868.1,1844.2,234.08,-0.53 +11/18/2021,1861.4,1869.5,1873.3,1856.6,186.06,-0.47 +11/17/2021,1870.2,1851.6,1870.6,1851.1,172.42,0.87 +11/16/2021,1854.1,1864.9,1879.5,1851,220.43,-0.67 +11/15/2021,1866.6,1872.6,1873,1858.5,221.21,-0.10 +11/12/2021,1868.5,1864.3,1871.4,1847.5,201.36,0.25 +11/11/2021,1863.9,1851.5,1868.7,1845.1,205.31,0.84 +11/10/2021,1848.3,1834.5,1870.6,1823,352.79,0.96 +11/09/2021,1830.8,1826.9,1834.8,1821,224.41,0.15 +11/08/2021,1828,1820.6,1828.3,1813.8,200.41,0.62 +11/05/2021,1816.8,1792.6,1820.1,1785.3,299.62,1.30 +11/04/2021,1793.5,1769.9,1800.3,1769.3,222.61,1.68 +11/03/2021,1763.9,1789.2,1789.3,1758.5,257.43,-1.43 +11/02/2021,1789.4,1794.8,1797.8,1787.4,145.79,-0.36 +11/01/2021,1795.8,1785.3,1797.5,1780.2,143.33,0.67 +10/29/2021,1783.9,1801.5,1802.9,1772.4,254.51,-1.04 +10/28/2021,1802.6,1798.7,1812.7,1793.1,220.88,0.21 +10/27/2021,1798.8,1795,1801,1784.3,182.8,0.30 +10/26/2021,1793.4,1808.7,1809.8,1783,197.93,-0.74 +10/25/2021,1806.8,1794.2,1811.5,1793,153.59,0.58 +10/22/2021,1796.3,1783.7,1815.5,1783.4,312.81,0.81 +10/21/2021,1781.9,1782.5,1790.3,1776.8,138.73,-0.17 +10/20/2021,1784.9,1769.4,1789.6,1767.1,174.08,0.81 +10/19/2021,1770.5,1764.8,1786,1763.4,166.97,0.27 +10/18/2021,1765.7,1767.5,1772.5,1760.3,152.74,-0.15 +10/15/2021,1768.3,1797.3,1797.7,1765.1,202.63,-1.65 +10/14/2021,1797.9,1793.6,1801.9,1787.6,164.65,0.18 +10/13/2021,1794.7,1760.4,1797.4,1757.9,299.04,2.01 +10/12/2021,1759.3,1753.6,1770,1750.5,168.11,0.21 +10/11/2021,1755.7,1757.4,1761.1,1749.9,114.77,-0.10 +10/08/2021,1757.4,1757,1782.4,1753.6,240.37,-0.10 +10/07/2021,1759.2,1763.8,1767.7,1752,146.41,-0.15 +10/06/2021,1761.8,1760.5,1765.9,1745.4,159.22,0.05 +10/05/2021,1760.9,1770.8,1771.1,1748.6,151.42,-0.38 +10/04/2021,1767.6,1762.6,1771.5,1747.7,166.18,0.52 +10/01/2021,1758.4,1757.2,1765.2,1749.9,151.2,0.08 +09/30/2021,1757,1726,1765,1721.8,246.37,1.98 +09/29/2021,1722.9,1734,1746,1721.1,177.39,-0.84 +09/28/2021,1737.5,1750,1754.3,1727.8,215.84,-0.83 +09/27/2021,1752,1751.8,1760.9,1744.7,137.57,0.02 +09/24/2021,1751.7,1743.7,1758,1740.2,151.55,0.11 +09/23/2021,1749.8,1769.2,1777.1,1737.5,225.46,-1.63 +09/22/2021,1778.8,1775,1788.4,1764.6,172.35,0.03 +09/21/2021,1778.2,1765.5,1782.8,1758.3,141.62,0.82 +09/20/2021,1763.8,1754.2,1768.4,1742.3,152.45,0.71 +09/17/2021,1751.4,1754.6,1767.8,1747.1,183.25,-0.30 +09/16/2021,1756.7,1795.5,1797.3,1745.5,255.27,-2.12 +09/15/2021,1794.8,1806.6,1808.5,1791.7,139.3,-0.68 +09/14/2021,1807.1,1794.8,1810.6,1780.6,197.95,0.71 +09/13/2021,1794.4,1789.8,1800.2,1784.4,114.31,0.13 +09/10/2021,1792.1,1796.2,1806,1788.2,136.25,-0.44 +09/09/2021,1800,1790.9,1803.4,1785.1,154.13,0.36 +09/08/2021,1793.5,1796.1,1804.4,1783.1,161.26,-0.22 +09/07/2021,1797.4,1824,1824.4,1792.8,0.02,-0.06 +09/06/2021,1798.5,1833.5,1833.5,1793.7,252.48,-1.92 +09/03/2021,1833.7,1811.5,1836.9,1810.9,184.98,1.23 +09/02/2021,1811.5,1816.2,1819.6,1806.5,113.03,-0.25 +09/01/2021,1816,1816.7,1822.7,1810.6,140.12,-0.12 +08/31/2021,1818.1,1812.2,1821.9,1803.4,170.39,0.33 +08/30/2021,1812.2,1821.6,1826.5,1810,104.88,-0.40 +08/27/2021,1819.5,1795.2,1821.9,1785.2,203.64,1.35 +08/26/2021,1795.2,1793,1800.4,1781.3,134.53,0.23 +08/25/2021,1791,1805.1,1805.3,1784,163.46,-0.97 +08/24/2021,1808.5,1807.6,1812.2,1802.6,114.79,0.12 +08/23/2021,1806.3,1781.2,1809.1,1778,156.32,1.25 +08/20/2021,1784,1782.8,1791,1780,107.97,0.05 +08/19/2021,1783.1,1789.5,1795,1774.6,151.25,-0.07 +08/18/2021,1784.4,1787.8,1795.7,1778.8,132.73,-0.19 +08/17/2021,1787.8,1789.1,1797.6,1782.1,144.82,-0.11 +08/16/2021,1789.8,1780.7,1791.3,1772,137.7,0.65 +08/13/2021,1778.2,1754.4,1781.9,1753,144.81,1.51 +08/12/2021,1751.8,1752.9,1759.6,1742.6,137.12,-0.09 +08/11/2021,1753.3,1730.4,1756.7,1724.6,185.44,1.25 +08/10/2021,1731.7,1732,1739.4,1718.5,182.56,0.30 +08/09/2021,1726.5,1765,1765.7,1677.9,289.54,-2.08 +08/06/2021,1763.1,1806.7,1807,1759.5,323.15,-2.53 +08/05/2021,1808.9,1814.9,1817.9,1799.7,169.84,-0.31 +08/04/2021,1814.5,1813.7,1835.9,1808.3,244.68,0.02 +08/03/2021,1814.1,1816.8,1818.2,1809.5,103.45,-0.44 +08/02/2021,1822.2,1817,1823.2,1808.2,159.76,0.28 +07/30/2021,1817.2,1832.5,1835.5,1813.1,157.14,-1.01 +07/29/2021,1835.8,1811.5,1837.5,1810.9,212.07,2.01 +07/28/2021,1799.7,1798.6,1809,1790.7,209.78,-0.01 +07/27/2021,1799.8,1797.1,1805.4,1792.8,177.04,0.03 +07/26/2021,1799.2,1802.3,1812,1796,204.55,-0.14 +07/23/2021,1801.8,1807.7,1810.7,1789.1,236.76,-0.20 +07/22/2021,1805.4,1803.9,1808.4,1791.9,193.32,0.11 +07/21/2021,1803.4,1810.6,1814.4,1794.3,218.64,-0.44 +07/20/2021,1811.4,1813.5,1825.9,1805.2,221.14,0.12 +07/19/2021,1809.2,1811.6,1818,1795,249.68,-0.32 +07/16/2021,1815,1830.7,1832.7,1809.5,184.66,-0.77 +07/15/2021,1829,1828.7,1835,1820.6,175.61,0.22 +07/14/2021,1825,1808.3,1831.1,1804.9,229.88,0.83 +07/13/2021,1809.9,1806.7,1818,1798.7,242.18,0.22 +07/12/2021,1805.9,1808.5,1811,1791,201.42,-0.26 +07/09/2021,1810.6,1803.2,1813,1796.6,185.58,0.58 +07/08/2021,1800.2,1803.8,1819.5,1793.5,249.34,-0.11 +07/07/2021,1802.1,1797,1810.2,1794.1,171.08,0.40 +07/06/2021,1795,1790.7,1814.8,1790.1,0.26,0.04 +07/05/2021,1794.2,1787.5,1815.7,1784.7,276.6,0.61 +07/02/2021,1783.3,1777.5,1795.9,1774.4,205.86,0.37 +07/01/2021,1776.8,1770.8,1783.4,1765.9,171.44,0.29 +06/30/2021,1771.6,1761.9,1774.7,1753.2,177.89,0.45 +06/29/2021,1763.6,1778.8,1779.2,1750.1,239.91,-0.96 +06/28/2021,1780.7,1782,1786.1,1770.4,160.79,0.16 +06/25/2021,1777.8,1775.7,1791,1773.6,161.2,0.06 +06/24/2021,1776.7,1778.2,1788.6,1772.7,152.23,-0.38 +06/23/2021,1783.4,1779.1,1795.6,1773.1,179.27,0.34 +06/22/2021,1777.4,1783.2,1790.1,1771.2,172.75,-0.31 +06/21/2021,1782.9,1764.3,1786.9,1764.1,195.52,0.79 +06/18/2021,1769,1773.9,1797.9,1761.2,264.61,-0.33 +06/17/2021,1774.8,1812.3,1826.4,1767.9,385.89,-4.65 +06/16/2021,1861.4,1861,1866,1804.4,234.1,0.27 +06/15/2021,1856.4,1867.8,1870.9,1853,155.34,-0.51 +06/14/2021,1865.9,1879.6,1879.7,1845.7,242.3,-0.73 +06/11/2021,1879.6,1901.9,1906.2,1876.1,220.46,-0.89 +06/10/2021,1896.4,1891.4,1903,1871.8,250.55,0.05 +06/09/2021,1895.5,1894.4,1901.7,1889.3,147.33,0.06 +06/08/2021,1894.4,1901.6,1906.9,1885.7,173.6,-0.23 +06/07/2021,1898.8,1894.3,1902.9,1883.7,146.02,0.36 +06/04/2021,1892,1872.7,1899,1855.6,228.83,1.00 +06/03/2021,1873.3,1910.5,1912.3,1866.7,278.58,-1.92 +06/02/2021,1909.9,1903,1911.8,1896.4,166.04,0.26 +06/01/2021,1905,1906.8,1919.2,1894.5,290.65,0.00 +05/31/2021,1905,1906.8,1919.2,1894.5,290.65,-0.02 +05/28/2021,1905.3,1899.8,1908.8,1884.3,198.14,0.51 +05/27/2021,1895.7,1896.8,1903.9,1888.2,35.79,-0.29 +05/26/2021,1901.2,1900,1913.3,1890.7,170.53,0.17 +05/25/2021,1898,1881.2,1901.2,1873.2,316.67,0.72 +05/24/2021,1884.5,1883.5,1887.9,1875.7,183.31,0.42 +05/21/2021,1876.7,1878.1,1890.3,1870.3,234.29,-0.28 +05/20/2021,1881.9,1869.9,1885.3,1864.2,223.57,0.02 +05/19/2021,1881.5,1870.2,1891.3,1852.2,398.21,0.72 +05/18/2021,1868,1867.3,1875.9,1863.5,229.02,0.02 +05/17/2021,1867.6,1845.9,1869.3,1841.1,267.71,1.60 +05/14/2021,1838.1,1826.4,1847.1,1819,224.38,0.77 +05/13/2021,1824,1816.2,1829.1,1808.4,249.93,0.07 +05/12/2021,1822.8,1838.2,1844.7,1813,339.21,-0.72 +05/11/2021,1836.1,1836.2,1842.5,1817.8,311.1,-0.08 +05/10/2021,1837.6,1835.4,1846.3,1830.5,269.71,0.34 +05/07/2021,1831.3,1815.4,1844.6,1813.4,367.7,0.86 +05/06/2021,1815.7,1787,1818.6,1781.8,287.63,1.76 +05/05/2021,1784.3,1778.4,1788.1,1769.3,178.81,0.47 +05/04/2021,1776,1793.2,1799.5,1769.2,246.59,-0.88 +05/03/2021,1791.8,1768.1,1798.9,1765.6,204.54,1.36 +04/30/2021,1767.7,1772.4,1773.3,1763.3,167.29,-0.03 +04/29/2021,1768.3,1781.9,1789.9,1754.6,231.52,-0.32 +04/28/2021,1773.9,1776.4,1782.7,1761.8,198.58,-0.28 +04/27/2021,1778.8,1781.1,1785.9,1773.9,147.95,-0.07 +04/26/2021,1780.1,1776.1,1783.1,1768.2,143.36,0.13 +04/23/2021,1777.8,1784,1796.3,1769.5,175.85,-0.24 +04/22/2021,1782,1794.5,1798.1,1777.1,163.75,-0.62 +04/21/2021,1793.1,1779.1,1798.4,1776.6,173.97,0.83 +04/20/2021,1778.4,1770.5,1780.8,1763.5,169.04,0.44 +04/19/2021,1770.6,1778.8,1790.4,1766.6,180.73,-0.54 +04/16/2021,1780.2,1764.8,1784.7,1760.3,173.5,0.76 +04/15/2021,1766.8,1736.6,1770.6,1734.4,198.14,1.76 +04/14/2021,1736.3,1746.4,1750.7,1732.3,145.26,-0.65 +04/13/2021,1747.6,1732.2,1749.5,1723.2,175.59,0.86 +04/12/2021,1732.7,1744.5,1746.2,1727,125.36,-0.69 +04/09/2021,1744.8,1756.5,1758.2,1730.8,171.4,-0.76 +04/08/2021,1758.2,1738.6,1759.4,1733.6,144.57,0.95 +04/07/2021,1741.6,1744.4,1745.4,1731.2,122.8,-0.08 +04/06/2021,1743,1729.2,1746.7,1728.2,152.6,0.82 +04/05/2021,1728.8,1730,1734.4,1721.6,101.75,0.02 +04/01/2021,1728.4,1709,1732,1706.4,170.43,0.75 +03/31/2021,1715.6,1685.9,1716.3,1677.3,210.77,1.76 +03/30/2021,1686,1713,1714.8,1678.3,225.87,-1.53 +03/29/2021,1712.2,1731.5,1732.6,1703.3,135.46,-1.16 +03/26/2021,1732.3,1725.5,1735.5,1718.8,172.94,0.42 +03/25/2021,1725.1,1733.2,1744.8,1720.3,226.21,-0.47 +03/24/2021,1733.2,1725.9,1737.7,1722.3,186.52,0.47 +03/23/2021,1725.1,1738.5,1742,1722.7,226.2,-0.75 +03/22/2021,1738.1,1745.6,1747,1726.4,196.31,-0.21 +03/19/2021,1741.7,1733.7,1746.1,1727.1,213.28,0.53 +03/18/2021,1732.5,1744,1754.2,1716.6,251.76,0.31 +03/17/2021,1727.1,1730,1750.6,1722,220.55,-0.22 +03/16/2021,1730.9,1730.7,1740.5,1724.4,173.89,0.10 +03/15/2021,1729.2,1726.5,1733.2,1719.2,163.05,0.55 +03/12/2021,1719.8,1720.5,1728,1696.6,232.21,-0.16 +03/11/2021,1722.6,1725,1738,1716.8,215.34,0.05 +03/10/2021,1721.8,1714.5,1725.3,1705.6,226.89,0.29 +03/09/2021,1716.9,1679.3,1718.7,1676.7,248.95,2.32 +03/08/2021,1678,1701.6,1712,1673.3,273.91,-1.21 +03/05/2021,1698.5,1695.3,1705.7,1683,269.33,-0.13 +03/04/2021,1700.7,1708.4,1721.6,1687.6,277.45,-0.88 +03/03/2021,1715.8,1736.5,1739.1,1699.4,255.65,-1.03 +03/02/2021,1733.6,1722.8,1737.8,1704.6,235.96,0.62 +03/01/2021,1723,1732.8,1757.4,1717.2,241.92,-0.34 +02/26/2021,1728.8,1770.9,1773.8,1714.9,362.55,-2.62 +02/25/2021,1775.4,1804.9,1805,1763.9,316.25,-1.25 +02/24/2021,1797.9,1805,1813,1782.2,224.06,-0.44 +02/23/2021,1805.9,1809.3,1815.2,1794.5,191.15,-0.14 +02/22/2021,1808.4,1782,1812.4,1778.6,221.2,1.74 +02/19/2021,1777.4,1774.6,1790.9,1759,251.78,0.14 +02/18/2021,1775,1776,1788.8,1766.6,224.77,0.12 +02/17/2021,1772.8,1793.1,1794.2,1767.9,257.34,-1.46 +02/16/2021,1799,1826,1827.1,1788.1,355.92,0.00 +02/15/2021,1799,1826,1827.1,1788.1,355.92,-1.33 +02/12/2021,1823.2,1825.4,1831.5,1810.1,171.9,-0.20 +02/11/2021,1826.8,1844.3,1848.6,1821.7,147.02,-0.86 +02/10/2021,1842.7,1838.3,1856.6,1834,176.44,0.28 +02/09/2021,1837.5,1832.4,1849.5,1830.3,154.39,0.18 +02/08/2021,1834.2,1818.1,1840.6,1807.3,177.56,1.17 +02/05/2021,1813,1794.3,1816,1792.2,205.76,1.22 +02/04/2021,1791.2,1834.5,1835.7,1784.6,279.62,-2.39 +02/03/2021,1835.1,1838.5,1845.9,1830.1,137.23,0.09 +02/02/2021,1833.4,1863.6,1866.3,1830.4,236,-1.64 +02/01/2021,1863.9,1865,1876,1851.7,242.05,0.74 +01/29/2021,1850.3,1845.6,1878.9,1841.2,276.17,0.49 +01/28/2021,1841.2,1847.2,1867,1835.6,277.59,-0.20 +01/27/2021,1844.9,1849.7,1851.5,1828.4,195.54,-0.32 +01/26/2021,1850.9,1854.9,1860.8,1847.2,170.26,-0.23 +01/25/2021,1855.2,1855.3,1867.4,1846.2,211.98,-0.05 +01/22/2021,1856.2,1870.1,1870.8,1836.3,249.72,-0.52 +01/21/2021,1865.9,1871,1874.6,1857.5,196.94,-0.03 +01/20/2021,1866.5,1839.9,1872,1831.1,274.4,1.33 +01/19/2021,1842,1830.6,1846,1804.2,0.4,0.10 +01/18/2021,1840.2,1828.8,1845,1800.8,331.59,0.56 +01/15/2021,1829.9,1847.3,1856.6,1822.1,231.11,-1.16 +01/14/2021,1851.4,1845.6,1857.6,1826.6,257.66,-0.19 +01/13/2021,1854.9,1855,1863,1841.6,225.99,0.58 +01/12/2021,1844.2,1845.4,1864,1835.8,240.66,-0.36 +01/11/2021,1850.8,1849.4,1856,1817.1,268.36,0.84 +01/08/2021,1835.4,1915.2,1918.4,1827.8,443.51,-4.09 +01/07/2021,1913.6,1921.5,1929.6,1907.5,199.98,0.26 +01/06/2021,1908.6,1952.8,1962.5,1902.6,366.61,-2.34 +01/05/2021,1954.4,1946,1957,1938.4,201.95,0.40 +01/04/2021,1946.6,1908.2,1948.7,1906.1,273.37,2.72 +12/31/2020,1895.1,1899,1904.9,1889.1,130.63,0.09 +12/30/2020,1893.4,1881.8,1899,1879.5,133.66,0.56 +12/29/2020,1882.9,1878,1891.3,1875.6,149.27,0.13 +12/28/2020,1880.4,1887,1904.1,1873,196.76,-0.15 +12/24/2020,1883.2,1877.3,1887.4,1873.1,89.41,0.27 +12/23/2020,1878.1,1865.6,1883.7,1860.9,162.54,0.42 +12/22/2020,1870.3,1883,1889.4,1863.7,176.02,-0.66 +12/21/2020,1882.8,1892.9,1912,1859,232.05,-0.32 +12/18/2020,1888.9,1891.3,1895.7,1881.9,153.23,-0.08 +12/17/2020,1890.4,1868.4,1902,1865.9,219.87,1.68 +12/16/2020,1859.1,1857.7,1870,1848.2,199.68,0.20 +12/15/2020,1855.3,1830.5,1859.3,1828.5,173.61,1.27 +12/14/2020,1832.1,1845,1845.6,1820,168.49,-0.62 +12/11/2020,1843.6,1840,1851.8,1826.8,153.8,0.34 +12/10/2020,1837.4,1843,1854.2,1831.5,164.8,-0.06 +12/09/2020,1838.5,1875.4,1875.9,1828.2,219.59,-1.94 +12/08/2020,1874.9,1866.1,1879.8,1863.9,151.79,0.48 +12/07/2020,1866,1841.1,1873,1824.8,209.04,1.41 +12/04/2020,1840,1844.7,1852.7,1832,171.26,-0.06 +12/03/2020,1841.1,1833.9,1847.4,1826.7,180.36,0.60 +12/02/2020,1830.2,1819.1,1835.7,1810.5,185.32,0.62 +12/01/2020,1818.9,1780.3,1821.1,1778.4,203.65,2.13 +11/30/2020,1780.9,1790.8,1793.3,1767.2,242.73,-0.40 +11/27/2020,1788.1,1812.1,1822.6,1776.5,282.35,0.00 +11/26/2020,1788.1,1812.1,1822.6,1776.5,282.35,-0.96 +11/25/2020,1805.5,1805.2,1816.3,1798.6,205.75,0.05 +11/24/2020,1804.6,1835.7,1836.9,1797.1,367.88,-1.81 +11/23/2020,1837.8,1869.8,1875,1828,319.66,-1.85 +11/20/2020,1872.4,1864.8,1879.2,1859.1,186.17,0.59 +11/19/2020,1861.5,1872,1872.6,1850,222.35,-0.66 +11/18/2020,1873.9,1879.5,1884.2,1860.3,209,-0.59 +11/17/2020,1885.1,1888.2,1892.7,1876.3,160.88,-0.14 +11/16/2020,1887.8,1886.6,1898,1861.5,222.94,0.08 +11/13/2020,1886.2,1875.6,1895.8,1872.1,162.54,0.69 +11/12/2020,1873.3,1863.9,1883,1860.7,209.93,0.63 +11/11/2020,1861.6,1876.1,1882.5,1853.9,215.17,-0.79 +11/10/2020,1876.4,1864.1,1888.9,1858.9,264.87,1.19 +11/09/2020,1854.4,1956,1966.1,1848,496.09,-4.99 +11/06/2020,1951.7,1950,1961.8,1937.2,246.78,0.25 +11/05/2020,1946.8,1903.4,1954.3,1902.2,297.51,2.67 +11/04/2020,1896.2,1910.3,1917.9,1881.8,293.95,-0.74 +11/03/2020,1910.4,1896.4,1912.2,1887.6,171.37,0.95 +11/02/2020,1892.5,1877,1897.1,1873.3,164.94,0.67 +10/30/2020,1879.9,1867.9,1890.9,1863.3,213.17,0.64 +10/29/2020,1868,1877.5,1885.1,1859.2,225.16,-0.60 +10/28/2020,1879.2,1909.8,1912.6,1869.1,297.09,-1.71 +10/27/2020,1911.9,1904.4,1913.8,1898.7,153.3,0.33 +10/26/2020,1905.7,1906,1911.1,1892.5,166.31,0.03 +10/23/2020,1905.2,1906.5,1917.3,1895.2,172.96,0.03 +10/22/2020,1904.6,1927.4,1929.4,1894.2,215.58,-1.29 +10/21/2020,1929.5,1911.6,1936,1911.6,201.27,0.74 +10/20/2020,1915.4,1906.4,1917.6,1896.6,163.91,0.19 +10/19/2020,1911.7,1903.2,1923.4,1900.2,159.85,0.28 +10/16/2020,1906.4,1912.7,1918.7,1901.1,146.91,-0.13 +10/15/2020,1908.9,1906,1913.2,1892.7,213.57,0.08 +10/14/2020,1907.3,1895.4,1917.5,1885,188.3,0.67 +10/13/2020,1894.6,1927.3,1930.6,1889.3,267.54,-1.78 +10/12/2020,1928.9,1935,1939.4,1923.8,157.21,0.14 +10/09/2020,1926.2,1898.4,1936.8,1898,229.85,1.64 +10/08/2020,1895.1,1890.6,1905.3,1885.3,185.45,0.23 +10/07/2020,1890.8,1882.6,1902.4,1877.1,188.59,-0.94 +10/06/2020,1908.8,1917.8,1927,1878.2,219.44,-0.59 +10/05/2020,1920.1,1910.9,1924.9,1891.2,177.59,0.66 +10/02/2020,1907.6,1911,1923.6,1895.2,212.73,-0.45 +10/01/2020,1916.3,1891.2,1917.9,1890,262.09,1.10 +09/30/2020,1895.5,1903.2,1908.2,1885.8,259.87,-0.40 +09/29/2020,1903.2,1886.4,1904.8,1880.8,217.8,1.11 +09/28/2020,1882.3,1862.7,1888.2,1851.1,235.92,0.86 +09/25/2020,1866.3,1872.7,1879.3,1854.1,230.86,-0.56 +09/24/2020,1876.9,1866.9,1880.9,1851,345.04,0.45 +09/23/2020,1868.4,1905.1,1909.9,1856,411.56,-2.05 +09/22/2020,1907.6,1918.1,1925.5,1898.9,282.71,-0.16 +09/21/2020,1910.6,1957.3,1962.9,1885.4,386.67,-2.62 +09/18/2020,1962.1,1951.1,1968.2,1951.1,176.07,0.63 +09/17/2020,1949.9,1967.6,1969.3,1938.2,273.14,-1.05 +09/16/2020,1970.5,1961.4,1983.8,1957.2,298.39,0.22 +09/15/2020,1966.2,1966.2,1982.4,1955.6,239.54,0.13 +09/14/2020,1963.7,1948.9,1972.5,1945.2,200.09,0.81 +09/11/2020,1947.9,1953.8,1963.4,1944,205.23,-0.83 +09/10/2020,1964.3,1955.3,1975.2,1948.6,271.48,0.48 +09/09/2020,1954.9,1939.4,1959.7,1926.3,227.18,0.79 +09/08/2020,1939.5,1937.4,1937.4,1909,0.04,-0.19 +09/07/2020,1943.2,1938,1948.3,1911.7,416.01,0.46 +09/04/2020,1934.3,1938,1956.6,1921.6,304.74,-0.18 +09/03/2020,1937.8,1948.9,1956.6,1927.2,303.03,-0.35 +09/02/2020,1944.7,1976.8,1980.4,1938.9,332.59,-1.73 +09/01/2020,1978.9,1973.7,2001.2,1969.2,304.89,0.02 +08/31/2020,1978.6,1973.9,1985.8,1962.3,245.11,0.19 +08/28/2020,1974.9,1937.5,1983,1928.2,334.1,2.19 +08/27/2020,1932.6,1963,1987,1914.7,467.17,-1.02 +08/26/2020,1952.5,1939,1963.4,1908.4,342.21,1.53 +08/25/2020,1923.1,1935.9,1944.1,1919.1,274.11,-0.83 +08/24/2020,1939.2,1947.9,1970.3,1930.8,286.26,-0.40 +08/21/2020,1947,1955.6,1963.1,1916.6,355.07,0.03 +08/20/2020,1946.5,1934.4,1963.1,1928.9,383.34,-1.21 +08/19/2020,1970.3,2010.5,2015.6,1930.5,443.26,-2.13 +08/18/2020,2013.1,1993.6,2024.6,1985.2,361.48,0.72 +08/17/2020,1998.7,1956.4,2000.8,1939.1,289.44,2.51 +08/14/2020,1949.8,1963.8,1970,1939.1,241.8,-1.05 +08/13/2020,1970.4,1927.3,1974.8,1923,349.89,1.10 +08/12/2020,1949,1921.6,1961,1874.2,459.84,0.14 +08/11/2020,1946.3,2038.4,2040.5,1911.3,565,-4.58 +08/10/2020,2039.7,2044.8,2060.8,2027.8,251.31,0.58 +08/07/2020,2028,2076.4,2089.2,2024.8,398.13,-2.00 +08/06/2020,2069.4,2055,2081.8,2049,312.76,0.98 +08/05/2020,2049.3,2037,2070.3,2027.5,366.38,1.40 +08/04/2020,2021,1993.5,2037.7,1982.6,274.42,1.75 +08/03/2020,1986.3,1997.4,2009.5,1975.2,178.75,0.02 +07/31/2020,1985.9,1973.6,2005.4,1971.4,279.32,0.97 +07/30/2020,1966.8,1986.4,1987.3,1952.3,271.38,0.69 +07/29/2020,1953.4,1950.6,1974.9,1935.2,209.84,0.45 +07/28/2020,1944.6,1937.1,1974.7,1900.2,434.45,0.70 +07/27/2020,1931,1901.2,1941.9,1899,428.23,1.77 +07/24/2020,1897.5,1884.9,1904.6,1880.5,300.17,0.40 +07/23/2020,1890,1871.6,1897.7,1863.1,418.75,1.34 +07/22/2020,1865.1,1842.8,1871.8,1842.1,382.23,1.15 +07/21/2020,1843.9,1819.6,1844.9,1817.2,271.09,1.46 +07/20/2020,1817.4,1812.3,1823.4,1806.6,177.74,0.41 +07/17/2020,1810,1796.9,1813.9,1795.2,167.01,0.54 +07/16/2020,1800.3,1813.1,1816.2,1794.1,196.57,-0.74 +07/15/2020,1813.8,1811.1,1819.5,1804,183.06,0.02 +07/14/2020,1813.4,1805.2,1815,1791.1,253.21,-0.04 +07/13/2020,1814.1,1803.4,1818.8,1802.1,230.4,0.68 +07/10/2020,1801.9,1808.4,1817,1796.5,223.83,-0.11 +07/09/2020,1803.8,1818.8,1825.5,1799.6,283.37,-0.92 +07/08/2020,1820.6,1807.9,1829.8,1803.8,247.5,0.59 +07/07/2020,1809.9,1793.9,1810.8,1781.2,221.73,0.61 +07/06/2020,1799,1793.7,1801.6,1788.6,0.11,0.31 +07/03/2020,1793.5,1787.9,1799,1779.2,184.65,0.20 +07/02/2020,1790,1779,1791.7,1766.3,186.31,0.57 +07/01/2020,1779.9,1798.9,1807.7,1767.9,263.25,-1.14 +06/30/2020,1800.5,1784.2,1804,1774.8,199.42,1.08 +06/29/2020,1781.2,1789.2,1790.4,1776.5,130.51,0.05 +06/26/2020,1780.3,1774.8,1786.2,1754,201.23,0.55 +06/25/2020,1770.6,1772.3,1779.6,1764.1,152.2,-0.25 +06/24/2020,1775.1,1784.4,1796.1,1770.6,239.53,-0.39 +06/23/2020,1782,1764.9,1786.8,1758.3,194.68,0.88 +06/22/2020,1766.4,1765.8,1779,1753.5,228.68,0.76 +06/19/2020,1753,1729.8,1760.9,1728.3,181.15,1.27 +06/18/2020,1731.1,1735.5,1749.2,1722.7,155.91,-0.26 +06/17/2020,1735.6,1735.3,1739.3,1717.3,140.07,-0.05 +06/16/2020,1736.5,1732.3,1741.3,1721.8,182.42,0.54 +06/15/2020,1727.2,1740.7,1743.8,1706.2,200.23,-0.58 +06/12/2020,1737.3,1733.6,1753,1728.2,151.4,-0.14 +06/11/2020,1739.8,1746.6,1754.9,1727.5,205.35,1.11 +06/10/2020,1720.7,1718.9,1749.4,1714.1,198.76,-0.07 +06/09/2020,1721.9,1703.9,1729.4,1697.6,182.91,0.99 +06/08/2020,1705.1,1686.7,1707.6,1680.7,154.77,1.31 +06/05/2020,1683,1720.8,1723.2,1671.7,273.68,-2.57 +06/04/2020,1727.4,1702.8,1729,1698.9,198.72,1.33 +06/03/2020,1704.8,1733.7,1738.9,1690.3,256.52,-1.68 +06/02/2020,1734,1750.3,1757,1728,175.35,-0.93 +06/01/2020,1750.3,1749.8,1761,1737.6,146.13,-0.08 +05/29/2020,1751.7,1732.7,1754.5,1725.3,150.11,1.35 +05/28/2020,1728.3,1725,1743.7,1720,164.82,1.03 +05/27/2020,1710.7,1703.1,1713.2,1684.2,137.42,-0.38 +05/26/2020,1717.3,1739.8,1745.6,1711.3,3.44,0.69 +05/25/2020,1705.6,1734.8,1737.2,1700,313.17,-1.72 +05/22/2020,1735.5,1726,1742,1722.5,196.82,0.79 +05/21/2020,1721.9,1751.7,1751.7,1715.3,238.74,-1.72 +05/20/2020,1752.1,1749.2,1757.6,1744,184.46,0.37 +05/19/2020,1745.6,1734.8,1751.6,1727.2,185.26,0.65 +05/18/2020,1734.4,1757.5,1775.8,1729.3,271.47,-1.25 +05/15/2020,1756.3,1738.5,1761.2,1736.8,200.18,0.88 +05/14/2020,1740.9,1723.1,1746.5,1716,212.91,1.43 +05/13/2020,1716.4,1705,1726.5,1701.6,211.61,0.56 +05/12/2020,1706.8,1700,1716.7,1693.5,198.07,0.52 +05/11/2020,1698,1706,1713.8,1692.1,202.17,-0.93 +05/08/2020,1713.9,1727.2,1735.5,1703.1,232.81,-0.69 +05/07/2020,1725.8,1686,1733.2,1683.9,250.7,2.21 +05/06/2020,1688.5,1714.1,1716.6,1683,203.37,-1.29 +05/05/2020,1710.6,1711,1717.8,1695.4,184.73,-0.16 +05/04/2020,1713.3,1711.2,1726,1700.3,148.73,0.73 +05/01/2020,1700.9,1693.5,1714.4,1676,168.02,0.40 +04/30/2020,1694.2,1729.6,1737,1687.5,234.53,-1.12 +04/29/2020,1713.4,1724.8,1733.5,1708.2,159.6,-0.51 +04/28/2020,1722.2,1724.4,1731.9,1704.1,171.34,-0.09 +04/27/2020,1723.8,1745,1745.8,1720,146.64,-0.68 +04/24/2020,1735.6,1753,1760.2,1725.4,180.24,-0.56 +04/23/2020,1745.4,1736.5,1764.2,1730.6,201.88,0.41 +04/22/2020,1738.3,1703.1,1742.4,1695.4,193.73,2.99 +04/21/2020,1687.8,1713.3,1718,1666.2,248.63,-1.37 +04/20/2020,1711.2,1693,1718.4,1685,186.91,0.73 +04/17/2020,1698.8,1738.5,1738.8,1691.2,227.07,-1.90 +04/16/2020,1731.7,1743.5,1768,1722.6,204.23,-0.49 +04/15/2020,1740.2,1758.1,1759.8,1731.6,186.7,-1.62 +04/14/2020,1768.9,1761.5,1788.8,1747.1,241.19,0.43 +04/13/2020,1761.4,1742.3,1772.8,1724.2,166.89,0.49 +04/09/2020,1752.8,1680.5,1754.5,1676.5,218.8,4.07 +04/08/2020,1684.3,1678.7,1695.8,1670.7,125.33,0.04 +04/07/2020,1683.7,1707.1,1742.6,1672,204.5,-0.60 +04/06/2020,1693.9,1647.7,1715.8,1638.2,192.75,2.93 +04/03/2020,1645.7,1635.3,1652.8,1624.4,139.61,0.49 +04/02/2020,1637.7,1602.4,1645.6,1595.2,167.71,2.91 +04/01/2020,1591.4,1589.4,1612.4,1576,164.48,-0.33 +03/31/2020,1596.6,1643.4,1645.6,1588.2,176.55,-2.84 +03/30/2020,1643.2,1663.4,1673.6,1632,157.37,-0.66 +03/27/2020,1654.1,1653.4,1661,1630.7,159.26,0.18 +03/26/2020,1651.2,1642.5,1672.5,1611,215.97,1.09 +03/25/2020,1633.4,1666.2,1699.3,1615.2,254.19,-1.65 +03/24/2020,1660.8,1563.8,1698,1560.5,418.78,5.95 +03/23/2020,1567.6,1505,1569.3,1484.6,362.07,5.59 +03/20/2020,1484.6,1471.6,1519.4,1457.5,269.97,0.36 +03/19/2020,1479.3,1487.2,1502.8,1460.1,325.29,0.09 +03/18/2020,1477.9,1527.6,1547,1473.3,435.19,-3.14 +03/17/2020,1525.8,1512.8,1554.3,1465.6,434.51,2.64 +03/16/2020,1486.5,1563.8,1574.8,1450.9,565.98,-1.99 +03/13/2020,1516.7,1582.7,1597.9,1504,551.05,-4.63 +03/12/2020,1590.3,1633.1,1651,1560.4,605.72,-3.17 +03/11/2020,1642.3,1649.3,1671.8,1632.4,404.35,-1.08 +03/10/2020,1660.3,1679.6,1681.3,1641.1,385.48,-0.92 +03/09/2020,1675.7,1692.6,1704.3,1658,504.16,0.20 +03/06/2020,1672.4,1673.1,1692.8,1642.4,659.63,0.26 +03/05/2020,1668,1638.2,1675.5,1635.6,363,1.52 +03/04/2020,1643,1640.1,1654.3,1632.6,313.34,-0.09 +03/03/2020,1644.4,1586,1650.5,1585.9,466.53,3.11 +03/02/2020,1594.8,1592.8,1612.1,1576.3,443.53,1.79 +02/28/2020,1566.7,1646.1,1651,1564,745.84,-4.61 +02/27/2020,1642.5,1643,1662.5,1636.7,573.29,-0.04 +02/26/2020,1643.1,1637.3,1657.1,1626.6,531.9,-0.42 +02/25/2020,1650,1661.8,1666.7,1627,672.76,-1.59 +02/24/2020,1676.6,1656,1691.7,1652.8,680.82,1.69 +02/21/2020,1648.8,1623.6,1652.1,1621.6,489.19,1.75 +02/20/2020,1620.5,1615,1626.5,1606.6,403.04,0.54 +02/19/2020,1611.8,1604.8,1615.9,1602.4,307.89,0.51 +02/18/2020,1603.6,1585.1,1608.2,1581.8,414.24,0.00 +02/17/2020,1603.6,1585.1,1608.2,1581.8,414.24,1.08 +02/14/2020,1586.4,1579,1588.2,1576,227.11,0.48 +02/13/2020,1578.8,1569.8,1581.7,1568.5,276.25,0.46 +02/12/2020,1571.6,1571.2,1573.6,1564.4,189.55,0.10 +02/11/2020,1570.1,1575.5,1577.5,1565.2,231.83,-0.60 +02/10/2020,1579.5,1575.8,1580.5,1571.5,191.75,0.39 +02/07/2020,1573.4,1570.7,1577.8,1563.5,286.42,0.22 +02/06/2020,1570,1560,1571.9,1556,229,0.46 +02/05/2020,1562.8,1556.1,1566.2,1551.1,306.05,0.47 +02/04/2020,1555.5,1581.5,1584.5,1552.8,349,-1.70 +02/03/2020,1582.4,1597.8,1598.5,1573.2,320.6,-0.35 +01/31/2020,1587.9,1578.4,1595.5,1575,343.37,-0.08 +01/30/2020,1589.2,1582.4,1590.7,1576.8,382.6,1.20 +01/29/2020,1570.4,1566.3,1577.7,1562,251.27,0.04 +01/28/2020,1569.8,1580.6,1582.2,1564.6,378.01,-0.48 +01/27/2020,1577.4,1580.5,1588.4,1575.3,398.06,0.35 +01/24/2020,1571.9,1562.9,1575.5,1555.8,427.14,0.42 +01/23/2020,1565.4,1558.9,1567.5,1551.3,361.03,0.56 +01/22/2020,1556.7,1558.9,1559.8,1550,286.08,-0.26 +01/21/2020,1560.8,1567,1571.4,1549.2,2.22,0.19 +01/20/2020,1557.9,1557.3,1568.8,1546,462.62,-0.15 +01/17/2020,1560.3,1553,1561.4,1549.3,264.93,0.63 +01/16/2020,1550.5,1556.6,1558.2,1548,260.05,-0.23 +01/15/2020,1554,1546.8,1558.8,1546.5,310.07,0.61 +01/14/2020,1544.6,1548.6,1549.5,1536.4,340.91,-0.39 +01/13/2020,1550.6,1563,1563.1,1547,311.73,-0.61 +01/10/2020,1560.1,1553.4,1564.1,1546.7,344.34,0.37 +01/09/2020,1554.3,1557.7,1562.4,1541,372.88,-0.38 +01/08/2020,1560.2,1578.8,1613.3,1553.4,813.41,-0.90 +01/07/2020,1574.3,1567.4,1579.2,1557,435.87,0.35 +01/06/2020,1568.8,1562.7,1590.9,1562.3,558.97,1.06 +01/03/2020,1552.4,1531.7,1556.6,1530.4,436.74,1.59 +01/02/2020,1528.1,1521,1534,1519.7,270.55,0.33 +12/31/2019,1523.1,1517.7,1529,1517.5,220.85,0.30 +12/30/2019,1518.6,1515.9,1519.1,1513.5,178.72,0.03 +12/27/2019,1518.1,1516.5,1519.9,1512.1,204.99,0.24 +12/26/2019,1514.4,1503.9,1517.4,1502.1,216.61,0.64 +12/24/2019,1504.8,1489.8,1505,1488.1,183.68,1.08 +12/23/2019,1488.7,1482.4,1490.1,1481.2,162.45,0.53 +12/20/2019,1480.9,1482.7,1484.8,1479.5,140.77,-0.24 +12/19/2019,1484.4,1479.4,1485.8,1477.1,201.19,0.39 +12/18/2019,1478.7,1480.4,1483.6,1474.3,197.97,-0.13 +12/17/2019,1480.6,1480.6,1484.9,1478.4,173.25,0.01 +12/16/2019,1480.5,1480,1484.5,1477.4,165.85,-0.05 +12/13/2019,1481.2,1470.8,1482.5,1465.5,356.68,0.60 +12/12/2019,1472.3,1479.2,1491.6,1468.2,409.86,-0.18 +12/11/2019,1475,1468.5,1483.5,1466.9,251.73,0.47 +12/10/2019,1468.1,1466.3,1473.7,1464.2,228.83,0.22 +12/09/2019,1464.9,1464.1,1469.8,1463,177.22,-0.01 +12/06/2019,1465.1,1481,1485.3,1463.3,317.32,-1.21 +12/05/2019,1483.1,1480,1485.7,1478,240.01,0.20 +12/04/2019,1480.2,1483.2,1489.9,1476.7,319.73,-0.28 +12/03/2019,1484.4,1468,1487.7,1465.4,400.9,1.03 +12/02/2019,1469.2,1470.3,1471.7,1459.8,316.58,-0.24 +11/29/2019,1472.7,1461.2,1472.9,1459.1,272.34,0.00 +11/28/2019,1472.7,1461.2,1472.9,1459.1,272.34,1.33 +11/27/2019,1453.4,1461.1,1461.9,1452,88.36,-0.47 +11/26/2019,1460.3,1455.1,1462.9,1449.6,346.36,0.23 +11/25/2019,1456.9,1461,1462,1453.9,298.71,-0.46 +11/22/2019,1463.6,1464.3,1473.4,1461.2,320.5,0.00 +11/21/2019,1463.6,1475.1,1475.9,1462.4,388.34,-0.72 +11/20/2019,1474.2,1472.7,1479.2,1466.1,369.97,-0.01 +11/19/2019,1474.3,1471.9,1475.8,1465.1,307.86,0.16 +11/18/2019,1471.9,1467.8,1474.4,1456.6,331.24,0.23 +11/15/2019,1468.5,1471.9,1472.1,1462.8,251.21,-0.33 +11/14/2019,1473.4,1464,1475.5,1461.7,317.4,0.69 +11/13/2019,1463.3,1456.5,1467.9,1456.4,352.33,0.66 +11/12/2019,1453.7,1455.9,1461.3,1446.2,429.61,-0.23 +11/11/2019,1457.1,1460,1467.4,1448.9,310.16,-0.40 +11/08/2019,1462.9,1469,1473.9,1457,447.07,-0.24 +11/07/2019,1466.4,1492.1,1493.6,1461.4,674.98,-1.79 +11/06/2019,1493.1,1484.3,1495.9,1483.8,313.72,0.63 +11/05/2019,1483.7,1511.6,1511.9,1480.7,593.62,-1.81 +11/04/2019,1511.1,1516.4,1517.1,1506.5,260.2,-0.02 +11/01/2019,1511.4,1515.1,1519,1505.4,380.99,-0.22 +10/31/2019,1514.8,1498.8,1516.7,1496,390.01,1.21 +10/30/2019,1496.7,1490.5,1499.3,1483.1,353.64,0.40 +10/29/2019,1490.7,1494.3,1497.1,1485.6,291.98,-0.34 +10/28/2019,1495.8,1507.4,1510.8,1492.3,318.13,-0.63 +10/25/2019,1505.3,1506.4,1520.9,1503.1,368.74,0.04 +10/24/2019,1504.7,1495.1,1506.9,1490.4,305.01,0.60 +10/23/2019,1495.7,1491.1,1499.4,1490.7,244.62,0.55 +10/22/2019,1487.5,1487.5,1492.1,1484,208.97,-0.04 +10/21/2019,1488.1,1495.6,1498.7,1484.8,284.29,-0.40 +10/18/2019,1494.1,1495.6,1497.9,1488.3,232.55,-0.28 +10/17/2019,1498.3,1494.2,1501.1,1487,305.67,0.29 +10/16/2019,1494,1484.8,1495.5,1480.6,367.9,0.71 +10/15/2019,1483.5,1497.7,1503,1480.8,317.99,-0.94 +10/14/2019,1497.6,1492,1501.5,1487.1,228.32,0.60 +10/11/2019,1488.7,1498.3,1508,1478,485.96,-0.81 +10/10/2019,1500.9,1510.8,1522.3,1495.7,417.88,-0.79 +10/09/2019,1512.8,1510.9,1518,1505.1,285.28,0.59 +10/08/2019,1503.9,1498.7,1515.3,1492.1,371.44,-0.03 +10/07/2019,1504.4,1518.6,1518.8,1493.3,257.78,-0.56 +10/04/2019,1512.9,1511.6,1522.2,1501.4,344.79,-0.06 +10/03/2019,1513.8,1505.6,1525.8,1501.7,408.74,0.39 +10/02/2019,1507.9,1485.4,1511.4,1480.5,393.1,1.27 +10/01/2019,1489,1478,1493.5,1465,450.17,1.09 +09/30/2019,1472.9,1501.7,1507.2,1470.5,439.71,-2.22 +09/27/2019,1506.4,1511.8,1514.4,1493.3,451.93,-0.58 +09/26/2019,1515.2,1510.9,1519.5,1507.1,378.29,0.19 +09/25/2019,1512.3,1539.8,1542.8,1507.4,481.46,-1.81 +09/24/2019,1540.2,1529.8,1543.3,1522.8,424.86,0.57 +09/23/2019,1531.5,1521.5,1534.4,1517.9,359.88,1.08 +09/20/2019,1515.1,1506.8,1524.5,1505.3,284.39,0.59 +09/19/2019,1506.2,1502,1512.1,1496.3,291.3,-0.63 +09/18/2019,1515.8,1509.7,1519.5,1490.7,364.96,0.16 +09/17/2019,1513.4,1506.5,1515,1500.9,336.63,0.13 +09/16/2019,1511.5,1513.1,1519.7,1503.4,349.61,0.80 +09/13/2019,1499.5,1506.5,1516.6,1493.1,364.42,-0.52 +09/12/2019,1507.4,1504.9,1532.2,1496.8,491.47,0.28 +09/11/2019,1503.2,1493.9,1506.2,1492.9,308.79,0.27 +09/10/2019,1499.2,1507,1509.1,1492.1,397.92,-0.79 +09/09/2019,1511.1,1516.4,1523.8,1505.5,317.52,-0.29 +09/06/2019,1515.5,1525.6,1536.2,1510.7,544.87,-0.66 +09/05/2019,1525.5,1561.4,1561.9,1514.3,606.4,-2.24 +09/04/2019,1560.4,1556,1566.2,1542.6,412.35,0.49 +09/03/2019,1552.8,1531.9,1532.9,1525.3,0,-0.20 +09/02/2019,1555.9,1535.2,1558.9,1528,554.83,1.73 +08/30/2019,1529.4,1536.9,1541.9,1525.6,330.85,-0.49 +08/29/2019,1536.9,1549.4,1559.8,1528.6,455.6,-0.79 +08/28/2019,1549.1,1551.8,1556.6,1541.4,353.91,-0.17 +08/27/2019,1551.8,1537.3,1554.5,1535.3,347.05,0.95 +08/26/2019,1537.2,1545.4,1565,1534.8,411.67,-0.03 +08/23/2019,1537.6,1508.8,1540.3,1503,473,1.93 +08/22/2019,1508.5,1512.4,1514.6,1502.1,279.41,-0.48 +08/21/2019,1515.7,1518.4,1518.4,1506.5,245.9,0.00 +08/20/2019,1515.7,1506.3,1518.8,1503,247.54,0.27 +08/19/2019,1511.6,1523,1523.6,1503.3,295.83,-0.79 +08/16/2019,1523.6,1533.9,1538.6,1513.9,322.46,-0.50 +08/15/2019,1531.2,1526.6,1537.7,1518.3,436.12,0.22 +08/14/2019,1527.8,1513,1534.9,1504.5,484.19,0.90 +08/13/2019,1514.1,1522.3,1546.1,1488.9,616.74,-0.20 +08/12/2019,1517.2,1509.2,1531.5,1498.6,355.1,0.58 +08/09/2019,1508.5,1515.9,1521.1,1506.2,332.61,-0.07 +08/08/2019,1509.5,1512.1,1521.3,1501.6,402.96,-0.66 +08/07/2019,1519.6,1486.7,1522.7,1484.3,651.55,2.39 +08/06/2019,1484.2,1481.1,1486.8,1468.2,381.92,0.52 +08/05/2019,1476.5,1451.2,1481.8,1448.8,534.19,1.30 +08/02/2019,1457.5,1457.5,1461.9,1442.5,493.05,1.75 +08/01/2019,1432.4,1425.6,1458.2,1412.1,587.56,-0.38 +07/31/2019,1437.8,1443.7,1447.8,1422.3,419.58,-0.28 +07/30/2019,1441.8,1439.5,1445.7,1434.8,259.62,1.51 +07/29/2019,1420.4,1419,1428,1414.4,224.27,0.08 +07/26/2019,1419.3,1414.9,1424.8,1412.9,306.02,0.33 +07/25/2019,1414.7,1426.8,1434.1,1411.1,489.39,-0.63 +07/24/2019,1423.6,1418.6,1430,1416.7,318.16,0.13 +07/23/2019,1421.7,1426,1431.4,1414.6,386.68,-0.36 +07/22/2019,1426.9,1428.5,1430.8,1423,255.35,0.01 +07/19/2019,1426.7,1448.3,1454.4,1421.1,530.02,-0.10 +07/18/2019,1428.1,1428.5,1449.7,1415.6,481.33,0.34 +07/17/2019,1423.3,1407.9,1428.4,1401.3,358.17,0.86 +07/16/2019,1411.2,1416.4,1420,1402.1,334.82,-0.16 +07/15/2019,1413.5,1417.7,1421.6,1409.3,243.38,0.09 +07/12/2019,1412.2,1406.2,1418.9,1404.5,284.97,0.39 +07/11/2019,1406.7,1421.1,1429.4,1402.7,400.09,-0.41 +07/10/2019,1412.5,1400,1421.1,1391.8,443.5,0.86 +07/09/2019,1400.5,1397.9,1402.4,1387.5,287.18,0.04 +07/08/2019,1400,1401,1409.9,1393.8,318.69,-0.24 +07/05/2019,1403.4,1426.5,1427.9,1393,0.34,0.24 +07/04/2019,1400.1,1421.6,1426.8,1388.6,577.38,-1.46 +07/03/2019,1420.9,1424.7,1441,1414.7,419.61,0.92 +07/02/2019,1408,1386.2,1424,1386.2,383.25,1.35 +07/01/2019,1389.3,1401.8,1401.9,1384.7,389.76,-1.73 +06/28/2019,1413.7,1413.3,1427.8,1408.6,306.62,0.12 +06/27/2019,1412,1412.7,1415.3,1401.4,336.36,-0.24 +06/26/2019,1415.4,1427.2,1427.9,1405,421.95,-0.23 +06/25/2019,1418.7,1423.4,1442.9,1415.1,643.59,0.04 +06/24/2019,1418.2,1403.9,1425.1,1403.6,375.15,1.29 +06/21/2019,1400.1,1391.2,1415.4,1386.1,518.89,0.23 +06/20/2019,1396.9,1364.5,1397.7,1361.3,542.9,3.57 +06/19/2019,1348.8,1350.4,1366.6,1344.8,332.61,-0.14 +06/18/2019,1350.7,1343.9,1358.5,1342.1,376.27,0.58 +06/17/2019,1342.9,1345.5,1347.1,1336.6,238.71,-0.12 +06/14/2019,1344.5,1346.5,1362.2,1341.4,358.45,0.06 +06/13/2019,1343.7,1337.8,1347,1335.9,204.83,0.52 +06/12/2019,1336.8,1330.6,1342.3,1329.8,234.46,0.42 +06/11/2019,1331.2,1331.8,1333.8,1323.6,215.15,0.14 +06/10/2019,1329.3,1341.2,1341.7,1329,228.03,-1.25 +06/07/2019,1346.1,1339.7,1352.7,1334.3,331.29,0.25 +06/06/2019,1342.7,1336.1,1344.2,1331.3,263.09,0.68 +06/05/2019,1333.6,1330.2,1348.9,1329.3,413.47,0.37 +06/04/2019,1328.7,1329.7,1334.1,1324.7,319.96,0.06 +06/03/2019,1327.9,1312.5,1333,1310.9,363.4,1.28 +05/31/2019,1311.1,1293.2,1311.9,1292.5,341.18,1.45 +05/30/2019,1292.4,1285.1,1293.9,1279.2,284.02,0.89 +05/29/2019,1281,1278.9,1285.2,1278.4,189.69,0.07 +05/28/2019,1280.1,1287.2,1289.6,1278.5,0.78,0.23 +05/27/2019,1277.1,1283.5,1286.9,1275.1,362.16,-0.51 +05/24/2019,1283.6,1283.2,1284.7,1280.1,218.71,-0.14 +05/23/2019,1285.4,1273.6,1287.1,1272.1,330.16,0.88 +05/22/2019,1274.2,1274.4,1277.1,1272,191.37,0.08 +05/21/2019,1273.2,1277.7,1277.7,1269,213.17,-0.32 +05/20/2019,1277.3,1277.6,1278.8,1273.3,212.18,0.13 +05/17/2019,1275.7,1287.2,1289,1274.6,264.57,-0.82 +05/16/2019,1286.2,1296.9,1299.3,1284.2,282.07,-0.89 +05/15/2019,1297.8,1298.3,1301.7,1293.6,247.52,0.12 +05/14/2019,1296.3,1302,1302.6,1294.3,222.05,-0.42 +05/13/2019,1301.8,1288.4,1302.2,1282.4,379.44,1.12 +05/10/2019,1287.4,1285.1,1290.3,1284,238.64,0.17 +05/09/2019,1285.2,1282.9,1289.2,1280.4,306.55,0.30 +05/08/2019,1281.4,1287.4,1292.8,1280.2,302.69,-0.33 +05/07/2019,1285.6,1284.1,1287.3,1279.1,251.09,0.14 +05/06/2019,1283.8,1286.4,1286.4,1278.1,244.34,0.20 +05/03/2019,1281.3,1272.9,1283.9,1269,280.32,0.73 +05/02/2019,1272,1278.2,1278.4,1267.3,282.5,-0.95 +05/01/2019,1284.2,1284.2,1289.4,1274.5,275.43,-0.12 +04/30/2019,1285.7,1283.5,1288.2,1281.6,239.44,0.33 +04/29/2019,1281.5,1287,1288.6,1279.9,208.96,-0.57 +04/26/2019,1288.8,1280.1,1290.9,1276,278.89,0.71 +04/25/2019,1279.7,1276.3,1284.8,1275.4,237.15,0.02 +04/24/2019,1279.4,1272.3,1280.7,1270.5,246.05,0.49 +04/23/2019,1273.2,1277.2,1278.5,1267.9,280.34,-0.34 +04/22/2019,1277.6,1277.9,1281.9,1275.7,136.44,0.13 +04/18/2019,1276,1276.3,1279.7,1273,229.63,-0.06 +04/17/2019,1276.8,1278.7,1282.1,1275.2,223.36,-0.03 +04/16/2019,1277.2,1290,1290.3,1275.5,326.51,-1.09 +04/15/2019,1291.3,1293.2,1293.5,1285.3,232.99,-0.30 +04/12/2019,1295.2,1296.8,1299.1,1293.2,192.49,0.15 +04/11/2019,1293.3,1311.4,1312.1,1292.9,324.74,-1.57 +04/10/2019,1313.9,1307.6,1314.7,1304.7,218.88,0.43 +04/09/2019,1308.3,1303.2,1310.4,1301.1,200.34,0.49 +04/08/2019,1301.9,1297.6,1307.9,1297,207.57,0.49 +04/05/2019,1295.6,1295.8,1297.4,1288.3,231.45,0.10 +04/04/2019,1294.3,1296.3,1298.7,1284.9,262.54,-0.08 +04/03/2019,1295.3,1295.6,1299,1292.7,190.37,-0.01 +04/02/2019,1295.4,1292.7,1297.1,1289.5,196.4,0.09 +04/01/2019,1294.2,1295.9,1301.7,1291,236.66,-0.33 +03/29/2019,1298.5,1296.3,1304.6,1291.3,270.18,0.25 +03/28/2019,1295.3,1315.9,1317.6,1293.3,426.82,-1.15 +03/27/2019,1310.4,1316.7,1318.8,1307.3,206.26,-0.35 +03/26/2019,1315,1320.5,1321.9,1312.1,267.17,-0.57 +03/25/2019,1322.6,1313.2,1324.5,1312.6,251.98,0.78 +03/22/2019,1312.3,1308.2,1314.7,1307,271.38,0.38 +03/21/2019,1307.3,1316.1,1320.2,1302.8,332.61,0.43 +03/20/2019,1301.7,1304.3,1317.2,1298.1,370.4,-0.37 +03/19/2019,1306.5,1304.8,1310.8,1303.4,206.9,0.38 +03/18/2019,1301.5,1299.3,1306.7,1298,176.49,-0.11 +03/15/2019,1302.9,1295.4,1306.3,1293.7,234.65,0.60 +03/14/2019,1295.1,1308.1,1308.6,1292.5,248.21,-1.08 +03/13/2019,1309.3,1303.7,1311.6,1303.4,214.24,0.86 +03/12/2019,1298.1,1293.1,1302.6,1292.9,203.89,0.54 +03/11/2019,1291.1,1298.5,1299.2,1290.6,196.86,-0.63 +03/08/2019,1299.3,1286.8,1301.3,1286.5,283.84,1.03 +03/07/2019,1286.1,1288.6,1289.6,1280.8,257.92,-0.12 +03/06/2019,1287.6,1288.5,1291.8,1284.3,192.93,0.23 +03/05/2019,1284.7,1288.5,1290.6,1282,216.93,-0.22 +03/04/2019,1287.5,1297.4,1298.1,1283.8,268.39,-0.90 +03/01/2019,1299.2,1315.9,1315.9,1291.3,343.47,-1.28 +02/28/2019,1316.1,1319.6,1328.9,1314,252.24,-0.39 +02/27/2019,1321.2,1331,1331.1,1318.4,198.04,-0.55 +02/26/2019,1328.5,1329.9,1332.4,1325.5,185.56,-0.08 +02/25/2019,1329.5,1332.7,1334.9,1327.3,181.78,-0.25 +02/22/2019,1332.8,1327.2,1335.6,1323.8,241.8,0.38 +02/21/2019,1327.8,1340.5,1343.7,1323.3,285.81,-1.49 +02/20/2019,1347.9,1347.8,1349.8,1339.8,246.72,0.23 +02/19/2019,1344.8,1325,1345,1323.8,348.64,0.00 +02/18/2019,1344.8,1327.9,1345,1324.4,348.64,1.72 +02/15/2019,1322.1,1314.7,1325.8,1314.3,200.28,0.62 +02/14/2019,1313.9,1311.8,1317.4,1304.7,228.46,-0.09 +02/13/2019,1315.1,1315.2,1321.7,1308.1,213.96,0.08 +02/12/2019,1314,1311.4,1318.3,1310.7,146.45,0.16 +02/11/2019,1311.9,1318.1,1318.7,1307.1,150.61,-0.50 +02/08/2019,1318.5,1313.2,1319.5,1311.5,150.61,0.33 +02/07/2019,1314.2,1308.1,1315.8,1306.4,166.76,-0.02 +02/06/2019,1314.4,1317.6,1319.7,1309.6,137.25,-0.36 +02/05/2019,1319.2,1317.1,1321,1314.8,129.01,-0.01 +02/04/2019,1319.3,1319.6,1320.1,1312.7,159.56,-0.21 +02/01/2019,1322.1,1323,1328.2,1320.6,200,-0.23 +01/31/2019,1325.2,1323,1331.1,1322.6,224.75,0.74 +01/30/2019,1315.5,1318.4,1328.6,1313.5,272.11,0.50 +01/29/2019,1308.9,1302.2,1310.8,1302,213.61,0.45 +01/28/2019,1303.1,1301,1303.7,1296.5,243.07,0.39 +01/25/2019,1298.1,1279.2,1303.4,1278.9,303.84,1.43 +01/24/2019,1279.8,1283.6,1283.6,1275.3,225.77,-0.33 +01/23/2019,1284,1284.4,1286,1277.7,217.13,-0.14 +01/22/2019,1285.8,1284.5,1287.2,1279,1.27,0.19 +01/21/2019,1283.4,1282.4,1285,1276,318.85,0.06 +01/18/2019,1282.6,1290.4,1292,1280.1,225.57,-0.75 +01/17/2019,1292.3,1294.6,1295,1288.3,191.98,-0.12 +01/16/2019,1293.8,1289.1,1295.4,1287.6,181.39,0.42 +01/15/2019,1288.4,1293.1,1294.8,1286.5,242.07,-0.22 +01/14/2019,1291.3,1292.7,1296.6,1288.6,221.89,0.14 +01/11/2019,1289.5,1290.2,1295.7,1287.2,210.64,0.16 +01/10/2019,1287.4,1293.6,1298,1286.7,239.92,-0.36 +01/09/2019,1292,1287,1295,1280.9,245.97,0.47 +01/08/2019,1285.9,1287.4,1288.4,1280.2,221.92,-0.31 +01/07/2019,1289.9,1290.2,1297,1287.3,204.68,0.32 +01/04/2019,1285.8,1298.9,1300,1278.1,316.06,-0.70 +01/03/2019,1294.8,1290.4,1296.9,1286.4,244.54,0.83 +01/02/2019,1284.1,1285,1291,1280.6,235.33,0.22 diff --git a/The Effect of Economic News on Gold Prices Analysis/Dataset/sentiment_labeled_data.csv b/The Effect of Economic News on Gold Prices Analysis/Dataset/sentiment_labeled_data.csv new file mode 100644 index 000000000..e680182aa --- /dev/null +++ b/The Effect of Economic News on Gold Prices Analysis/Dataset/sentiment_labeled_data.csv @@ -0,0 +1,1280 @@ +Date,Price,Vol_K,Change_percent,Country,Event,D_Consensus,D_Forecast,Sentiment +2023-12-01,2089.7,241.62,1.58,US,ISM Manufacturing PMI ,1.8887722980062926,1.053740779768177,Positive +2023-11-30,2057.2,151.92,-0.48,US,Core PCE Price Index MoM ,0.0,0.19900497512437815,Negative +2023-11-29,2067.1,197.79,0.81,US,GDP Growth Rate QoQ 2nd Est,0.3629764065335743,0.5449591280653943,Positive +2023-11-28,2050.5,1.86,1.35,,,1.097918675666989,1.4835862307477667,Neutral +2023-11-27,2023.1,1.06,0.47,,,1.097918675666989,1.4835862307477667,Neutral +2023-11-24,2013.7,0.52,0.95,,,1.097918675666989,1.4835862307477667,Neutral +2023-11-23,1994.75,200.515,-0.43,JP,Inflation Rate YoY ,1.097918675666989,0.1877934272300471,Negative +2023-11-22,2003.4,0.67,-0.43,US,Durable Goods Orders MoM ,5.027322404371584,5.664488017429194,Negative +2023-11-21,2012.0,0.67,1.07,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Positive +2023-11-20,1990.7,0.31,0.3,,,1.097918675666989,1.4835862307477667,Neutral +2023-11-17,1984.7,133.12,-0.13,US,Building Permits Prel ,1.8796037592075254,1.8796037592075254,Negative +2023-11-16,1987.3,186.81,1.17,,,1.097918675666989,1.4835862307477667,Neutral +2023-11-15,1964.3,142.92,-0.11,US,PPI MoM ,1.2048192771084338,1.2048192771084338,Negative +2023-11-14,1966.5,180.74,0.84,US,Core Inflation Rate MoM ,0.19900497512437815,0.19900497512437815,Positive +2023-11-13,1950.2,183.7,0.65,,,1.097918675666989,1.4835862307477667,Neutral +2023-11-10,1937.7,229.64,-1.63,US,Michigan Consumer Sentiment Prel ,5.275779376498808,6.050955414012746,Negative +2023-11-09,1969.8,214.08,0.61,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Positive +2023-11-08,1957.8,189.36,-0.8,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Negative +2023-11-07,1973.5,218.95,-0.76,,,1.097918675666989,1.4835862307477667,Neutral +2023-11-06,1988.6,146.28,-0.53,CA,Ivey PMI s.a ,1.1070110701107037,2.441314553990605,Negative +2023-11-03,1999.2,222.19,0.29,US,Non Farm Payrolls ,18.12688821752266,23.46041055718475,Positive +2023-11-02,1993.5,158.65,0.3,GB,BoE Interest Rate Decision,0.0,0.0,Positive +2023-11-01,1987.5,197.63,-0.34,US,ISM Manufacturing PMI ,4.7569803516028895,5.761316872427978,Negative +2023-10-31,1994.3,214.78,-0.56,EA,GDP Growth Rate QoQ Flash,0.20020020020020018,0.20020020020020018,Negative +2023-10-30,2005.6,181.34,0.83,JP,BoJ Interest Rate Decision,0.0,0.0,Positive +2023-10-27,1989.0,0.37,0.06,US,Core PCE Price Index MoM ,0.0,0.19900497512437815,Positive +2023-10-26,1987.9,0.2,0.12,US,Durable Goods Orders MoM ,5.639097744360902,6.8052930056710785,Positive +2023-10-25,1985.5,0.16,0.44,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Positive +2023-10-24,1976.8,1.23,-0.07,GB,Unemployment Rate - Adjusted ,1.097918675666989,1.4835862307477667,Negative +2023-10-23,1978.2,0.45,-0.81,,,1.097918675666989,1.4835862307477667,Neutral +2023-10-20,1994.4,200.515,0.7,GB,Retail Sales MoM ,1.415571284125379,1.415571284125379,Positive +2023-10-19,1980.5,264.82,0.62,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Positive +2023-10-18,1968.3,270.05,1.68,US,Building Permits Prel ,1.172572011215913,0.6610729722857932,Positive +2023-10-17,1935.7,165.06,0.07,US,Retail Sales MoM ,0.7920792079207921,0.7920792079207921,Positive +2023-10-16,1934.3,182.82,-0.37,,,1.097918675666989,1.4835862307477667,Neutral +2023-10-13,1941.5,312.99,3.11,US,Michigan Consumer Sentiment Prel ,6.402439024390248,7.575757575757576,Positive +2023-10-12,1883.0,163.48,-0.23,US,Core Inflation Rate MoM ,0.0,0.0,Negative +2023-10-11,1887.3,169.96,0.64,US,PPI MoM ,0.3968253968253968,0.1982160555004956,Positive +2023-10-10,1875.3,157.34,0.59,,,1.097918675666989,1.4835862307477667,Neutral +2023-10-09,1864.3,187.8,1.04,,,1.097918675666989,1.4835862307477667,Neutral +2023-10-06,1845.2,231.02,0.73,US,Non Farm Payrolls ,65.48323471400394,76.38603696098562,Positive +2023-10-05,1831.8,172.46,-0.16,CA,Ivey PMI s.a ,4.385128693994289,6.750241080038573,Negative +2023-10-04,1834.8,195.05,-0.36,US,ISM Services PMI ,0.0,0.18467220683287425,Negative +2023-10-03,1841.5,216.78,-0.31,US,JOLTs Job Openings ,8.346213292117453,10.515356585111919,Negative +2023-10-02,1847.2,202.15,-1.01,US,ISM Manufacturing PMI ,2.4539877300613555,1.8348623853210984,Negative +2023-09-29,1866.1,245.13,-0.67,US,Core PCE Price Index MoM ,0.19940179461615157,0.19940179461615157,Negative +2023-09-28,1878.6,231.42,-0.65,US,GDP Growth Rate QoQ Final,0.0,0.0,Negative +2023-09-27,1890.9,238.53,-1.51,US,Durable Goods Orders MoM ,1.4042126379137412,3.2388663967611335,Negative +2023-09-26,1919.8,212.26,-0.87,,,1.097918675666989,1.4835862307477667,Neutral +2023-09-25,1936.6,164.26,-0.46,,,1.097918675666989,1.4835862307477667,Neutral +2023-09-22,1945.6,139.93,0.31,GB,Retail Sales MoM ,0.1982160555004956,0.0,Positive +2023-09-21,1939.6,225.91,-1.4,GB,BoE Interest Rate Decision,0.4514672686230252,0.4514672686230252,Negative +2023-09-20,1967.1,220.98,0.69,US,Fed Interest Rate Decision,0.0,0.0,Positive +2023-09-19,1953.7,131.1,0.02,US,Building Permits Prel ,5.017561465127941,5.688396677573622,Positive +2023-09-18,1953.4,138.03,0.37,,,1.097918675666989,1.4835862307477667,Neutral +2023-09-15,1946.2,199.77,0.69,US,Michigan Consumer Sentiment Prel ,2.0319303338171135,3.3165104542177324,Positive +2023-09-14,1932.8,201.74,0.02,US,PPI MoM ,0.5934718100890208,0.5934718100890208,Positive +2023-09-13,1932.5,161.0,-0.13,US,Core Inflation Rate MoM ,0.19900497512437815,0.19900497512437815,Negative +2023-09-12,1935.1,161.99,-0.62,GB,Unemployment Rate ,0.0,0.18433179723502194,Negative +2023-09-11,1947.2,131.08,0.23,,,1.097918675666989,1.4835862307477667,Neutral +2023-09-08,1942.7,138.69,0.01,CA,Unemployment Rate ,0.18001800180018018,0.3597122302158276,Positive +2023-09-07,1942.5,117.17,-0.09,CA,Ivey PMI s.a ,8.293153326904527,10.731707317073171,Negative +2023-09-06,1944.2,148.78,-0.43,US,ISM Services PMI ,3.7037037037037033,3.8924930491195573,Negative +2023-09-05,1952.6,192.79,-0.54,,,1.097918675666989,1.4835862307477667,Neutral +2023-09-04,1963.25,200.515,-0.17,,,1.097918675666989,1.4835862307477667,Neutral +2023-09-03,1966.65,200.515,-0.02,,,1.097918675666989,1.4835862307477667,Neutral +2023-09-01,1967.1,160.73,0.06,US,Non Farm Payrolls ,9.497206703910614,3.804347826086957,Positive +2023-08-31,1965.9,133.71,-0.36,US,Core PCE Price Index MoM ,0.0,0.0,Negative +2023-08-30,1973.0,142.38,0.4,US,GDP Growth Rate QoQ 2nd Est,0.5741626794258372,0.5741626794258372,Positive +2023-08-29,1965.1,174.22,0.94,US,JOLTs Job Openings ,6.614140576404726,7.660978501830185,Positive +2023-08-28,1946.8,115.55,0.36,,,1.097918675666989,1.4835862307477667,Neutral +2023-08-25,1939.9,166.99,-0.37,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Negative +2023-08-24,1947.1,137.39,-0.05,US,Durable Goods Orders MoM ,2.6431718061674,11.962224554039874,Negative +2023-08-23,1948.1,170.04,1.15,,,1.097918675666989,1.4835862307477667,Neutral +2023-08-22,1926.0,131.09,0.16,,,1.097918675666989,1.4835862307477667,Neutral +2023-08-21,1923.0,138.11,0.34,,,1.097918675666989,1.4835862307477667,Neutral +2023-08-18,1916.5,114.74,0.07,GB,Retail Sales MoM ,1.4242115971515767,1.8274111675126905,Positive +2023-08-17,1915.2,152.33,-0.68,JP,Inflation Rate YoY ,1.5122873345935728,0.37593984962406046,Negative +2023-08-16,1928.3,128.61,-0.36,US,Building Permits Prel ,1.07554417413573,0.7694280584765388,Negative +2023-08-15,1935.2,167.15,-0.45,US,Retail Sales MoM ,0.5934718100890208,0.7920792079207921,Negative +2023-08-14,1944.0,120.98,-0.13,JP,GDP Growth Annualized Prel,5.316223648029331,5.128205128205128,Negative +2023-08-11,1946.6,122.32,-0.12,US,PPI MoM ,0.19900497512437815,0.19900497512437815,Negative +2023-08-10,1948.9,168.26,-0.09,US,Core Inflation Rate MoM ,0.0,0.0,Negative +2023-08-09,1950.6,139.26,-0.47,,,1.097918675666989,1.4835862307477667,Neutral +2023-08-08,1959.9,142.34,-0.51,CN,Inflation Rate YoY ,0.2014098690835851,0.0,Negative +2023-08-07,1970.0,104.41,-0.31,CN,Balance of Trade ,13.14060446780552,15.405046480743684,Negative +2023-08-04,1976.1,156.42,0.37,US,Non Farm Payrolls ,6.701030927835052,1.5873015873015872,Positive +2023-08-03,1968.8,141.35,-0.31,US,ISM Services PMI ,0.5623242736644745,1.3245033112582836,Negative +2023-08-02,1975.0,169.66,-0.19,,,1.097918675666989,1.4835862307477667,Neutral +2023-08-01,1978.8,167.76,-1.51,US,ISM Manufacturing PMI ,0.8492569002123113,3.3542976939203384,Negative +2023-07-31,2009.2,139.96,0.47,EA,GDP Growth Rate QoQ Flash,0.19900497512437815,0.0,Positive +2023-07-28,1999.9,159.6,1.76,US,Core PCE Price Index MoM ,0.0,0.0,Positive +2023-07-27,1965.3,16.91,-1.23,US,Durable Goods Orders MoM ,7.000946073793755,7.787274453941122,Negative +2023-07-26,1989.7,11.94,0.33,US,Fed Interest Rate Decision,0.0,0.0,Positive +2023-07-25,1983.1,8.63,0.08,,,1.097918675666989,1.4835862307477667,Neutral +2023-07-24,1981.6,6.44,0.76,,,1.097918675666989,1.4835862307477667,Neutral +2023-07-21,1966.6,156.54,-0.22,GB,Retail Sales MoM ,0.9910802775024778,1.1904761904761905,Negative +2023-07-20,1970.9,189.93,-0.5,JP,Inflation Rate YoY ,0.3745318352059928,0.0,Negative +2023-07-19,1980.8,159.41,0.0,US,Building Permits Prel ,2.5445292620865163,1.1276268580215285,Neutral +2023-07-18,1980.8,264.09,1.25,US,Retail Sales MoM ,0.595829195630586,0.19900497512437815,Positive +2023-07-17,1956.4,165.83,-0.41,,,1.097918675666989,1.4835862307477667,Neutral +2023-07-14,1964.4,209.31,0.03,US,Michigan Consumer Sentiment Prel ,10.20848310567936,11.730629978276603,Positive +2023-07-13,1963.8,241.22,0.11,US,PPI MoM ,0.19940179461615157,0.0,Positive +2023-07-12,1961.7,270.87,1.27,US,Core Inflation Rate MoM ,0.19900497512437815,0.19900497512437815,Positive +2023-07-11,1937.1,189.37,0.32,GB,Unemployment Rate,0.3710575139146571,0.18535681186283615,Positive +2023-07-10,1931.0,208.09,-0.08,,,1.097918675666989,1.4835862307477667,Neutral +2023-07-07,1932.5,214.27,0.89,US,Non Farm Payrolls ,7.35632183908046,17.82608695652174,Positive +2023-07-06,1915.4,231.51,-0.61,US,ISM Services PMI ,5.47686496694995,7.435653002859863,Negative +2023-07-05,1927.1,245.93,-0.35,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Negative +2023-07-04,1933.95,200.515,0.23,,,1.097918675666989,1.4835862307477667,Neutral +2023-07-03,1929.5,152.96,0.01,US,ISM Manufacturing PMI ,2.127659574468085,4.2105263157894735,Positive +2023-06-30,1929.4,180.69,0.6,US,Core PCE Price Index MoM,0.0,0.0,Positive +2023-06-29,1917.9,205.25,0.24,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Positive +2023-06-28,1913.4,0.63,-0.09,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Negative +2023-06-27,1915.1,0.23,-0.52,US,Durable Goods Orders MoM,5.362462760675274,5.158730158730159,Negative +2023-06-26,1925.1,0.77,0.21,EA,ECB President Lagarde Speech ,1.097918675666989,1.4835862307477667,Positive +2023-06-23,1921.0,0.75,0.31,GB,Retail Sales MoM,0.9990009990009991,1.2,Positive +2023-06-22,1915.0,0.37,-1.09,US,Fed Chair Powell Testimony,1.097918675666989,1.4835862307477667,Negative +2023-06-21,1936.1,0.81,-0.14,US,Fed Chair Powell Testimony,1.097918675666989,1.4835862307477667,Negative +2023-06-20,1938.9,0.74,-1.28,US,Building Permits Prel,3.6307849654819826,3.3707865168539355,Negative +2023-06-19,1964.05,200.515,-0.27,,,1.097918675666989,1.4835862307477667,Neutral +2023-06-18,1969.45,200.515,0.37,,,1.097918675666989,1.4835862307477667,Neutral +2023-06-16,1962.2,0.62,0.02,US,Michigan Consumer Sentiment Prel ,6.244995996797435,4.932378679395388,Positive +2023-06-15,1961.8,0.82,-0.36,US,Retail Sales MoM,0.7984031936127743,0.19900497512437815,Negative +2023-06-14,1968.9,199.71,0.53,US,PPI MoM,0.4016064257028113,0.8016032064128256,Positive +2023-06-13,1958.6,198.4,-0.56,US,Core Inflation Rate YoY,0.0,0.18066847335140035,Negative +2023-06-12,1969.7,122.54,-0.38,,,1.097918675666989,1.4835862307477667,Neutral +2023-06-09,1977.2,130.41,-0.07,CA,Unemployment Rate,0.18132366273798747,0.18132366273798747,Negative +2023-06-08,1978.6,191.84,1.03,CN,Inflation Rate YoY,0.19900497512437815,0.0,Positive +2023-06-07,1958.4,189.53,-1.17,US,Balance of Trade ,0.8064516129032372,4.74308300395258,Negative +2023-06-06,1981.5,136.0,0.36,CA,Ivey PMI s.a,6.62488809310654,5.405405405405405,Positive +2023-06-05,1974.3,179.99,0.24,US,ISM Services PMI,3.6714975845410738,4.050144648023147,Positive +2023-06-02,1969.6,209.69,-1.3,US,Non Farm Payrolls,56.22641509433962,61.15384615384616,Negative +2023-06-01,1995.5,176.91,0.68,US,ISM Manufacturing PMI,0.21074815595363838,2.2940563086548513,Positive +2023-05-31,1982.1,207.75,0.25,US,JOLTs Job Openings ,7.110069342709247,8.895237157070389,Positive +2023-05-30,1977.1,264.37,0.89,CN,NBS Manufacturing PMI,1.2096774193548419,2.0080321285140563,Positive +2023-05-29,1959.75,200.515,-0.09,,,1.097918675666989,1.4835862307477667,Neutral +2023-05-28,1961.5,200.515,-0.08,,,1.097918675666989,1.4835862307477667,Neutral +2023-05-26,1963.1,130.07,1.03,,,1.097918675666989,1.4835862307477667,Neutral +2023-05-25,1943.1,0.0,-1.0,,,1.097918675666989,1.4835862307477667,Neutral +2023-05-24,1962.8,0.19,-0.49,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Negative +2023-05-23,1972.4,0.0,-0.12,,,1.097918675666989,1.4835862307477667,Neutral +2023-05-22,1974.8,0.01,-0.2,,,1.097918675666989,1.4835862307477667,Neutral +2023-05-19,1978.7,0.11,1.13,,,1.097918675666989,1.4835862307477667,Neutral +2023-05-18,1956.5,0.02,-1.22,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Negative +2023-05-17,1980.7,0.01,-0.39,US,Building Permits Prel ,1.0900596937451406,0.7280291211648473,Negative +2023-05-16,1988.4,0.05,-1.47,US,Retail Sales MoM ,0.7905138339920948,0.5934718100890208,Negative +2023-05-15,2018.0,0.0,-0.09,,,1.097918675666989,1.4835862307477667,Neutral +2023-05-12,2019.8,220.5,-0.03,,,1.097918675666989,1.4835862307477667,Neutral +2023-05-11,2020.5,296.98,-0.81,US,PPI MoM ,0.19900497512437815,0.19940179461615157,Negative +2023-05-10,2037.1,260.81,-0.28,US,Core Inflation Rate YoY ,0.0,0.18001800180018018,Negative +2023-05-09,2042.9,199.7,0.48,,,1.097918675666989,1.4835862307477667,Neutral +2023-05-08,2033.2,182.21,0.41,,,1.097918675666989,1.4835862307477667,Neutral +2023-05-05,2024.8,283.3,-1.5,,,1.097918675666989,1.4835862307477667,Neutral +2023-05-04,2055.7,311.0,0.92,US,Balance of Trade ,1.4229249011857796,1.741884402216946,Positive +2023-05-03,2037.0,229.67,0.68,US,ISM Services PMI ,0.19102196752626824,0.7662835249042118,Positive +2023-05-02,2023.3,245.64,1.56,US,JOLTs Job Openings ,1.8168426221458434,1.08427796944307,Positive +2023-05-01,1992.2,173.02,-0.35,,,1.097918675666989,1.4835862307477667,Neutral +2023-04-28,1999.1,172.45,0.01,US,Core PCE Price Index MoM ,0.0,0.198609731876862,Positive +2023-04-27,1999.0,203.9,0.61,US,GDP Growth Rate QoQ Adv,1.7458777885548016,2.321083172147002,Positive +2023-04-26,1986.9,0.62,-0.41,US,Durable Goods Orders MoM ,4.8123195380173245,5.009633911368016,Negative +2023-04-25,1995.1,0.85,0.23,,,1.097918675666989,1.4835862307477667,Neutral +2023-04-24,1990.6,0.54,0.47,,,1.097918675666989,1.4835862307477667,Neutral +2023-04-21,1981.3,0.62,-1.42,GB,Retail Sales MoM ,0.8113590263691681,0.8113590263691681,Negative +2023-04-20,2009.8,0.42,0.59,GB,Gfk Consumer Confidence ,15.625,12.698412698412698,Positive +2023-04-19,1998.0,0.92,-0.61,GB,Inflation Rate YoY ,0.5004170141784825,0.16625103906899202,Negative +2023-04-18,2010.3,0.22,0.81,US,Building Permits Prel ,1.9156096298213785,1.9156096298213785,Positive +2023-04-17,1994.2,0.55,-0.4,CN,GDP Growth Rate YoY,0.9216589861751149,2.4141132776230267,Negative +2023-04-14,2002.2,0.72,-1.92,US,Retail Sales MoM ,1.2170385395537524,0.2038735983690114,Negative +2023-04-13,2041.3,1.04,1.51,US,PPI MoM ,1.0050251256281406,1.2048192771084338,Positive +2023-04-12,2010.9,0.17,0.3,US,Core Inflation Rate YoY ,0.0,0.18001800180018018,Positive +2023-04-11,2004.8,0.07,0.79,,,1.097918675666989,1.4835862307477667,Neutral +2023-04-10,1989.1,0.65,-1.13,JP,Consumer Confidence ,5.9880239520958085,3.147353361945641,Negative +2023-04-06,2011.9,0.49,-0.45,CA,Unemployment Rate ,0.18165304268846394,0.3629764065335743,Negative +2023-04-05,2020.9,0.53,-0.06,US,Balance of Trade ,2.166064981949458,2.166064981949458,Negative +2023-04-04,2022.2,0.81,1.93,US,JOLTs Job Openings ,4.397355960808225,7.997791173899052,Positive +2023-04-03,1983.9,0.74,0.76,US,ISM Manufacturing PMI ,2.5316455696202596,5.607476635514025,Positive +2023-03-31,1969.0,0.96,-0.57,US,Core PCE Price Index MoM ,0.198609731876862,0.5946481665014867,Negative +2023-03-30,1980.3,10.12,0.68,CN,NBS Manufacturing PMI ,0.7662835249042118,1.344860710854939,Positive +2023-03-29,1966.9,88.56,-0.33,,,1.097918675666989,1.4835862307477667,Neutral +2023-03-28,1973.5,183.58,0.1,,,1.097918675666989,1.4835862307477667,Neutral +2023-03-27,1971.5,107.04,-1.51,,,1.097918675666989,1.4835862307477667,Neutral +2023-03-24,2001.7,118.69,-0.58,US,Durable Goods Orders MoM ,3.2128514056224904,3.410230692076229,Negative +2023-03-23,2013.3,74.55,2.37,GB,BoE Interest Rate Decision,0.0,0.0,Positive +2023-03-22,1966.6,60.53,0.42,US,Fed Interest Rate Decision,0.0,0.0,Positive +2023-03-21,1958.3,65.17,-2.07,CA,Inflation Rate YoY ,0.3616636528028936,0.0,Negative +2023-03-20,1999.7,69.06,0.48,,,1.097918675666989,1.4835862307477667,Neutral +2023-03-17,1990.2,67.46,2.6,US,Michigan Consumer Sentiment Prel ,5.479452054794522,6.948640483383688,Positive +2023-03-16,1939.7,34.77,-0.43,US,Building Permits Prel ,9.52380952380952,10.067462376751424,Negative +2023-03-15,1948.1,84.73,1.95,US,PPI MoM ,0.7984031936127743,0.9970089730807579,Positive +2023-03-14,1910.9,261.28,-0.29,US,Core Inflation Rate YoY ,0.0,0.18001800180018018,Negative +2023-03-13,1916.5,452.33,2.64,US,President Biden Speech on Banking System ,1.097918675666989,1.4835862307477667,Positive +2023-03-10,1867.2,345.81,1.78,US,Non Farm Payrolls ,41.005802707930364,38.69731800766284,Positive +2023-03-09,1834.6,228.47,0.88,JP,BoJ Interest Rate Decision,0.0,0.0,Positive +2023-03-08,1818.6,208.29,-0.08,US,Balance of Trade ,0.8810572687224796,1.0271460014673555,Negative +2023-03-07,1820.0,248.23,-1.87,US,Fed Chair Powell Testimony,1.097918675666989,1.4835862307477667,Negative +2023-03-06,1854.6,136.22,0.0,CA,Ivey PMI s.a ,7.926267281105985,6.319702602230482,Neutral +2023-03-03,1854.6,158.96,0.77,US,ISM Non-Manufacturing PMI ,1.0849909584086825,0.9033423667570009,Positive +2023-03-02,1840.5,139.76,-0.27,EA,Inflation Rate YoY Flash ,0.5141388174807203,0.17108639863130895,Negative +2023-03-01,1845.4,182.58,0.47,US,ISM Manufacturing PMI ,0.6204756980351543,0.6204756980351543,Positive +2023-02-28,1836.7,184.51,0.65,CA,GDP Growth Rate QoQ,1.097918675666989,0.796812749003984,Positive +2023-02-27,1824.9,130.43,0.87,US,Durable Goods Orders MoM ,1.0928961748633874,2.17391304347826,Positive +2023-02-24,1809.2,0.4,-0.53,US,Core PCE Price Index MoM ,0.39603960396039606,0.5946481665014867,Negative +2023-02-23,1818.8,0.65,-0.79,GB,Gfk Consumer Confidence ,12.5,10.126582278481013,Negative +2023-02-22,1833.3,0.57,-0.5,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Negative +2023-02-21,1842.5,210.17,-0.43,CA,Inflation Rate YoY ,0.35714285714285743,0.0,Negative +2023-02-20,1850.5,200.515,0.15,,,1.097918675666989,1.4835862307477667,Neutral +2023-02-19,1847.75,200.515,0.4,,,1.097918675666989,1.4835862307477667,Neutral +2023-02-17,1840.4,0.04,-0.09,GB,Retail Sales MoM ,1.5968063872255487,2.607823470411234,Negative +2023-02-16,1842.0,0.22,0.43,US,Building Permits Prel ,0.596367579289787,1.8852679773767917,Positive +2023-02-15,1834.2,0.37,-1.07,US,Retail Sales MoM ,2.2900763358778624,3.4548944337811895,Negative +2023-02-14,1854.0,0.66,0.11,US,Core Inflation Rate YoY ,0.18001800180018018,0.3603603603603607,Positive +2023-02-13,1851.9,0.57,-0.59,JP,GDP Growth Annualized Prel,2.729044834307992,1.9569471624266144,Negative +2023-02-10,1862.8,0.03,-0.18,US,Michigan Consumer Sentiment Prel ,2.114803625377652,2.114803625377652,Negative +2023-02-09,1866.2,0.22,-0.6,CN,Inflation Rate YoY ,0.19175455417066106,0.19212295869356408,Negative +2023-02-08,1877.4,0.23,0.3,,,1.097918675666989,1.4835862307477667,Neutral +2023-02-07,1871.7,0.3,0.29,US,Balance of Trade ,1.6308376575240833,2.071005917159751,Positive +2023-02-06,1866.2,0.42,0.18,CA,Ivey PMI s.a ,34.429400386847206,39.762611275964396,Positive +2023-02-03,1862.9,0.99,-2.79,US,Non Farm Payrolls ,94.45234708392604,92.37288135593221,Negative +2023-02-02,1916.3,0.75,-0.6,EA,Deposit Facility Rate,0.0,0.0,Negative +2023-02-01,1927.8,2.29,-0.09,US,ISM Manufacturing PMI ,1.2448132780083017,1.2448132780083017,Negative +2023-01-31,1929.5,1.91,0.34,EA,GDP Growth Rate QoQ Flash,0.4,0.19980019980019983,Positive +2023-01-30,1922.9,27.22,-0.71,CN,NBS Manufacturing PMI ,0.594648166501495,1.1928429423459275,Negative +2023-01-27,1936.6,2.33,-0.05,US,Core PCE Price Index MoM ,0.0,0.398406374501992,Negative +2023-01-26,1937.6,2.1,-0.65,US,Durable Goods Orders MoM ,5.735430157261795,6.307977736549166,Negative +2023-01-25,1950.3,1.27,0.37,CA,BoC Interest Rate Decision,0.0,0.0,Positive +2023-01-24,1943.1,1.08,0.36,,,1.097918675666989,1.4835862307477667,Neutral +2023-01-23,1936.2,0.97,0.41,,,1.097918675666989,1.4835862307477667,Neutral +2023-01-20,1928.2,165.27,0.22,GB,Retail Sales MoM ,3.015075376884422,2.6183282980866065,Positive +2023-01-19,1923.9,214.25,0.89,US,Building Permits Prel ,2.162162162162164,3.7533512064343078,Positive +2023-01-18,1907.0,218.97,-0.01,US,PPI MoM ,0.8048289738430584,0.8048289738430584,Negative +2023-01-17,1907.2,0.71,-0.14,GB,Claimant Count Change ,1.097918675666989,20.163487738419615,Negative +2023-01-16,1909.9,268.37,-0.52,CN,GDP Growth Rate YoY,2.101241642788921,2.6819923371647514,Negative +2023-01-15,1919.9,200.515,-0.09,,,1.097918675666989,1.4835862307477667,Neutral +2023-01-13,1921.7,247.88,1.21,US,Michigan Consumer Sentiment Prel ,6.5027755749405145,8.988764044943812,Positive +2023-01-12,1898.8,265.17,1.06,US,Core Inflation Rate YoY ,0.0,0.1793721973094172,Positive +2023-01-11,1878.9,222.25,0.13,CN,Inflation Rate YoY ,0.0,0.3853564547206169,Positive +2023-01-10,1876.5,170.51,-0.07,,,1.097918675666989,1.4835862307477667,Neutral +2023-01-09,1877.8,204.55,0.43,,,1.097918675666989,1.4835862307477667,Neutral +2023-01-06,1869.7,215.37,1.58,US,Non Farm Payrolls ,10.849056603773585,1.3513513513513513,Positive +2023-01-05,1840.6,188.6,-0.99,US,Balance of Trade ,17.228464419475657,15.849056603773585,Negative +2023-01-04,1859.0,198.35,0.7,US,ISM Manufacturing PMI ,0.2042900919305443,1.219512195121954,Positive +2023-01-03,1846.1,212.27,0.56,,,1.097918675666989,1.4835862307477667,Neutral +2023-01-02,1835.8,200.515,0.53,CN,Caixin Manufacturing PMI ,0.4048582995951474,2.0408163265306123,Positive +2022-12-30,1826.2,107.5,0.01,CN,NBS Manufacturing PMI ,2.083333333333333,5.128205128205128,Positive +2022-12-29,1826.0,105.99,0.56,,,1.097918675666989,1.4835862307477667,Neutral +2022-12-28,1815.8,118.08,-0.4,,,1.097918675666989,1.4835862307477667,Neutral +2022-12-27,1823.1,159.62,0.74,,,1.097918675666989,1.4835862307477667,Neutral +2022-12-26,1809.7,200.515,0.3,,,1.097918675666989,1.4835862307477667,Neutral +2022-12-23,1804.2,105.46,0.5,US,Durable Goods Orders MoM ,3.083247687564235,3.285420944558522,Positive +2022-12-22,1795.3,175.77,-1.65,JP,Inflation Rate YoY ,1.097918675666989,0.18570102135561764,Negative +2022-12-21,1825.4,110.18,0.0,CA,Inflation Rate YoY ,0.17621145374449354,0.17621145374449354,Neutral +2022-12-20,1825.4,197.5,1.54,US,Building Permits Prel ,7.473216618761433,7.2213500784929305,Positive +2022-12-19,1797.7,86.09,-0.14,JP,BoJ Interest Rate Decision,0.0,0.0,Negative +2022-12-16,1800.2,128.75,0.69,GB,Retail Sales MoM ,1.4014014014014013,1.4014014014014013,Positive +2022-12-15,1787.8,185.32,-1.7,US,Retail Sales MoM ,1.0070493454179255,1.6064257028112452,Negative +2022-12-14,1818.7,143.8,-0.37,US,Fed Interest Rate Decision,0.0,0.0,Negative +2022-12-13,1825.5,230.91,1.85,US,Core Inflation Rate YoY ,0.17841213202497785,0.3565062388591804,Positive +2022-12-12,1792.3,107.78,-1.02,GB,GDP MoM ,0.1982160555004956,0.1982160555004956,Negative +2022-12-09,1810.7,150.94,0.51,US,PPI MoM ,0.19900497512437815,0.0,Positive +2022-12-08,1801.5,116.27,0.19,CN,Inflation Rate YoY ,0.0,0.3868471953578333,Positive +2022-12-07,1798.0,155.57,0.88,,,1.097918675666989,1.4835862307477667,Neutral +2022-12-06,1782.4,127.86,0.06,US,Balance of Trade ,2.2900763358778593,6.924101198402134,Positive +2022-12-05,1781.3,179.82,-1.56,US,ISM Non-Manufacturing PMI ,5.776173285198561,6.334841628959276,Negative +2022-12-02,1809.6,183.72,-0.31,US,Non Farm Payrolls ,27.155172413793103,22.362869198312236,Negative +2022-12-01,1815.2,226.15,3.14,US,Personal Income MoM ,0.5934718100890208,0.7920792079207921,Positive +2022-11-30,1759.9,192.24,-0.22,US,JOLTs Job Openings ,0.3143200517703515,0.6073433330266008,Negative +2022-11-29,1763.7,127.32,1.34,CN,NBS Manufacturing PMI ,2.0408163265306123,2.0408163265306123,Positive +2022-11-28,1740.3,132.77,-0.78,,,1.097918675666989,1.4835862307477667,Neutral +2022-11-25,1754.0,134.3,0.0,,,1.097918675666989,1.4835862307477667,Neutral +2022-11-24,1754.0,134.3,0.48,,,1.097918675666989,1.4835862307477667,Neutral +2022-11-23,1745.6,167.77,0.33,US,Durable Goods Orders MoM ,1.183431952662722,1.3820335636722607,Positive +2022-11-22,1739.9,153.09,0.02,,,1.097918675666989,1.4835862307477667,Neutral +2022-11-21,1739.6,166.08,-0.84,,,1.097918675666989,1.4835862307477667,Neutral +2022-11-18,1754.4,137.33,-0.49,GB,Retail Sales MoM ,0.5946481665014867,1.393034825870647,Negative +2022-11-17,1763.0,169.1,-0.72,US,Building Permits Prel ,1.097918675666989,3.0568779754447477,Negative +2022-11-16,1775.8,200.76,-0.06,US,Retail Sales MoM ,0.5865102639296187,0.7827788649706457,Negative +2022-11-15,1776.8,283.02,-0.01,US,PPI MoM ,0.3976143141153082,0.19900497512437815,Negative +2022-11-14,1776.9,191.35,0.42,CN,Industrial Production YoY ,0.3629764065335743,1.0849909584086797,Positive +2022-11-11,1769.4,227.04,0.9,US,Michigan Consumer Sentiment Prel ,8.333333333333329,7.99999999999999,Positive +2022-11-10,1753.7,305.72,2.33,US,Core Inflation Rate YoY ,0.3546099290780145,0.7079646017699122,Positive +2022-11-09,1713.7,239.65,-0.13,,,1.097918675666989,1.4835862307477667,Neutral +2022-11-08,1716.0,297.62,2.11,CN,Inflation Rate YoY ,0.5741626794258372,0.9551098376313272,Positive +2022-11-07,1680.5,187.59,0.23,,,1.097918675666989,1.4835862307477667,Neutral +2022-11-04,1676.6,293.52,2.8,US,Non Farm Payrolls ,26.406926406926406,8.366533864541832,Positive +2022-11-03,1630.9,254.7,-1.16,US,Balance of Trade ,1.5224913494809609,1.8018018018017976,Negative +2022-11-02,1650.0,220.93,0.02,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Positive +2022-11-01,1649.7,197.98,0.55,US,ISM Manufacturing PMI ,0.39525691699605303,0.19743336623889712,Positive +2022-10-31,1640.7,128.41,-0.25,EA,Inflation Rate YoY Flash ,0.8271298593879246,0.49545829892650745,Negative +2022-10-28,1644.8,196.36,-1.25,US,Personal Income MoM ,0.198609731876862,0.3976143141153082,Negative +2022-10-27,1665.6,189.29,-0.22,US,Durable Goods Orders MoM ,0.39603960396039606,0.3976143141153082,Negative +2022-10-26,1669.2,186.93,0.68,CA,BoC Monetary Policy Report,1.097918675666989,1.4835862307477667,Positive +2022-10-25,1658.0,182.8,0.24,,,1.097918675666989,1.4835862307477667,Neutral +2022-10-24,1654.1,171.02,-0.13,,,1.097918675666989,1.4835862307477667,Neutral +2022-10-21,1656.3,271.1,1.19,GB,Retail Sales MoM ,1.834862385321101,2.238046795523906,Positive +2022-10-20,1636.8,163.73,0.16,GB,Gfk Consumer Confidence ,10.204081632653061,12.121212121212121,Positive +2022-10-19,1634.2,179.25,-1.3,US,Building Permits ,1.6609672691744028,3.801530486299677,Negative +2022-10-18,1655.8,163.17,-0.49,CN,20th National Congress of the Chinese Communist Party,1.097918675666989,1.4835862307477667,Negative +2022-10-17,1664.0,148.89,0.92,GB,Chancellor Jeremy Hunt Statement,1.097918675666989,1.4835862307477667,Positive +2022-10-14,1648.9,183.17,-1.68,US,Retail Sales MoM ,0.39920159680638717,0.39920159680638717,Negative +2022-10-13,1677.0,237.01,-0.03,US,Core Inflation Rate YoY ,0.17683465959328046,0.3539823008849561,Negative +2022-10-12,1677.5,131.77,-0.5,US,PPI MoM ,0.3976143141153082,0.796812749003984,Negative +2022-10-11,1686.0,171.81,0.64,GB,Claimant Count Change ,1.097918675666989,84.93150684931507,Positive +2022-10-10,1675.2,157.15,-1.99,,,1.097918675666989,1.4835862307477667,Neutral +2022-10-07,1709.3,157.45,-0.67,US,Non Farm Payrolls ,5.058365758754864,9.747292418772563,Negative +2022-10-06,1720.8,139.44,0.0,CA,Ivey PMI s.a ,1.097918675666989,7.792207792207792,Neutral +2022-10-05,1720.8,173.22,-0.56,US,Balance of Trade ,0.4474272930648726,0.8928571428571344,Negative +2022-10-04,1730.5,205.08,1.67,US,JOLTs Job Openings ,6.615356422943004,9.452444364194456,Positive +2022-10-03,1702.0,215.49,1.79,US,ISM Manufacturing PMI ,2.4975984630163386,3.816793893129771,Positive +2022-09-30,1672.0,179.99,0.2,US,Personal Income MoM ,0.0,0.19900497512437815,Positive +2022-09-29,1668.6,201.96,-0.08,CN,NBS Manufacturing PMI ,0.9930486593843099,0.594648166501495,Negative +2022-09-28,1670.0,279.82,2.07,,,1.097918675666989,1.4835862307477667,Neutral +2022-09-27,1636.2,197.06,0.17,US,Durable Goods Orders MoM ,0.4024144869215292,1.415571284125379,Positive +2022-09-26,1633.4,219.86,-1.34,,,1.097918675666989,1.4835862307477667,Neutral +2022-09-23,1655.6,243.05,-1.52,,,1.097918675666989,1.4835862307477667,Neutral +2022-09-22,1681.1,241.28,0.32,GB,Gfk Consumer Confidence ,15.555555555555555,33.734939759036145,Positive +2022-09-21,1675.7,227.94,0.28,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Positive +2022-09-20,1671.1,143.93,-0.42,US,Building Permits ,4.50690574267023,5.449722691102001,Negative +2022-09-19,1678.2,141.17,-0.31,JP,Inflation Rate YoY ,1.097918675666989,0.7575757575757576,Negative +2022-09-16,1683.5,217.23,0.37,US,Michigan Consumer Sentiment Prel ,0.8298755186721992,1.5113350125944562,Positive +2022-09-15,1677.3,268.09,-1.86,US,Retail Sales MoM ,0.5982053838484547,0.398406374501992,Negative +2022-09-14,1709.1,163.29,-0.48,US,PPI MoM ,0.0,0.4,Negative +2022-09-13,1717.4,232.7,-1.33,US,Core Inflation Rate YoY ,0.35587188612099674,0.7130124777183608,Negative +2022-09-12,1740.6,154.37,0.69,GB,GDP MoM ,0.3976143141153082,0.19940179461615157,Positive +2022-09-09,1728.6,154.71,0.49,,,1.097918675666989,1.4835862307477667,Neutral +2022-09-08,1720.2,184.18,-0.44,CN,Inflation Rate YoY ,0.5698005698005697,0.7590132827324478,Negative +2022-09-07,1727.8,173.62,1.17,US,Balance of Trade ,0.5714285714285796,1.0021474588403765,Positive +2022-09-06,1707.9,0.02,-0.29,US,ISM Non-Manufacturing PMI ,3.185840707964597,3.365810451727189,Negative +2022-09-05,1712.9,206.27,-0.33,GB,S&P Global/CIPS UK Services PMI Final ,3.065134099616861,3.065134099616861,Negative +2022-09-04,1718.65,200.515,-0.23,,,1.097918675666989,1.4835862307477667,Neutral +2022-09-02,1722.6,174.68,0.78,US,Non Farm Payrolls ,4.870129870129871,1.5974440894568689,Positive +2022-09-01,1709.3,198.62,-0.98,US,ISM Manufacturing PMI ,1.5122873345935675,1.5122873345935675,Negative +2022-08-31,1726.2,176.73,-0.58,EA,Inflation Rate YoY Flash ,0.16934801016088075,0.0,Negative +2022-08-30,1736.3,130.66,-0.77,US,JOLTs Job Openings ,6.954912071929141,6.499846079423024,Negative +2022-08-29,1749.7,156.22,-0.01,,,1.097918675666989,1.4835862307477667,Neutral +2022-08-26,1749.8,176.9,-1.22,US,Personal Income MoM ,0.7936507936507936,0.595829195630586,Negative +2022-08-25,1771.4,117.57,0.56,,,1.097918675666989,1.4835862307477667,Neutral +2022-08-24,1761.5,112.65,0.02,US,Durable Goods Orders MoM ,1.1928429423459244,1.5873015873015872,Positive +2022-08-23,1761.2,145.26,0.73,GB,S&P Global/CIPS Manufacturing PMI Flash ,10.397553516819576,10.783316378433362,Positive +2022-08-22,1748.4,142.86,-0.82,,,1.097918675666989,1.4835862307477667,Neutral +2022-08-19,1762.9,138.7,-0.47,GB,Retail Sales MoM ,0.9990009990009991,0.7984031936127743,Negative +2022-08-18,1771.2,124.32,-0.31,GB,Gfk Consumer Confidence ,4.705882352941177,2.3255813953488373,Negative +2022-08-17,1776.7,137.83,-0.73,US,Retail Sales MoM ,0.19980019980019983,0.39920159680638717,Negative +2022-08-16,1789.7,94.4,-0.47,US,Building Permits ,1.1100832562442193,0.18416206261510146,Negative +2022-08-15,1798.1,137.77,-0.96,,,1.097918675666989,1.4835862307477667,Neutral +2022-08-12,1815.5,118.65,0.46,US,Michigan Consumer Sentiment Prel ,4.788213627992636,7.076350093109878,Positive +2022-08-11,1807.2,121.26,-0.36,US,PPI MoM ,1.4042126379137412,1.801801801801802,Negative +2022-08-10,1813.7,154.59,0.08,US,Core Inflation Rate YoY ,0.35714285714285743,0.0,Positive +2022-08-09,1812.3,120.51,0.39,CN,Inflation Rate YoY ,0.3787878787878791,0.3802281368821289,Positive +2022-08-08,1805.2,103.68,0.78,,,1.097918675666989,1.4835862307477667,Neutral +2022-08-05,1791.2,168.9,-0.87,US,Non Farm Payrolls ,71.37355584082157,58.119658119658126,Negative +2022-08-04,1806.9,153.29,1.72,US,Balance of Trade ,0.6301197227473221,4.207920792079215,Positive +2022-08-03,1776.4,151.73,-0.74,US,ISM Non-Manufacturing PMI ,5.7553956834532425,7.622504537205087,Negative +2022-08-02,1789.7,174.17,0.11,US,JOLTs Job Openings ,2.661027403295441,2.661027403295441,Positive +2022-08-01,1787.7,133.74,0.33,US,ISM Manufacturing PMI ,1.5122873345935675,1.1320754716981025,Positive +2022-07-29,1781.8,136.89,0.71,US,Personal Income MoM ,0.1978239366963403,0.1978239366963403,Positive +2022-07-28,1769.2,192.86,2.91,,,1.097918675666989,1.4835862307477667,Neutral +2022-07-27,1719.1,144.87,0.08,US,Durable Goods Orders MoM ,4.733727810650888,4.330708661417323,Positive +2022-07-26,1717.7,147.37,-0.08,,,1.097918675666989,1.4835862307477667,Neutral +2022-07-25,1719.1,160.72,-0.48,,,1.097918675666989,1.4835862307477667,Neutral +2022-07-22,1727.4,200.62,0.82,GB,Retail Sales MoM ,0.4016064257028113,0.20060180541624875,Positive +2022-07-21,1713.4,248.88,0.78,GB,Gfk Consumer Confidence ,2.4390243902439024,7.142857142857142,Positive +2022-07-20,1700.2,174.47,-0.61,GB,Inflation Rate YoY ,0.1684919966301602,0.16820857863751065,Negative +2022-07-19,1710.7,131.77,0.03,US,Building Permits ,1.6147635524798218,0.22909507445590446,Positive +2022-07-18,1710.2,157.54,0.39,,,1.097918675666989,1.4835862307477667,Neutral +2022-07-15,1703.6,176.8,-0.13,US,Retail Sales MoM ,0.3929273084479371,0.9852216748768474,Negative +2022-07-14,1705.8,266.35,-1.71,US,PPI MoM ,0.5888125613346418,0.39215686274509803,Negative +2022-07-13,1735.5,300.55,0.62,US,Core Inflation Rate YoY ,0.3584229390680994,0.17905102954341878,Positive +2022-07-12,1724.8,255.17,-0.4,,,1.097918675666989,1.4835862307477667,Neutral +2022-07-11,1731.7,171.9,-0.61,,,1.097918675666989,1.4835862307477667,Neutral +2022-07-08,1742.3,189.18,0.15,US,Non Farm Payrolls ,32.44929797191888,21.39673105497771,Positive +2022-07-07,1739.7,151.26,0.18,US,Balance of Trade,0.708382526564338,0.5865102639296188,Positive +2022-07-06,1736.5,258.82,-1.83,US,ISM Non-Manufacturing PMI ,1.8083182640144666,0.17937219730940684,Negative +2022-07-05,1768.9,1.33,0.28,GB,S&P Global/CIPS UK Services PMI Final ,1.6559337626494914,1.6559337626494914,Positive +2022-07-04,1763.9,310.37,-2.09,,,1.097918675666989,1.4835862307477667,Neutral +2022-07-01,1801.5,249.49,-0.32,US,ISM Manufacturing PMI ,3.489439853076214,3.669724770642202,Negative +2022-06-30,1807.3,208.9,-0.56,US,Personal Income MoM,0.0,0.3968253968253968,Negative +2022-06-29,1817.5,155.54,-0.2,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Negative +2022-06-28,1821.2,111.4,-0.2,EA,ECB Forum on Central Banking,1.097918675666989,1.4835862307477667,Negative +2022-06-27,1824.8,143.82,-0.3,US,Durable Goods Orders MoM,1.1904761904761905,1.9920318725099602,Negative +2022-06-24,1830.3,139.72,0.03,GB,Retail Sales MoM,0.4048582995951417,0.4032258064516129,Positive +2022-06-23,1829.8,167.07,-0.47,US,Fed Chair Powell Testimony,1.097918675666989,1.4835862307477667,Negative +2022-06-22,1838.4,149.55,-0.02,US,Fed Chair Powell Testimony,1.097918675666989,1.4835862307477667,Negative +2022-06-21,1838.8,176.3,0.0,,,1.097918675666989,1.4835862307477667,Neutral +2022-06-20,1838.8,176.3,-0.1,,,1.097918675666989,1.4835862307477667,Neutral +2022-06-17,1840.6,141.72,-0.5,,,1.097918675666989,1.4835862307477667,Neutral +2022-06-16,1849.9,180.89,1.67,US,Building Permits,4.017857142857136,4.236343366778148,Positive +2022-06-15,1819.6,203.42,0.34,US,Retail Sales MoM,1.001001001001001,1.2,Positive +2022-06-14,1813.5,165.15,-1.0,US,PPI MoM,0.0,0.1970443349753695,Negative +2022-06-13,1831.8,252.54,-2.33,GB,GDP MoM ,0.8016032064128256,0.6018054162487463,Negative +2022-06-10,1875.5,267.2,1.23,US,Core Inflation Rate YoY,0.1787310098302057,0.0,Positive +2022-06-09,1852.8,131.29,-0.2,CN,Inflation Rate YoY,0.19175455417066106,0.19212295869356408,Negative +2022-06-08,1856.5,114.14,0.24,CN,Balance of Trade,30.13937282229966,44.327990135635034,Positive +2022-06-07,1852.1,119.21,0.46,US,Balance of Trade ,2.7334851936218745,4.404291360813106,Positive +2022-06-06,1843.7,103.18,-0.35,,,1.097918675666989,1.4835862307477667,Neutral +2022-06-03,1850.2,115.34,-1.13,US,Non Farm Payrolls,18.156424581005588,19.69057665260197,Negative +2022-06-02,1871.4,127.47,1.23,,,1.097918675666989,1.4835862307477667,Neutral +2022-06-01,1848.7,158.04,0.02,US,ISM Manufacturing PMI,2.8673835125448055,2.3235031277926796,Positive +2022-05-31,1848.4,201.8,0.0,EA,Inflation Rate YoY Flash,0.6908462867012096,0.8643042350907527,Neutral +2022-05-30,1848.4,201.8,-0.48,,,1.097918675666989,1.4835862307477667,Neutral +2022-05-27,1857.3,123.76,0.53,,,1.097918675666989,1.4835862307477667,Neutral +2022-05-26,1847.6,123.36,0.07,,,1.097918675666989,1.4835862307477667,Neutral +2022-05-25,1846.3,182.82,-1.02,US,Durable Goods Orders MoM ,0.39603960396039606,0.0,Negative +2022-05-24,1865.4,174.76,0.95,GB,S&P Global/CIPS Manufacturing PMI Flash,0.7233273056057841,1.0830324909747315,Positive +2022-05-23,1847.8,163.27,0.31,,,1.097918675666989,1.4835862307477667,Neutral +2022-05-20,1842.1,143.05,0.05,,,1.097918675666989,1.4835862307477667,Neutral +2022-05-19,1841.2,175.24,1.39,GB,Gfk Consumer Confidence,2.564102564102564,0.0,Positive +2022-05-18,1815.9,150.35,-0.16,US,Building Permits ,0.30231051608723364,0.04311273981462004,Negative +2022-05-17,1818.9,137.29,0.27,US,Retail Sales MoM ,0.0,0.5911330049261082,Positive +2022-05-16,1814.0,159.49,0.32,,,1.097918675666989,1.4835862307477667,Neutral +2022-05-13,1808.2,179.48,-0.9,,,1.097918675666989,1.4835862307477667,Neutral +2022-05-12,1824.6,255.61,-1.57,US,PPI MoM ,0.0,0.0,Negative +2022-05-11,1853.7,243.56,0.69,US,Core Inflation Rate YoY ,0.3565062388591804,0.0,Positive +2022-05-10,1841.0,260.81,-0.95,CN,Inflation Rate YoY ,0.5774783445620795,0.5774783445620795,Negative +2022-05-09,1858.6,218.82,-1.29,,,1.097918675666989,1.4835862307477667,Neutral +2022-05-06,1882.8,194.28,0.38,,,1.097918675666989,1.4835862307477667,Neutral +2022-05-05,1875.7,218.39,0.37,,,1.097918675666989,1.4835862307477667,Neutral +2022-05-04,1868.8,161.48,-0.1,US,Balance of Trade ,2.5949953660797007,17.729083665338642,Negative +2022-05-03,1870.6,167.43,0.38,US,JOLTs Job Openings ,4.662618370206799,2.342667618287921,Positive +2022-05-02,1863.6,193.83,-2.52,,,1.097918675666989,1.4835862307477667,Neutral +2022-04-29,1911.7,177.14,1.08,US,Personal Income MoM ,0.1982160555004956,0.1982160555004956,Positive +2022-04-28,1891.3,170.91,0.14,,,1.097918675666989,1.4835862307477667,Neutral +2022-04-27,1888.7,178.2,-0.81,,,1.097918675666989,1.4835862307477667,Neutral +2022-04-26,1904.1,166.2,0.43,US,Durable Goods Orders MoM ,0.3929273084479371,0.5888125613346418,Positive +2022-04-25,1896.0,231.49,-1.98,,,1.097918675666989,1.4835862307477667,Neutral +2022-04-22,1934.3,176.68,-0.71,GB,Retail Sales MoM ,2.238046795523906,2.639593908629442,Negative +2022-04-21,1948.2,154.92,-0.38,GB,Gfk Consumer Confidence ,14.285714285714285,14.285714285714285,Negative +2022-04-20,1955.6,139.51,-0.17,CA,Inflation Rate YoY ,1.0638297872340434,1.2422360248447217,Negative +2022-04-19,1959.0,181.44,-1.38,US,Building Permits ,2.043422733077907,2.690582959641253,Negative +2022-04-18,1986.4,138.13,0.58,,,1.097918675666989,1.4835862307477667,Neutral +2022-04-14,1974.9,139.42,-0.49,US,Retail Sales MoM ,0.1978239366963403,0.1982160555004956,Negative +2022-04-13,1984.7,132.03,0.44,US,PPI MoM ,0.5853658536585369,0.78125,Positive +2022-04-12,1976.1,172.39,1.43,US,Core Inflation Rate YoY ,0.17683465959328046,0.3533568904593642,Positive +2022-04-11,1948.2,184.39,0.13,GB,GDP MoM ,0.398406374501992,0.7952286282306164,Positive +2022-04-08,1945.6,142.5,0.4,JP,Consumer Confidence ,1.097918675666989,3.5398230088495657,Positive +2022-04-07,1937.8,122.81,0.76,,,1.097918675666989,1.4835862307477667,Neutral +2022-04-06,1923.1,153.97,-0.23,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Negative +2022-04-05,1927.5,147.26,-0.34,US,Balance of Trade ,0.7923033389926462,1.3620885357548274,Negative +2022-04-04,1934.0,108.44,0.54,,,1.097918675666989,1.4835862307477667,Neutral +2022-04-01,1923.7,135.15,-1.55,US,Non Farm Payrolls ,12.79826464208243,6.502242152466367,Negative +2022-03-31,1954.0,155.3,0.77,US,Personal Income MoM ,0.0,0.1978239366963403,Positive +2022-03-30,1939.0,136.04,1.4,CN,NBS Manufacturing PMI ,0.7968127490039812,0.8032128514056196,Positive +2022-03-29,1912.2,128.05,-1.42,US,JOLTs Job Openings ,2.286598469870197,1.4208679277582843,Negative +2022-03-28,1939.8,181.37,-0.74,,,1.097918675666989,1.4835862307477667,Neutral +2022-03-25,1954.2,147.9,-0.41,GB,Retail Sales MoM ,1.7946161515453645,1.9920318725099602,Negative +2022-03-24,1962.2,181.2,1.29,US,Durable Goods Orders MoM ,3.494347379239465,3.494347379239465,Positive +2022-03-23,1937.3,153.31,0.82,GB,Inflation Rate YoY ,0.5352363960749336,0.17809439002671432,Positive +2022-03-22,1921.5,153.28,-0.41,,,1.097918675666989,1.4835862307477667,Neutral +2022-03-21,1929.5,146.41,0.01,,,1.097918675666989,1.4835862307477667,Neutral +2022-03-18,1929.3,150.88,-0.72,,,1.097918675666989,1.4835862307477667,Neutral +2022-03-17,1943.2,149.83,1.78,US,Building Permits ,0.3822467615204883,0.04238186056368349,Positive +2022-03-16,1909.2,195.46,-1.06,US,Retail Sales MoM ,0.198609731876862,0.7920792079207921,Negative +2022-03-15,1929.7,220.37,-1.59,US,PPI MoM ,0.19665683382497526,0.5888125613346418,Negative +2022-03-14,1960.8,162.2,-1.22,CN,Industrial Production YoY JAN-FEB,6.463195691202872,6.64869721473495,Negative +2022-03-11,1985.0,262.09,-0.77,US,Michigan Consumer Sentiment Prel ,2.784602784602778,3.7489812550937196,Negative +2022-03-10,2000.4,303.27,0.61,US,Core Inflation Rate YoY ,0.0,0.0,Positive +2022-03-09,1988.2,360.35,-2.7,US,JOLTs Job Openings ,2.9153010177678036,4.01508910375926,Negative +2022-03-08,2043.3,447.65,2.37,US,Balance of Trade ,2.957906712172933,6.601042269832083,Positive +2022-03-07,1995.9,372.19,1.49,,,1.097918675666989,1.4835862307477667,Neutral +2022-03-04,1966.6,241.53,1.59,US,Non Farm Payrolls ,51.52919369786839,63.751214771622934,Positive +2022-03-03,1935.9,180.21,0.71,US,Fed Chair Powell Testimony,1.097918675666989,1.4835862307477667,Positive +2022-03-02,1922.3,227.98,-1.11,EA,Inflation Rate YoY Flash ,0.7194244604316552,1.081081081081082,Negative +2022-03-01,1943.8,224.0,2.27,US,ISM Manufacturing PMI ,1.0204081632653086,0.8496176720475787,Positive +2022-02-28,1900.7,249.27,0.69,CN,NBS Manufacturing PMI ,0.5934718100890292,0.39370078740156644,Positive +2022-02-25,1887.6,229.78,-2.01,US,Durable Goods Orders MoM ,1.5625,2.3529411764705883,Negative +2022-02-24,1926.3,423.05,0.83,GB,Gfk Consumer Confidence ,37.2093023255814,48.78048780487805,Positive +2022-02-23,1910.4,154.84,0.16,,,1.097918675666989,1.4835862307477667,Neutral +2022-02-22,1907.4,334.59,0.0,,,1.097918675666989,1.4835862307477667,Neutral +2022-02-21,1907.4,334.59,0.4,GB,Markit/CIPS Manufacturing PMI Flash ,0.17316017316016333,0.5176876617774017,Positive +2022-02-18,1899.8,161.75,-0.12,GB,Retail Sales MoM ,1.749271137026239,1.9455252918287937,Negative +2022-02-17,1902.0,268.55,1.63,US,Building Permits ,5.966945696501396,4.6491789294092545,Positive +2022-02-16,1871.5,141.49,0.82,US,Retail Sales MoM ,3.402646502835539,4.368471035137702,Positive +2022-02-15,1856.2,214.88,-0.71,GB,Claimant Count Change ,13.242784380305597,16.925734024179615,Negative +2022-02-14,1869.4,231.02,1.48,,,1.097918675666989,1.4835862307477667,Neutral +2022-02-11,1842.1,239.09,0.26,US,Michigan Consumer Sentiment Prel ,8.909370199692777,8.909370199692777,Positive +2022-02-10,1837.4,227.46,0.04,US,Core Inflation Rate YoY ,0.1787310098302057,0.5371530886302589,Positive +2022-02-09,1836.6,136.72,0.48,,,1.097918675666989,1.4835862307477667,Neutral +2022-02-08,1827.9,142.41,0.33,US,Balance of Trade ,2.8272894898586323,3.069367710251688,Positive +2022-02-07,1821.8,139.81,0.77,,,1.097918675666989,1.4835862307477667,Neutral +2022-02-04,1807.8,177.71,0.21,US,Non Farm Payrolls ,102.58899676375404,175.50200803212851,Positive +2022-02-03,1804.1,173.72,-0.34,US,ISM Non-Manufacturing PMI ,0.6644518272425225,1.8047579983593132,Negative +2022-02-02,1810.3,123.02,0.49,EA,Inflation Rate YoY Flash ,1.278538812785388,1.0948905109489049,Positive +2022-02-01,1801.5,128.88,0.28,US,ISM Manufacturing PMI ,0.17226528854436077,0.6861063464837025,Positive +2022-01-31,1796.4,139.42,0.55,JP,Consumer Confidence ,1.097918675666989,7.253886010362686,Positive +2022-01-28,1786.6,217.15,-0.36,US,Personal Income MoM ,0.3968253968253968,0.3968253968253968,Negative +2022-01-27,1793.1,196.04,-2.0,US,Durable Goods Orders MoM ,0.8113590263691681,1.415571284125379,Negative +2022-01-26,1829.7,270.03,-1.23,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Negative +2022-01-25,1852.5,197.8,0.59,,,1.097918675666989,1.4835862307477667,Neutral +2022-01-24,1841.7,244.33,0.54,US,Markit Composite PMI Flash ,1.097918675666989,10.87557603686637,Positive +2022-01-21,1831.8,225.25,-0.59,GB,Retail Sales MoM ,6.478578892371996,6.478578892371996,Negative +2022-01-20,1842.6,233.86,-0.03,GB,Gfk Consumer Confidence ,24.242424242424242,5.555555555555555,Negative +2022-01-19,1843.2,318.49,1.6,US,Building Permits ,7.520769567118493,6.66231221423906,Positive +2022-01-18,1814.1,0.34,0.09,GB,Claimant Count Change ,1.097918675666989,18.64623243933588,Positive +2022-01-17,1812.4,362.94,-0.23,,,1.097918675666989,1.4835862307477667,Neutral +2022-01-14,1816.5,174.94,-0.27,US,Retail Sales MoM ,3.873598369011213,4.471544715447155,Negative +2022-01-13,1821.4,215.52,-0.32,CN,Exports YoY ,1.277501774308017,0.14094432699083873,Negative +2022-01-12,1827.3,192.98,0.48,US,Core Inflation Rate YoY ,0.18034265103697042,0.18034265103697042,Positive +2022-01-11,1818.5,184.15,1.1,US,Fed Chair Powell Testimony,1.097918675666989,1.4835862307477667,Positive +2022-01-10,1798.8,173.04,0.08,,,1.097918675666989,1.4835862307477667,Neutral +2022-01-07,1797.4,238.93,0.46,US,Non Farm Payrolls ,67.0,72.32,Positive +2022-01-06,1789.2,238.64,-1.97,US,Balance of Trade ,3.9667306461932292,1.9875776397515457,Negative +2022-01-05,1825.1,173.34,0.58,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Positive +2022-01-04,1814.6,167.71,0.81,US,ISM Manufacturing PMI ,2.1720969089390096,2.5020850708924103,Positive +2022-01-03,1800.1,168.31,-1.56,CN,Caixin Manufacturing PMI ,1.7664376840039224,1.5686274509803866,Negative +2021-12-31,1828.6,106.6,0.8,,,1.097918675666989,1.4835862307477667,Neutral +2021-12-30,1814.1,113.43,0.46,CN,NBS Manufacturing PMI ,0.5923000987166774,0.39292730844794277,Positive +2021-12-29,1805.8,138.69,-0.28,,,1.097918675666989,1.4835862307477667,Neutral +2021-12-28,1810.9,100.54,0.12,,,1.097918675666989,1.4835862307477667,Neutral +2021-12-27,1808.8,84.23,-0.16,,,1.097918675666989,1.4835862307477667,Neutral +2021-12-23,1811.7,104.84,0.53,US,Durable Goods Orders MoM ,1.7291066282420755,2.7027027027027026,Positive +2021-12-22,1802.2,110.41,0.75,,,1.097918675666989,1.4835862307477667,Neutral +2021-12-21,1788.7,134.15,-0.33,,,1.097918675666989,1.4835862307477667,Neutral +2021-12-20,1794.6,105.39,-0.57,,,1.097918675666989,1.4835862307477667,Neutral +2021-12-17,1804.9,156.61,0.37,GB,Retail Sales MoM ,1.1741682974559686,0.78125,Positive +2021-12-16,1798.2,167.78,1.91,US,Building Permits ,2.2399999999999967,3.777061262091206,Positive +2021-12-15,1764.5,161.1,-0.44,US,Retail Sales MoM ,0.9891196834817014,1.3820335636722607,Negative +2021-12-14,1772.3,153.25,-0.89,GB,Claimant Count Change ,1.097918675666989,86.62790697674419,Negative +2021-12-13,1788.3,106.06,0.2,,,1.097918675666989,1.4835862307477667,Neutral +2021-12-10,1784.8,142.0,0.46,US,Core Inflation Rate YoY ,0.0,0.0,Positive +2021-12-09,1776.7,123.97,-0.49,,,1.097918675666989,1.4835862307477667,Neutral +2021-12-08,1785.5,109.69,0.04,US,JOLTs Job Openings ,5.641736331530245,5.357142857142854,Positive +2021-12-07,1784.7,129.89,0.29,US,Balance of Trade ,0.4514672686230206,1.6654049962149802,Positive +2021-12-06,1779.5,104.48,-0.25,CN,Exports YoY ,4.255319148936169,8.695652173913043,Negative +2021-12-03,1783.9,175.18,1.2,US,Non Farm Payrolls ,89.35611038107753,89.35611038107753,Positive +2021-12-02,1762.7,172.72,-1.21,JP,Consumer Confidence ,1.097918675666989,1.9950124688279232,Negative +2021-12-01,1784.3,180.34,0.44,US,ISM Manufacturing PMI ,0.16246953696182198,0.1622060016220623,Positive +2021-11-30,1776.5,242.86,-0.49,US,Fed Chair Powell Testimony,1.097918675666989,1.4835862307477667,Negative +2021-11-29,1785.2,151.37,-0.1,US,Fed Chair Powell Speech ,1.097918675666989,1.4835862307477667,Negative +2021-11-26,1786.9,2.97,-0.07,,,1.097918675666989,1.4835862307477667,Neutral +2021-11-25,1788.1,180.64,0.21,,,1.097918675666989,1.4835862307477667,Neutral +2021-11-24,1784.3,203.24,0.03,US,Durable Goods Orders MoM ,1.4042126379137412,1.6032064128256511,Positive +2021-11-23,1783.8,311.35,-1.25,US,Markit Manufacturing PMI Flash ,0.16792611251049777,0.5046257359125387,Negative +2021-11-22,1806.3,352.86,-2.45,,,1.097918675666989,1.4835862307477667,Neutral +2021-11-19,1851.6,234.08,-0.53,GB,Retail Sales MoM ,0.5923000987166832,0.1970443349753695,Negative +2021-11-18,1861.4,186.06,-0.47,GB,GfK Consumer Confidence ,25.806451612903224,13.793103448275861,Negative +2021-11-17,1870.2,172.42,0.87,US,Building Permits ,0.5597014925373139,0.510322430990495,Positive +2021-11-16,1854.1,220.43,-0.67,US,Retail Sales MoM ,0.5819592628516006,0.9718172983479108,Negative +2021-11-15,1866.6,221.21,-0.1,,,1.097918675666989,1.4835862307477667,Neutral +2021-11-12,1868.5,201.36,0.25,US,JOLTs Job Openings ,1.2696660226331762,3.1386386851146897,Positive +2021-11-11,1863.9,205.31,0.84,EA,ECB Macroeconomic Projections,1.097918675666989,1.4835862307477667,Positive +2021-11-10,1848.3,352.79,0.96,US,Core Inflation Rate YoY ,0.5509641873278243,0.9199632014719408,Positive +2021-11-09,1830.8,224.41,0.15,US,PPI MoM ,0.0,0.0,Positive +2021-11-08,1828.0,200.41,0.62,,,1.097918675666989,1.4835862307477667,Neutral +2021-11-05,1816.8,299.62,1.3,US,Non Farm Payrolls ,16.4969450101833,28.11158798283262,Positive +2021-11-04,1793.5,222.61,1.68,US,Balance of Trade ,0.49875311720698967,7.617817947062629,Positive +2021-11-03,1763.9,257.43,-1.43,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Negative +2021-11-02,1789.4,145.79,-0.36,,,1.097918675666989,1.4835862307477667,Neutral +2021-11-01,1795.8,143.33,0.67,US,ISM Manufacturing PMI ,0.4905968928863404,0.819000819000819,Positive +2021-10-29,1783.9,254.51,-1.04,US,Personal Income MoM ,1.6194331983805668,2.4193548387096775,Negative +2021-10-28,1802.6,220.88,0.21,,,1.097918675666989,1.4835862307477667,Neutral +2021-10-27,1798.8,182.8,0.3,US,Durable Goods Orders MoM ,1.4213197969543145,0.8097165991902834,Positive +2021-10-26,1793.4,197.93,-0.74,,,1.097918675666989,1.4835862307477667,Neutral +2021-10-25,1806.8,153.59,0.58,,,1.097918675666989,1.4835862307477667,Neutral +2021-10-22,1796.3,312.81,0.81,EA,Markit Composite PMI Flash ,1.6289592760181097,1.9873532068654047,Positive +2021-10-21,1781.9,138.73,-0.17,GB,Gfk Consumer Confidence ,6.25,20.0,Negative +2021-10-20,1784.9,174.08,0.81,GB,Inflation Rate YoY ,0.1881467544684856,0.1881467544684856,Positive +2021-10-19,1770.5,166.97,0.27,US,Building Permits ,4.263293511360973,4.7207291423229725,Positive +2021-10-18,1765.7,152.74,-0.15,,,1.097918675666989,1.4835862307477667,Neutral +2021-10-15,1768.3,202.63,-1.65,US,Retail Sales MoM ,1.7910447761194035,1.5904572564612327,Negative +2021-10-14,1797.9,164.65,0.18,,,1.097918675666989,1.4835862307477667,Neutral +2021-10-13,1794.7,299.04,2.01,US,Core Inflation Rate YoY ,0.0,0.0,Positive +2021-10-12,1759.3,168.11,0.21,US,JOLTs Job Openings ,4.346270792344845,3.2465488556140167,Positive +2021-10-11,1755.7,114.77,-0.1,,,1.097918675666989,1.4835862307477667,Neutral +2021-10-08,1757.4,240.37,-0.1,US,Non Farm Payrolls ,88.05755395683454,83.88059701492537,Negative +2021-10-07,1759.2,146.41,-0.15,CA,Ivey PMI s.a ,1.097918675666989,9.14454277286136,Negative +2021-10-06,1761.8,159.22,0.05,,,1.097918675666989,1.4835862307477667,Neutral +2021-10-05,1760.9,151.42,-0.38,US,Balance of Trade ,3.9215686274509762,3.494060097833683,Negative +2021-10-04,1767.6,166.18,0.52,,,1.097918675666989,1.4835862307477667,Neutral +2021-10-01,1758.4,151.2,0.08,US,Personal Income MoM ,0.19900497512437815,0.0,Positive +2021-09-30,1757.0,246.37,1.98,JP,Tankan Large Manufacturers Index,31.25,38.70967741935484,Positive +2021-09-29,1722.9,177.39,-0.84,CN,NBS Manufacturing PMI ,0.9930486593843099,1.5841584158415787,Negative +2021-09-28,1737.5,215.84,-0.83,,,1.097918675666989,1.4835862307477667,Neutral +2021-09-27,1752.0,137.57,0.02,US,Durable Goods Orders MoM ,2.1463414634146343,2.7397260273972597,Positive +2021-09-24,1751.7,151.55,0.11,,,1.097918675666989,1.4835862307477667,Neutral +2021-09-23,1749.8,225.46,-1.63,GB,Gfk Consumer Confidence ,50.0,50.0,Negative +2021-09-22,1778.8,172.35,0.03,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Positive +2021-09-21,1778.2,141.62,0.82,CN,Loan Prime Rate 1Y,1.097918675666989,0.0,Positive +2021-09-20,1763.8,152.45,0.71,,,1.097918675666989,1.4835862307477667,Neutral +2021-09-17,1751.4,183.25,-0.3,,,1.097918675666989,1.4835862307477667,Neutral +2021-09-16,1756.7,255.27,-2.12,US,Retail Sales MoM ,3.003003003003003,2.8000000000000003,Negative +2021-09-15,1794.8,139.3,-0.68,GB,Inflation Rate YoY ,0.5655042412818094,0.5655042412818094,Negative +2021-09-14,1807.1,197.95,0.71,US,Core Inflation Rate YoY ,0.369685767097967,0.5540166204986142,Positive +2021-09-13,1794.4,114.31,0.13,,,1.097918675666989,1.4835862307477667,Neutral +2021-09-10,1792.1,136.25,-0.44,GB,Balance of Trade ,1.097918675666989,53.658536585365866,Negative +2021-09-09,1800.0,154.13,0.36,,,1.097918675666989,1.4835862307477667,Neutral +2021-09-08,1793.5,161.26,-0.22,CA,Ivey PMI s.a ,1.097918675666989,16.260162601626014,Negative +2021-09-07,1797.4,0.02,-0.06,,,1.097918675666989,1.4835862307477667,Neutral +2021-09-06,1798.5,252.48,-1.92,,,1.097918675666989,1.4835862307477667,Neutral +2021-09-03,1833.7,184.98,1.23,US,Non Farm Payrolls ,104.46247464503043,104.46247464503043,Positive +2021-09-02,1811.5,113.03,-0.25,US,Balance of Trade ,1.4285714285714286,0.0,Negative +2021-09-01,1816.0,140.12,-0.12,,,1.097918675666989,1.4835862307477667,Neutral +2021-08-31,1818.1,170.39,0.33,JP,Consumer Confidence ,1.097918675666989,0.8032128514056148,Positive +2021-08-30,1812.2,104.88,-0.4,CN,NBS Manufacturing PMI ,0.19743336623889712,0.3944773175542322,Negative +2021-08-27,1819.5,203.64,1.35,US,Personal Income MoM ,1.7769002961500493,1.7769002961500493,Positive +2021-08-26,1795.2,134.53,0.23,,,1.097918675666989,1.4835862307477667,Neutral +2021-08-25,1791.0,163.46,-0.97,US,Durable Goods Orders MoM ,0.4016064257028113,0.20060180541624875,Negative +2021-08-24,1808.5,114.79,0.12,,,1.097918675666989,1.4835862307477667,Neutral +2021-08-23,1806.3,156.32,1.25,,,1.097918675666989,1.4835862307477667,Neutral +2021-08-20,1784.0,107.97,0.05,,,1.097918675666989,1.4835862307477667,Neutral +2021-08-19,1783.1,151.25,-0.07,GB,Gfk Consumer Confidence ,14.285714285714285,30.76923076923077,Negative +2021-08-18,1784.4,132.73,-0.19,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Negative +2021-08-17,1787.8,144.82,-0.11,US,Retail Sales MoM ,1.6227180527383367,1.6227180527383367,Negative +2021-08-16,1789.8,137.7,0.65,,,1.097918675666989,1.4835862307477667,Neutral +2021-08-13,1778.2,144.81,1.51,,,1.097918675666989,1.4835862307477667,Neutral +2021-08-12,1751.8,137.12,-0.09,GB,Balance of Trade ,1.097918675666989,16.216216216216207,Negative +2021-08-11,1753.3,185.44,1.25,US,Core Inflation Rate YoY ,0.0,0.1839926402943884,Positive +2021-08-10,1731.7,182.56,0.3,,,1.097918675666989,1.4835862307477667,Neutral +2021-08-09,1726.5,289.54,-2.08,,,1.097918675666989,1.4835862307477667,Neutral +2021-08-06,1763.1,323.15,-2.53,US,Non Farm Payrolls ,8.04851157662624,4.663774403470716,Negative +2021-08-05,1808.9,169.84,-0.31,US,Balance of Trade ,2.4226110363391613,1.8791946308724907,Negative +2021-08-04,1814.5,244.68,0.02,,,1.097918675666989,1.4835862307477667,Neutral +2021-08-03,1814.1,103.45,-0.44,,,1.097918675666989,1.4835862307477667,Neutral +2021-08-02,1822.2,159.76,0.28,JP,Consumer Confidence ,1.097918675666989,1.3245033112582782,Positive +2021-07-30,1817.2,157.14,-1.01,US,Personal Income MoM ,0.8016032064128256,0.8016032064128256,Negative +2021-07-29,1835.8,212.07,2.01,,,1.097918675666989,1.4835862307477667,Neutral +2021-07-28,1799.7,209.78,-0.01,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Negative +2021-07-27,1799.8,177.04,0.03,US,Durable Goods Orders MoM ,2.526724975704568,2.142161635832522,Positive +2021-07-26,1799.2,204.55,-0.14,,,1.097918675666989,1.4835862307477667,Neutral +2021-07-23,1801.8,236.76,-0.2,,,1.097918675666989,1.4835862307477667,Neutral +2021-07-22,1805.4,193.32,0.11,GB,Gfk Consumer Confidence ,14.285714285714285,0.0,Positive +2021-07-21,1803.4,218.64,-0.44,,,1.097918675666989,1.4835862307477667,Neutral +2021-07-20,1811.4,221.14,0.12,JP,Balance of Trade ,18.194740582800286,4.284621270084165,Positive +2021-07-19,1809.2,249.68,-0.32,JP,Inflation Rate YoY ,1.097918675666989,0.39920159680638717,Negative +2021-07-16,1815.0,184.66,-0.77,US,Retail Sales MoM ,1.996007984031936,2.197802197802198,Negative +2021-07-15,1829.0,175.61,0.22,GB,Claimant Count Change ,1.097918675666989,4.448246364414031,Positive +2021-07-14,1825.0,229.88,0.83,GB,Inflation Rate YoY ,0.5730659025787972,0.38167938931297746,Positive +2021-07-13,1809.9,242.18,0.22,US,Core Inflation Rate YoY ,0.9216589861751149,1.1070110701107008,Positive +2021-07-12,1805.9,201.42,-0.26,,,1.097918675666989,1.4835862307477667,Neutral +2021-07-09,1810.6,185.58,0.58,GB,Balance of Trade,1.097918675666989,919.9999999999998,Positive +2021-07-08,1800.2,249.34,-0.11,CN,Inflation Rate YoY ,0.390625,0.7797270955165692,Negative +2021-07-07,1802.1,171.08,0.4,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Positive +2021-07-06,1795.0,0.26,0.04,,,1.097918675666989,1.4835862307477667,Neutral +2021-07-05,1794.2,276.6,0.61,,,1.097918675666989,1.4835862307477667,Neutral +2021-07-02,1783.3,205.86,0.37,US,Balance of Trade,0.2824858757062187,0.5641748942171952,Positive +2021-07-01,1776.8,171.44,0.29,,,1.097918675666989,1.4835862307477667,Neutral +2021-06-30,1771.6,177.89,0.45,JP,Consumer Confidence ,1.097918675666989,12.32492997198879,Positive +2021-06-29,1763.6,239.91,-0.96,CN,NBS Manufacturing PMI ,0.1947419668938684,0.0,Negative +2021-06-28,1780.7,160.79,0.16,,,1.097918675666989,1.4835862307477667,Neutral +2021-06-25,1777.8,161.2,0.06,US,Personal Income MoM,1.0471204188481678,2.1052631578947363,Positive +2021-06-24,1776.7,152.23,-0.38,US,Durable Goods Orders MoM,0.9514747859181735,0.5752636625119846,Negative +2021-06-23,1783.4,179.27,0.34,,,1.097918675666989,1.4835862307477667,Neutral +2021-06-22,1777.4,172.75,-0.31,,,1.097918675666989,1.4835862307477667,Neutral +2021-06-21,1782.9,195.52,0.79,,,1.097918675666989,1.4835862307477667,Neutral +2021-06-18,1769.0,264.61,-0.33,,,1.097918675666989,1.4835862307477667,Neutral +2021-06-17,1774.8,385.89,-4.65,JP,Inflation Rate YoY,1.097918675666989,0.4016064257028113,Negative +2021-06-16,1861.4,234.1,0.27,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Positive +2021-06-15,1856.4,155.34,-0.51,US,Retail Sales MoM,1.0214504596527068,2.0325203252032518,Negative +2021-06-14,1865.9,242.3,-0.73,,,1.097918675666989,1.4835862307477667,Neutral +2021-06-11,1879.6,220.46,-0.89,GB,Balance of Trade ,1.097918675666989,148.38709677419354,Negative +2021-06-10,1896.4,250.55,0.05,US,Core Inflation Rate YoY,0.7462686567164172,1.1214953271028034,Positive +2021-06-09,1895.5,147.33,0.06,,,1.097918675666989,1.4835862307477667,Neutral +2021-06-08,1894.4,173.6,-0.23,US,Balance of Trade ,0.14609203798392156,0.14609203798392156,Negative +2021-06-07,1898.8,146.02,0.36,,,1.097918675666989,1.4835862307477667,Neutral +2021-06-04,1892.0,228.83,1.0,US,Non Farm Payrolls,15.041322314049587,8.717948717948717,Positive +2021-06-03,1873.3,278.58,-1.92,,,1.097918675666989,1.4835862307477667,Neutral +2021-06-02,1909.9,166.04,0.26,,,1.097918675666989,1.4835862307477667,Neutral +2021-06-01,1905.0,290.65,0.0,,,1.097918675666989,1.4835862307477667,Neutral +2021-05-31,1905.0,290.65,-0.02,,,1.097918675666989,1.4835862307477667,Neutral +2021-05-28,1905.3,198.14,0.51,,,1.097918675666989,1.4835862307477667,Neutral +2021-05-27,1895.7,35.79,-0.29,US,Durable Goods Orders MoM ,4.0241448692152915,4.0241448692152915,Negative +2021-05-26,1901.2,170.53,0.17,,,1.097918675666989,1.4835862307477667,Neutral +2021-05-25,1898.0,316.67,0.72,,,1.097918675666989,1.4835862307477667,Neutral +2021-05-24,1884.5,183.31,0.42,,,1.097918675666989,1.4835862307477667,Neutral +2021-05-21,1876.7,234.29,-0.28,,,1.097918675666989,1.4835862307477667,Neutral +2021-05-20,1881.9,223.57,0.02,GB,Gfk Consumer Confidence,30.0,45.45454545454545,Positive +2021-05-19,1881.5,398.21,0.72,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Positive +2021-05-18,1868.0,229.02,0.02,GB,Claimant Count Change ,1.097918675666989,735.7798165137615,Positive +2021-05-17,1867.6,267.71,1.6,,,1.097918675666989,1.4835862307477667,Neutral +2021-05-14,1838.1,224.38,0.77,,,1.097918675666989,1.4835862307477667,Neutral +2021-05-13,1824.0,249.93,0.07,,,1.097918675666989,1.4835862307477667,Neutral +2021-05-12,1822.8,339.21,-0.72,US,Core Inflation Rate YoY ,1.3295346628679963,1.520912547528517,Negative +2021-05-11,1836.1,311.1,-0.08,,,1.097918675666989,1.4835862307477667,Neutral +2021-05-10,1837.6,269.71,0.34,,,1.097918675666989,1.4835862307477667,Neutral +2021-05-07,1831.3,367.7,0.86,,,1.097918675666989,1.4835862307477667,Neutral +2021-05-06,1815.7,287.63,1.76,,,1.097918675666989,1.4835862307477667,Neutral +2021-05-05,1784.3,178.81,0.47,,,1.097918675666989,1.4835862307477667,Neutral +2021-05-04,1776.0,246.59,-0.88,US,Balance of Trade ,0.1352265043948537,1.3623978201634876,Negative +2021-05-03,1791.8,204.54,1.36,,,1.097918675666989,1.4835862307477667,Neutral +2021-04-30,1767.7,167.29,-0.03,US,Personal Income MoM ,1.1315417256011284,0.8474576271186449,Negative +2021-04-29,1768.3,231.52,-0.32,CN,NBS Manufacturing PMI ,1.1560693641618522,1.9193857965451053,Negative +2021-04-28,1773.9,198.58,-0.28,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Negative +2021-04-27,1778.8,147.95,-0.07,,,1.097918675666989,1.4835862307477667,Neutral +2021-04-26,1780.1,143.36,0.13,US,Durable Goods Orders MoM ,3.8834951456310676,2.3483365949119372,Positive +2021-04-23,1777.8,175.85,-0.24,,,1.097918675666989,1.4835862307477667,Neutral +2021-04-22,1782.0,163.75,-0.62,GB,Gfk Consumer Confidence ,23.076923076923077,23.076923076923077,Negative +2021-04-21,1793.1,173.97,0.83,GB,Inflation Rate YoY ,0.1970443349753695,0.1970443349753695,Positive +2021-04-20,1778.4,169.04,0.44,GB,Claimant Count Change ,1.097918675666989,173.68094351334577,Positive +2021-04-19,1770.6,180.73,-0.54,CN,Loan Prime Rate 1Y,0.0,0.0,Negative +2021-04-16,1780.2,173.5,0.76,,,1.097918675666989,1.4835862307477667,Neutral +2021-04-15,1766.8,198.14,1.76,US,Retail Sales MoM ,6.7415730337078665,9.273840769903764,Positive +2021-04-14,1736.3,145.26,-0.65,,,1.097918675666989,1.4835862307477667,Neutral +2021-04-13,1747.6,175.59,0.86,US,Core Inflation Rate YoY ,0.19398642095053367,0.0,Positive +2021-04-12,1732.7,125.36,-0.69,,,1.097918675666989,1.4835862307477667,Neutral +2021-04-09,1744.8,171.4,-0.76,,,1.097918675666989,1.4835862307477667,Neutral +2021-04-08,1758.2,144.57,0.95,JP,Consumer Confidence ,1.097918675666989,0.27359781121751414,Positive +2021-04-07,1741.6,122.8,-0.08,US,Balance of Trade ,0.8534850640113717,1.8584703359542494,Negative +2021-04-06,1743.0,152.6,0.82,,,1.097918675666989,1.4835862307477667,Neutral +2021-04-05,1728.8,101.75,0.02,,,1.097918675666989,1.4835862307477667,Neutral +2021-04-01,1728.4,170.43,0.75,,,1.097918675666989,1.4835862307477667,Neutral +2021-03-31,1715.6,210.77,1.76,JP,Tankan Large Manufacturers Index,166.66666666666669,350.0,Positive +2021-03-30,1686.0,225.87,-1.53,US,President Biden Speech on Recovery Package ,1.097918675666989,1.4835862307477667,Negative +2021-03-29,1712.2,135.46,-1.16,,,1.097918675666989,1.4835862307477667,Neutral +2021-03-26,1732.3,172.94,0.42,US,Personal Income MoM ,0.4672897196261686,2.1201413427561855,Positive +2021-03-25,1725.1,226.21,-0.47,,,1.097918675666989,1.4835862307477667,Neutral +2021-03-24,1733.2,186.52,0.47,US,Durable Goods Orders MoM ,3.8114343029087263,4.3999999999999995,Positive +2021-03-23,1725.1,226.2,-0.75,GB,Claimant Count Change ,1.097918675666989,293.4844192634561,Negative +2021-03-22,1738.1,196.31,-0.21,,,1.097918675666989,1.4835862307477667,Neutral +2021-03-19,1741.7,213.28,0.53,,,1.097918675666989,1.4835862307477667,Neutral +2021-03-18,1732.5,251.76,0.31,GB,Gfk Consumer Confidence ,22.857142857142858,22.857142857142858,Positive +2021-03-17,1727.1,220.55,-0.22,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Negative +2021-03-16,1730.9,173.89,0.1,US,Retail Sales MoM ,5.181347150259067,4.979253112033195,Positive +2021-03-15,1729.2,163.05,0.55,,,1.097918675666989,1.4835862307477667,Neutral +2021-03-12,1719.8,232.21,-0.16,GB,Balance of Trade ,1.097918675666989,118.5185185185185,Negative +2021-03-11,1722.6,215.34,0.05,,,1.097918675666989,1.4835862307477667,Neutral +2021-03-10,1721.8,226.89,0.29,US,Core Inflation Rate YoY ,0.1947419668938658,0.1947419668938658,Positive +2021-03-09,1716.9,248.95,2.32,CN,Inflation Rate YoY ,0.4024144869215292,0.20100502512562815,Positive +2021-03-08,1678.0,273.91,-1.21,,,1.097918675666989,1.4835862307477667,Neutral +2021-03-05,1698.5,269.33,-0.13,US,Balance of Trade ,1.039346696362291,1.039346696362291,Negative +2021-03-04,1700.7,277.45,-0.88,JP,Consumer Confidence ,1.097918675666989,9.146341463414624,Negative +2021-03-03,1715.8,255.65,-1.03,,,1.097918675666989,1.4835862307477667,Neutral +2021-03-02,1733.6,235.96,0.62,,,1.097918675666989,1.4835862307477667,Neutral +2021-03-01,1723.0,241.92,-0.34,,,1.097918675666989,1.4835862307477667,Neutral +2021-02-26,1728.8,362.55,-2.62,US,Personal Income MoM ,0.836820083682009,2.5316455696202533,Negative +2021-02-25,1775.4,316.25,-1.25,US,Durable Goods Orders MoM ,4.401913875598087,4.2065009560229445,Negative +2021-02-24,1797.9,224.06,-0.44,,,1.097918675666989,1.4835862307477667,Neutral +2021-02-23,1805.9,191.15,-0.14,GB,Claimant Count Change ,1.097918675666989,1500.0,Negative +2021-02-22,1808.4,221.2,1.74,,,1.097918675666989,1.4835862307477667,Neutral +2021-02-19,1777.4,251.78,0.14,CN,Loan Prime Rate 1Y,1.097918675666989,0.0,Positive +2021-02-18,1775.0,224.77,0.12,GB,Gfk Consumer Confidence ,16.3265306122449,12.5,Positive +2021-02-17,1772.8,257.34,-1.46,US,Retail Sales MoM ,7.894736842105261,8.286252354048964,Negative +2021-02-16,1799.0,355.92,0.0,JP,Balance of Trade ,59.8331346841478,28.184353831850185,Neutral +2021-02-15,1799.0,355.92,-1.33,,,1.097918675666989,1.4835862307477667,Neutral +2021-02-12,1823.2,171.9,-0.2,GB,Balance of Trade ,1.097918675666989,42.5531914893617,Negative +2021-02-11,1826.8,147.02,-0.86,,,1.097918675666989,1.4835862307477667,Neutral +2021-02-10,1842.7,176.44,0.28,US,Core Inflation Rate YoY ,0.194363459669582,0.3883495145631068,Positive +2021-02-09,1837.5,154.39,0.18,CN,Inflation Rate YoY ,0.6018054162487463,0.20100502512562815,Positive +2021-02-08,1834.2,177.56,1.17,,,1.097918675666989,1.4835862307477667,Neutral +2021-02-05,1813.0,205.76,1.22,US,Balance of Trade ,1.3709063214013577,5.014749262536881,Positive +2021-02-04,1791.2,279.62,-2.39,,,1.097918675666989,1.4835862307477667,Neutral +2021-02-03,1835.1,137.23,0.09,,,1.097918675666989,1.4835862307477667,Neutral +2021-02-02,1833.4,236.0,-1.64,,,1.097918675666989,1.4835862307477667,Neutral +2021-02-01,1863.9,242.05,0.74,,,1.097918675666989,1.4835862307477667,Neutral +2021-01-29,1850.3,276.17,0.49,US,Personal Income MoM ,0.99304865938431,0.99304865938431,Positive +2021-01-28,1841.2,277.59,-0.2,,,1.097918675666989,1.4835862307477667,Neutral +2021-01-27,1844.9,195.54,-0.32,US,Durable Goods Orders MoM ,1.3847675568743818,1.188118811881188,Negative +2021-01-26,1850.9,170.26,-0.23,GB,Claimant Count Change ,130.2325581395349,137.5,Negative +2021-01-25,1855.2,211.98,-0.05,,,1.097918675666989,1.4835862307477667,Neutral +2021-01-22,1856.2,249.72,-0.52,,,1.097918675666989,1.4835862307477667,Neutral +2021-01-21,1865.9,196.94,-0.03,GB,Gfk Consumer Confidence ,3.571428571428571,0.0,Negative +2021-01-20,1866.5,274.4,1.33,GB,Inflation Rate YoY ,0.1978239366963403,0.0,Positive +2021-01-19,1842.0,0.4,0.1,US,Treasury Secretary Yellen Senate Confirmation Hearing,1.097918675666989,1.4835862307477667,Positive +2021-01-18,1840.2,331.59,0.56,,,1.097918675666989,1.4835862307477667,Neutral +2021-01-15,1829.9,231.11,-1.16,US,Retail Sales MoM ,1.4098690835850958,1.0090817356205852,Negative +2021-01-14,1851.4,257.66,-0.19,,,1.097918675666989,1.4835862307477667,Neutral +2021-01-13,1854.9,225.99,0.58,US,Core Inflation Rate YoY ,0.0,0.0,Positive +2021-01-12,1844.2,240.66,-0.36,,,1.097918675666989,1.4835862307477667,Neutral +2021-01-11,1850.8,268.36,0.84,,,1.097918675666989,1.4835862307477667,Neutral +2021-01-08,1835.4,443.51,-4.09,US,Non Farm Payrolls ,620.5882352941177,1866.6666666666667,Negative +2021-01-07,1913.6,199.98,0.26,US,Balance of Trade ,4.383975812547228,0.7423904974016333,Positive +2021-01-06,1908.6,366.61,-2.34,JP,Consumer Confidence ,1.097918675666989,9.439528023598818,Negative +2021-01-05,1954.4,201.95,0.4,,,1.097918675666989,1.4835862307477667,Neutral +2021-01-04,1946.6,273.37,2.72,,,1.097918675666989,1.4835862307477667,Neutral +2020-12-31,1895.1,130.63,0.09,,,1.097918675666989,1.4835862307477667,Neutral +2020-12-30,1893.4,133.66,0.56,CN,NBS Manufacturing PMI ,0.19065776930410186,0.7662835249042118,Positive +2020-12-29,1882.9,149.27,0.13,,,1.097918675666989,1.4835862307477667,Neutral +2020-12-28,1880.4,196.76,-0.15,,,1.097918675666989,1.4835862307477667,Neutral +2020-12-24,1883.2,89.41,0.27,,,1.097918675666989,1.4835862307477667,Neutral +2020-12-23,1878.1,162.54,0.42,US,Durable Goods Orders MoM ,0.5911330049261082,0.5911330049261082,Positive +2020-12-22,1870.3,176.02,-0.66,,,1.097918675666989,1.4835862307477667,Neutral +2020-12-21,1882.8,232.05,-0.32,,,1.097918675666989,1.4835862307477667,Neutral +2020-12-18,1888.9,153.23,-0.08,,,1.097918675666989,1.4835862307477667,Neutral +2020-12-17,1890.4,219.87,1.68,GB,GfK Consumer Confidence ,17.857142857142858,14.545454545454545,Positive +2020-12-16,1859.1,199.68,0.2,US,Retail Sales MoM ,1.6227180527383367,1.6227180527383367,Positive +2020-12-15,1855.3,173.61,1.27,GB,Claimant Count Change ,1.097918675666989,71.9832109129066,Positive +2020-12-14,1832.1,168.49,-0.62,,,1.097918675666989,1.4835862307477667,Neutral +2020-12-11,1843.6,153.8,0.34,,,1.097918675666989,1.4835862307477667,Neutral +2020-12-10,1837.4,164.8,-0.06,US,Core Inflation Rate YoY ,0.0,0.0,Negative +2020-12-09,1838.5,219.59,-1.94,,,1.097918675666989,1.4835862307477667,Neutral +2020-12-08,1874.9,151.79,0.48,CN,Inflation Rate YoY ,1.0050251256281406,1.2048192771084338,Positive +2020-12-07,1866.0,209.04,1.41,CA,Ivey PMI s.a ,3.6900369003690034,2.4141132776230214,Positive +2020-12-04,1840.0,171.26,-0.06,US,Balance of Trade ,2.679275019700545,2.9897718332022007,Negative +2020-12-03,1841.1,180.36,0.6,,,1.097918675666989,1.4835862307477667,Neutral +2020-12-02,1830.2,185.32,0.62,JP,Consumer Confidence ,1.097918675666989,2.0679468242245282,Positive +2020-12-01,1818.9,203.65,2.13,,,1.097918675666989,1.4835862307477667,Neutral +2020-11-30,1780.9,242.73,-0.4,EA,Eurogroup Video Conference,1.097918675666989,1.4835862307477667,Negative +2020-11-27,1788.1,282.35,0.0,,,1.097918675666989,1.4835862307477667,Neutral +2020-11-26,1788.1,282.35,-0.96,,,1.097918675666989,1.4835862307477667,Neutral +2020-11-25,1805.5,205.75,0.05,US,Durable Goods Orders MoM ,0.7827788649706457,0.979431929480901,Positive +2020-11-24,1804.6,367.88,-1.81,,,1.097918675666989,1.4835862307477667,Neutral +2020-11-23,1837.8,319.66,-1.85,,,1.097918675666989,1.4835862307477667,Neutral +2020-11-20,1872.4,186.17,0.59,,,1.097918675666989,1.4835862307477667,Neutral +2020-11-19,1861.5,222.35,-0.66,GB,GfK Consumer Confidence ,3.0303030303030303,0.0,Negative +2020-11-18,1873.9,209.0,-0.59,GB,Inflation Rate YoY ,0.1974333662388944,0.0,Negative +2020-11-17,1885.1,160.88,-0.14,US,Retail Sales MoM ,0.3968253968253968,0.198609731876862,Negative +2020-11-16,1887.8,222.94,0.08,,,1.097918675666989,1.4835862307477667,Neutral +2020-11-13,1886.2,162.54,0.69,,,1.097918675666989,1.4835862307477667,Neutral +2020-11-12,1873.3,209.93,0.63,US,Core Inflation Rate YoY ,0.3868471953578333,0.3868471953578333,Positive +2020-11-11,1861.6,215.17,-0.79,,,1.097918675666989,1.4835862307477667,Neutral +2020-11-10,1876.4,264.87,1.19,GB,Claimant Count Change ,752.8301886792452,1827.7777777777778,Positive +2020-11-09,1854.4,496.09,-4.99,CN,Inflation Rate YoY ,0.5923000987166832,0.9852216748768474,Negative +2020-11-06,1951.7,246.78,0.25,US,Non Farm Payrolls ,6.133979015334948,22.28024369016536,Positive +2020-11-05,1946.8,297.51,2.67,,,1.097918675666989,1.4835862307477667,Neutral +2020-11-04,1896.2,293.95,-0.74,US,Balance of Trade ,0.15785319652723193,1.2698412698412653,Negative +2020-11-03,1910.4,171.37,0.95,EA,Eurogroup Video Conference,1.097918675666989,1.4835862307477667,Positive +2020-11-02,1892.5,164.94,0.67,US,Presidential Election,1.097918675666989,1.4835862307477667,Positive +2020-10-30,1879.9,213.17,0.64,US,Personal Income MoM ,0.9871668311944718,0.9871668311944718,Positive +2020-10-29,1868.0,225.16,-0.6,JP,Consumer Confidence ,1.097918675666989,3.458213256484137,Negative +2020-10-28,1879.2,297.09,-1.71,,,1.097918675666989,1.4835862307477667,Neutral +2020-10-27,1911.9,153.3,0.33,US,Durable Goods Orders MoM ,2.7343749999999996,2.932551319648094,Positive +2020-10-26,1905.7,166.31,0.03,,,1.097918675666989,1.4835862307477667,Neutral +2020-10-23,1905.2,172.96,0.03,,,1.097918675666989,1.4835862307477667,Neutral +2020-10-22,1904.6,215.58,-1.29,GB,Gfk Consumer Confidence ,10.344827586206897,17.857142857142858,Negative +2020-10-21,1929.5,201.27,0.74,GB,Inflation Rate YoY ,0.0,0.1982160555004956,Positive +2020-10-20,1915.4,163.91,0.19,,,1.097918675666989,1.4835862307477667,Neutral +2020-10-19,1911.7,159.85,0.28,CN,Loan Prime Rate 1Y,0.0,0.0,Positive +2020-10-16,1906.4,146.91,-0.13,US,Retail Sales MoM ,2.3391812865497075,2.7343749999999996,Negative +2020-10-15,1908.9,213.57,0.08,,,1.097918675666989,1.4835862307477667,Neutral +2020-10-14,1907.3,188.3,0.67,CN,Inflation Rate YoY ,0.19323671497584494,0.5785920925747347,Positive +2020-10-13,1894.6,267.54,-1.78,US,Core Inflation Rate YoY ,0.19323671497584494,0.0,Negative +2020-10-12,1928.9,157.21,0.14,,,1.097918675666989,1.4835862307477667,Neutral +2020-10-09,1926.2,229.85,1.64,GB,Balance of Trade ,1.097918675666989,53.333333333333336,Positive +2020-10-08,1895.1,185.45,0.23,,,1.097918675666989,1.4835862307477667,Neutral +2020-10-07,1890.8,188.59,-0.94,CA,Ivey PMI s.a ,1.097918675666989,22.222222222222225,Negative +2020-10-06,1908.8,219.44,-0.59,US,Balance of Trade ,1.5128593040847202,0.9049773755656023,Negative +2020-10-05,1920.1,177.59,0.66,EA,Eurogroup Video Conference,1.097918675666989,1.4835862307477667,Positive +2020-10-02,1907.6,212.73,-0.45,US,Non Farm Payrolls ,25.0,32.21306277742549,Negative +2020-10-01,1916.3,262.09,1.1,US,Personal Income MoM ,0.632244467860906,1.4690451206715633,Positive +2020-09-30,1895.5,259.87,-0.4,JP,Tankan Large Manufacturers Index,16.3265306122449,3.8461538461538463,Negative +2020-09-29,1903.2,217.8,1.11,CN,NBS Manufacturing PMI ,0.5785920925747293,0.19249278152069568,Positive +2020-09-28,1882.3,235.92,0.86,,,1.097918675666989,1.4835862307477667,Neutral +2020-09-25,1866.3,230.86,-0.56,US,Durable Goods Orders MoM ,2.1589793915603535,3.125,Negative +2020-09-24,1876.9,345.04,0.45,GB,Winter Economy Plan,1.097918675666989,1.4835862307477667,Positive +2020-09-23,1868.4,411.56,-2.05,,,1.097918675666989,1.4835862307477667,Neutral +2020-09-22,1907.6,282.71,-0.16,,,1.097918675666989,1.4835862307477667,Neutral +2020-09-21,1910.6,386.67,-2.62,,,1.097918675666989,1.4835862307477667,Neutral +2020-09-18,1962.1,176.07,0.63,,,1.097918675666989,1.4835862307477667,Neutral +2020-09-17,1949.9,273.14,-1.05,JP,Inflation Rate YoY ,1.097918675666989,0.19940179461615157,Negative +2020-09-16,1970.5,298.39,0.22,US,Retail Sales MoM ,0.7874015748031495,0.7874015748031495,Positive +2020-09-15,1966.2,239.54,0.13,GB,Claimant Count Change ,30.108757870635372,36.11774065234686,Positive +2020-09-14,1963.7,200.09,0.81,,,1.097918675666989,1.4835862307477667,Neutral +2020-09-11,1947.9,205.23,-0.83,US,Core Inflation Rate YoY ,0.1936108422071638,0.38759689922480656,Negative +2020-09-10,1964.3,271.48,0.48,,,1.097918675666989,1.4835862307477667,Neutral +2020-09-09,1954.9,227.18,0.79,,,1.097918675666989,1.4835862307477667,Neutral +2020-09-08,1939.5,0.04,-0.19,CN,Inflation Rate YoY ,0.0,0.19065776930409933,Negative +2020-09-07,1943.2,416.01,0.46,,,1.097918675666989,1.4835862307477667,Neutral +2020-09-04,1934.3,304.74,-0.18,US,Non Farm Payrolls ,2.092352092352092,8.315863032844165,Negative +2020-09-03,1937.8,303.03,-0.35,US,Balance of Trade ,9.286898839137647,7.565789473684213,Negative +2020-09-02,1944.7,332.59,-1.73,,,1.097918675666989,1.4835862307477667,Neutral +2020-09-01,1978.9,304.89,0.02,,,1.097918675666989,1.4835862307477667,Neutral +2020-08-31,1978.6,245.11,0.19,JP,Consumer Confidence ,1.097918675666989,1.0118043844856686,Positive +2020-08-28,1974.9,334.1,2.19,US,Personal Income MoM ,1.1976047904191618,1.6,Positive +2020-08-27,1932.6,467.17,-1.02,,,1.097918675666989,1.4835862307477667,Neutral +2020-08-26,1952.5,342.21,1.53,US,Durable Goods Orders MoM ,11.94805194805195,12.68462206776716,Positive +2020-08-25,1923.1,274.11,-0.83,,,1.097918675666989,1.4835862307477667,Neutral +2020-08-24,1939.2,286.26,-0.4,,,1.097918675666989,1.4835862307477667,Neutral +2020-08-21,1947.0,355.07,0.03,,,1.097918675666989,1.4835862307477667,Neutral +2020-08-20,1946.5,383.34,-1.21,GB,Gfk Consumer Confidence ,7.8431372549019605,12.0,Negative +2020-08-19,1970.3,443.26,-2.13,GB,Inflation Rate YoY ,0.7874015748031495,0.5899705014749264,Negative +2020-08-18,2013.1,361.48,0.72,JP,Balance of Trade ,274.46153846153845,245.0651769087523,Positive +2020-08-17,1998.7,289.44,2.51,,,1.097918675666989,1.4835862307477667,Neutral +2020-08-14,1949.8,241.8,-1.05,US,Retail Sales MoM ,1.3579049466537343,1.550387596899225,Negative +2020-08-13,1970.4,349.89,1.1,,,1.097918675666989,1.4835862307477667,Neutral +2020-08-12,1949.0,459.84,0.14,US,Core Inflation Rate YoY ,0.9737098344693284,1.1695906432748537,Positive +2020-08-11,1946.3,565.0,-4.58,GB,Claimant Count Change ,160.1518026565465,178.08764940239044,Negative +2020-08-10,2039.7,251.31,0.58,,,1.097918675666989,1.4835862307477667,Neutral +2020-08-07,2028.0,398.13,-2.0,US,Non Farm Payrolls ,9.690844233055886,8.451536643026005,Negative +2020-08-06,2069.4,312.76,0.98,,,1.097918675666989,1.4835862307477667,Neutral +2020-08-05,2049.3,366.38,1.4,US,Balance of Trade ,1.2024048096192412,0.0,Positive +2020-08-04,2021.0,274.42,1.75,,,1.097918675666989,1.4835862307477667,Neutral +2020-08-03,1986.3,178.75,0.02,,,1.097918675666989,1.4835862307477667,Neutral +2020-07-31,1985.9,279.32,0.97,US,Personal Income MoM ,1.2195121951219512,1.6227180527383367,Positive +2020-07-30,1966.8,271.38,0.69,CN,NBS Manufacturing PMI ,0.7782101167315146,0.19398642095053625,Positive +2020-07-29,1953.4,209.84,0.45,,,1.097918675666989,1.4835862307477667,Neutral +2020-07-28,1944.6,434.45,0.7,,,1.097918675666989,1.4835862307477667,Neutral +2020-07-27,1931.0,428.23,1.77,US,Durable Goods Orders MoM ,0.5249343832020977,4.096170970614424,Positive +2020-07-24,1897.5,300.17,0.4,,,1.097918675666989,1.4835862307477667,Neutral +2020-07-23,1890.0,418.75,1.34,GB,Gfk Consumer Confidence ,3.8461538461538463,3.8461538461538463,Positive +2020-07-22,1865.1,382.23,1.15,CA,Inflation Rate YoY ,0.7920792079207921,0.7920792079207921,Positive +2020-07-21,1843.9,271.09,1.46,,,1.097918675666989,1.4835862307477667,Neutral +2020-07-20,1817.4,177.74,0.41,JP,Inflation Rate YoY ,1.097918675666989,0.0,Positive +2020-07-17,1810.0,167.01,0.54,,,1.097918675666989,1.4835862307477667,Neutral +2020-07-16,1800.3,196.57,-0.74,US,Retail Sales MoM ,4.444444444444443,5.357142857142856,Negative +2020-07-15,1813.8,183.06,0.02,GB,Inflation Rate YoY ,0.39603960396039606,0.0,Positive +2020-07-14,1813.4,253.21,-0.04,US,Core Inflation Rate YoY ,0.19550342130987308,0.0,Negative +2020-07-13,1814.1,230.4,0.68,,,1.097918675666989,1.4835862307477667,Neutral +2020-07-10,1801.9,223.83,-0.11,,,1.097918675666989,1.4835862307477667,Neutral +2020-07-09,1803.8,283.37,-0.92,EA,Eurogroup Meeting,1.097918675666989,1.4835862307477667,Negative +2020-07-08,1820.6,247.5,0.59,GB,Supplementary Budget,1.097918675666989,1.4835862307477667,Positive +2020-07-07,1809.9,221.73,0.61,CA,Ivey PMI s.a ,1.097918675666989,29.745596868884544,Positive +2020-07-06,1799.0,0.11,0.31,,,1.097918675666989,1.4835862307477667,Neutral +2020-07-03,1793.5,184.65,0.2,,,1.097918675666989,1.4835862307477667,Neutral +2020-07-02,1790.0,186.31,0.57,US,Balance of Trade,3.001876172607883,3.001876172607883,Positive +2020-07-01,1779.9,263.25,-1.14,JP,Consumer Confidence ,1.097918675666989,5.387205387205392,Negative +2020-06-30,1800.5,199.42,1.08,JP,Tankan Large Manufacturers Index,9.375,0.0,Positive +2020-06-29,1781.2,130.51,0.05,CN,NBS Manufacturing PMI ,0.9775171065493646,1.3712047012732531,Positive +2020-06-26,1780.3,201.23,0.55,US,Personal Income MoM,4.0089086859688186,3.1042128603104207,Positive +2020-06-25,1770.6,152.2,-0.25,US,Durable Goods Orders MoM,7.734806629834255,11.74577634754626,Negative +2020-06-24,1775.1,239.53,-0.39,,,1.097918675666989,1.4835862307477667,Neutral +2020-06-23,1782.0,194.68,0.88,,,1.097918675666989,1.4835862307477667,Neutral +2020-06-22,1766.4,228.68,0.76,,,1.097918675666989,1.4835862307477667,Neutral +2020-06-19,1753.0,181.15,1.27,,,1.097918675666989,1.4835862307477667,Neutral +2020-06-18,1731.1,155.91,-0.26,JP,Inflation Rate YoY,0.0,0.0,Negative +2020-06-17,1735.6,140.07,-0.05,GB,Inflation Rate YoY,0.0,0.0,Negative +2020-06-16,1736.5,182.42,0.54,US,Retail Sales MoM,15.433571996817816,16.293929712460063,Positive +2020-06-15,1727.2,200.23,-0.58,,,1.097918675666989,1.4835862307477667,Neutral +2020-06-12,1737.3,151.4,-0.14,GB,Balance of Trade ,1.097918675666989,266.25766871165644,Negative +2020-06-11,1739.8,205.35,1.11,,,1.097918675666989,1.4835862307477667,Neutral +2020-06-10,1720.7,198.76,-0.07,US,Core Inflation Rate YoY,0.19512195121951204,0.0,Negative +2020-06-09,1721.9,182.91,0.99,CN,Inflation Rate YoY,0.5708848715509038,0.5708848715509038,Positive +2020-06-08,1705.1,154.77,1.31,,,1.097918675666989,1.4835862307477667,Neutral +2020-06-05,1683.0,273.68,-2.57,US,Non Farm Payrolls,382.8415300546448,357.8301886792453,Negative +2020-06-04,1727.4,198.72,1.33,US,Balance of Trade ,0.8213552361396275,9.542356377799415,Positive +2020-06-03,1704.8,256.52,-1.68,,,1.097918675666989,1.4835862307477667,Neutral +2020-06-02,1734.0,175.35,-0.93,,,1.097918675666989,1.4835862307477667,Neutral +2020-06-01,1750.3,146.13,-0.08,,,1.097918675666989,1.4835862307477667,Neutral +2020-05-29,1751.7,150.11,1.35,,,1.097918675666989,1.4835862307477667,Neutral +2020-05-28,1728.3,164.82,1.03,US,Durable Goods Orders MoM ,5.642633228840131,5.642633228840131,Positive +2020-05-27,1710.7,137.42,-0.38,,,1.097918675666989,1.4835862307477667,Neutral +2020-05-26,1717.3,3.44,0.69,,,1.097918675666989,1.4835862307477667,Neutral +2020-05-25,1705.6,313.17,-1.72,,,1.097918675666989,1.4835862307477667,Neutral +2020-05-22,1735.5,196.82,0.79,,,1.097918675666989,1.4835862307477667,Neutral +2020-05-21,1721.9,238.74,-1.72,GB,Gfk Consumer Confidence,1.097918675666989,21.333333333333336,Negative +2020-05-20,1752.1,184.46,0.37,GB,Inflation Rate YoY ,0.19665683382497526,0.0,Positive +2020-05-19,1745.6,185.26,0.65,GB,Claimant Count Change ,23.46805736636245,27.396351575456052,Positive +2020-05-18,1734.4,271.47,-1.25,,,1.097918675666989,1.4835862307477667,Neutral +2020-05-15,1756.3,200.18,0.88,,,1.097918675666989,1.4835862307477667,Neutral +2020-05-14,1740.9,212.91,1.43,,,1.097918675666989,1.4835862307477667,Neutral +2020-05-13,1716.4,211.61,0.56,US,Retail Sales MoM ,12.290502793296094,12.813370473537608,Positive +2020-05-12,1706.8,198.07,0.52,US,Core Inflation Rate YoY ,0.5819592628516006,0.3883495145631068,Positive +2020-05-11,1698.0,202.17,-0.93,,,1.097918675666989,1.4835862307477667,Neutral +2020-05-08,1713.9,232.81,-0.69,,,1.097918675666989,1.4835862307477667,Neutral +2020-05-07,1725.8,250.7,2.21,US,Non Farm Payrolls ,7.058989623285254,6.055015492324794,Positive +2020-05-06,1688.5,203.37,-1.29,,,1.097918675666989,1.4835862307477667,Neutral +2020-05-05,1710.6,184.73,-0.16,US,Balance of Trade ,0.9153318077803171,0.4566210045662003,Negative +2020-05-04,1713.3,148.73,0.73,,,1.097918675666989,1.4835862307477667,Neutral +2020-05-01,1700.9,168.02,0.4,,,1.097918675666989,1.4835862307477667,Neutral +2020-04-30,1694.2,234.53,-1.12,US,Personal Income MoM ,1.0362694300518136,2.0618556701030926,Negative +2020-04-29,1713.4,159.6,-0.51,EA,Business Confidence ,1.097918675666989,55.60975609756099,Negative +2020-04-28,1722.2,171.34,-0.09,,,1.097918675666989,1.4835862307477667,Neutral +2020-04-27,1723.8,146.64,-0.68,,,1.097918675666989,1.4835862307477667,Neutral +2020-04-24,1735.6,180.24,-0.56,US,Durable Goods Orders MoM ,6.784260515603798,6.521739130434781,Negative +2020-04-23,1745.4,201.88,0.41,GB,Gfk Consumer Confidence ,16.43835616438356,30.37974683544304,Positive +2020-04-22,1738.3,193.73,2.99,GB,Inflation Rate YoY ,0.0,0.38910505836575876,Positive +2020-04-21,1687.8,248.63,-1.37,GB,Claimant Count Change ,173.00743889479278,182.1879382889201,Negative +2020-04-20,1711.2,186.91,0.73,,,1.097918675666989,1.4835862307477667,Neutral +2020-04-17,1698.8,227.07,-1.9,,,1.097918675666989,1.4835862307477667,Neutral +2020-04-16,1731.7,204.23,-0.49,,,1.097918675666989,1.4835862307477667,Neutral +2020-04-15,1740.2,186.7,-1.62,US,Retail Sales MoM ,1.6806722689075613,5.188679245283017,Negative +2020-04-14,1768.9,241.19,0.43,,,1.097918675666989,1.4835862307477667,Neutral +2020-04-13,1761.4,166.89,0.49,,,1.097918675666989,1.4835862307477667,Neutral +2020-04-09,1752.8,218.8,4.07,EA,Eurogroup Meeting,1.097918675666989,1.4835862307477667,Positive +2020-04-08,1684.3,125.33,0.04,,,1.097918675666989,1.4835862307477667,Neutral +2020-04-07,1683.7,204.5,-0.6,EA,Eurogroup Meeting,1.097918675666989,1.4835862307477667,Negative +2020-04-06,1693.9,192.75,2.93,JP,Consumer Confidence ,1.097918675666989,17.17612809315866,Positive +2020-04-03,1645.7,139.61,0.49,US,Non Farm Payrolls ,150.25,129.6470588235294,Positive +2020-04-02,1637.7,167.71,2.91,US,Balance of Trade ,0.25348542458808976,2.3106546854942196,Positive +2020-04-01,1591.4,164.48,-0.33,,,1.097918675666989,1.4835862307477667,Neutral +2020-03-31,1596.6,176.55,-2.84,JP,Tankan Large Manufacturers Index,23.52941176470588,42.10526315789473,Negative +2020-03-30,1643.2,157.37,-0.66,EA,Business Confidence ,68.65671641791047,533.3333333333333,Negative +2020-03-27,1654.1,159.26,0.18,US,Personal Income MoM ,0.39603960396039606,0.5946481665014867,Positive +2020-03-26,1651.2,215.97,1.09,,,1.097918675666989,1.4835862307477667,Neutral +2020-03-25,1633.4,254.19,-1.65,US,Durable Goods Orders MoM ,3.9840637450199203,3.7810945273631846,Negative +2020-03-24,1660.8,418.78,5.95,CA,Parliamentary Debate & Vote on Coronavirus Aid Package,1.097918675666989,1.4835862307477667,Positive +2020-03-23,1567.6,362.07,5.59,,,1.097918675666989,1.4835862307477667,Neutral +2020-03-20,1484.6,269.97,0.36,,,1.097918675666989,1.4835862307477667,Neutral +2020-03-19,1479.3,325.29,0.09,CN,Loan Prime Rate 1Y,1.097918675666989,0.18518518518518534,Positive +2020-03-18,1477.9,435.19,-3.14,JP,Inflation Rate YoY ,0.7905138339920948,0.1982160555004956,Negative +2020-03-17,1525.8,434.51,2.64,US,Retail Sales MoM ,1.4042126379137412,1.2048192771084338,Positive +2020-03-16,1486.5,565.98,-1.99,,,1.097918675666989,1.4835862307477667,Neutral +2020-03-13,1516.7,551.05,-4.63,US,President Trump Statement on Coronavirus,1.097918675666989,1.4835862307477667,Negative +2020-03-12,1590.3,605.72,-3.17,,,1.097918675666989,1.4835862307477667,Neutral +2020-03-11,1642.3,404.35,-1.08,US,Core Inflation Rate YoY ,0.1910219675262657,0.1910219675262657,Negative +2020-03-10,1660.3,385.48,-0.92,,,1.097918675666989,1.4835862307477667,Neutral +2020-03-09,1675.7,504.16,0.2,CN,Inflation Rate YoY ,0.0,0.18132366273798747,Positive +2020-03-06,1672.4,659.63,0.26,US,Balance of Trade ,1.7699115044247882,1.109877913429523,Positive +2020-03-05,1668.0,363.0,1.52,,,1.097918675666989,1.4835862307477667,Neutral +2020-03-04,1643.0,313.34,-0.09,,,1.097918675666989,1.4835862307477667,Neutral +2020-03-03,1644.4,466.53,3.11,US,Fed Press Conference,1.097918675666989,1.4835862307477667,Positive +2020-03-02,1594.8,443.53,1.79,,,1.097918675666989,1.4835862307477667,Neutral +2020-02-28,1566.7,745.84,-4.61,US,Personal Income MoM ,0.5946481665014867,0.5946481665014867,Negative +2020-02-27,1642.5,573.29,-0.04,US,Durable Goods Orders MoM ,2.644964394710071,3.6809815950920246,Negative +2020-02-26,1643.1,531.9,-0.42,US,President Trump Speech ,1.097918675666989,1.4835862307477667,Negative +2020-02-25,1650.0,672.76,-1.59,,,1.097918675666989,1.4835862307477667,Neutral +2020-02-24,1676.6,680.82,1.69,,,1.097918675666989,1.4835862307477667,Neutral +2020-02-21,1648.8,489.19,1.75,,,1.097918675666989,1.4835862307477667,Neutral +2020-02-20,1620.5,403.04,0.54,JP,Inflation Rate YoY ,0.0,0.0,Positive +2020-02-19,1611.8,307.89,0.51,GB,Inflation Rate YoY ,0.3868471953578333,0.775193798449612,Positive +2020-02-18,1603.6,414.24,0.0,GB,Claimant Count Change ,117.5257731958763,88.37209302325581,Neutral +2020-02-17,1603.6,414.24,1.08,,,1.097918675666989,1.4835862307477667,Neutral +2020-02-14,1586.4,227.11,0.48,US,Retail Sales MoM ,0.0,0.0,Positive +2020-02-13,1578.8,276.25,0.46,US,Core Inflation Rate YoY ,0.1913875598086126,0.0,Positive +2020-02-12,1571.6,189.55,0.1,,,1.097918675666989,1.4835862307477667,Neutral +2020-02-11,1570.1,231.83,-0.6,GB,Balance of Trade ,1.097918675666989,337.3671300081766,Negative +2020-02-10,1579.5,191.75,0.39,,,1.097918675666989,1.4835862307477667,Neutral +2020-02-07,1573.4,286.42,0.22,US,Non Farm Payrolls ,33.67875647668394,41.17647058823529,Positive +2020-02-06,1570.0,229.0,0.46,,,1.097918675666989,1.4835862307477667,Neutral +2020-02-05,1562.8,306.05,0.47,US,Balance of Trade ,1.4568158168574314,0.20639834881321242,Positive +2020-02-04,1555.5,349.0,-1.7,,,1.097918675666989,1.4835862307477667,Neutral +2020-02-03,1582.4,320.6,-0.35,RU,Full Year GDP Growth 2019,1.097918675666989,1.4835862307477667,Negative +2020-01-31,1587.9,343.37,-0.08,US,Personal Income MoM ,0.19900497512437815,0.3976143141153082,Negative +2020-01-30,1589.2,382.6,1.2,EA,Business Confidence ,13.793103448275865,16.94915254237289,Positive +2020-01-29,1570.4,251.27,0.04,US,USMCA Trade Deal Signature,1.097918675666989,1.4835862307477667,Positive +2020-01-28,1569.8,378.01,-0.48,US,Durable Goods Orders MoM ,3.8910505836575875,3.4951456310679614,Negative +2020-01-27,1577.4,398.06,0.35,,,1.097918675666989,1.4835862307477667,Neutral +2020-01-24,1571.9,427.14,0.42,,,1.097918675666989,1.4835862307477667,Neutral +2020-01-23,1565.4,361.03,0.56,JP,Inflation Rate YoY ,0.7905138339920948,0.5923000987166832,Positive +2020-01-22,1556.7,286.08,-0.26,JP,Balance of Trade ,1.658374792703151,20.689655172413794,Negative +2020-01-21,1560.8,2.22,0.19,GB,Claimant Count Change ,40.00000000000001,52.98329355608592,Positive +2020-01-20,1557.9,462.62,-0.15,,,1.097918675666989,1.4835862307477667,Neutral +2020-01-17,1560.3,264.93,0.63,,,1.097918675666989,1.4835862307477667,Neutral +2020-01-16,1550.5,260.05,-0.23,US,Retail Sales MoM ,0.0,0.0,Negative +2020-01-15,1554.0,310.07,0.61,US,US-China Phase 1 Trade Deal Signature,1.097918675666989,1.4835862307477667,Positive +2020-01-14,1544.6,340.91,-0.39,US,Core Inflation Rate YoY ,0.0,0.1913875598086126,Negative +2020-01-13,1550.6,311.73,-0.61,GB,Balance of Trade ,1.097918675666989,790.1639344262295,Negative +2020-01-10,1560.1,344.34,0.37,US,Non Farm Payrolls ,12.258064516129032,12.861736334405144,Positive +2020-01-09,1554.3,372.88,-0.38,,,1.097918675666989,1.4835862307477667,Neutral +2020-01-08,1560.2,813.41,-0.9,EA,Business Confidence ,30.508474576271187,46.15384615384615,Negative +2020-01-07,1574.3,435.87,0.35,US,Balance of Trade ,1.629802095459827,0.23501762632197754,Positive +2020-01-06,1568.8,558.97,1.06,,,1.097918675666989,1.4835862307477667,Neutral +2020-01-03,1552.4,436.74,1.59,US,FOMC Minutes,1.097918675666989,1.4835862307477667,Positive +2020-01-02,1528.1,270.55,0.33,,,1.097918675666989,1.4835862307477667,Neutral +2019-12-31,1523.1,220.85,0.3,,,1.097918675666989,1.4835862307477667,Neutral +2019-12-30,1518.6,178.72,0.03,CN,NBS Manufacturing PMI ,0.19743336623889712,0.19704433497535825,Positive +2019-12-27,1518.1,204.99,0.24,,,1.097918675666989,1.4835862307477667,Neutral +2019-12-26,1514.4,216.61,0.64,,,1.097918675666989,1.4835862307477667,Neutral +2019-12-24,1504.8,183.68,1.08,,,1.097918675666989,1.4835862307477667,Neutral +2019-12-23,1488.7,162.45,0.53,US,Durable Goods Orders MoM ,7.035175879396986,6.256306760847628,Positive +2019-12-20,1480.9,140.77,-0.24,US,Personal Income MoM ,0.3968253968253968,0.595829195630586,Negative +2019-12-19,1484.4,201.19,0.39,GB,GfK Consumer Confidence ,25.0,9.090909090909092,Positive +2019-12-18,1478.7,197.97,-0.13,GB,Inflation Rate YoY ,0.194363459669582,0.194363459669582,Negative +2019-12-17,1480.6,173.25,0.01,GB,Claimant Count Change ,15.837937384898716,0.6802721088435351,Positive +2019-12-16,1480.5,165.85,-0.05,,,1.097918675666989,1.4835862307477667,Neutral +2019-12-13,1481.2,356.68,0.6,US,Retail Sales MoM ,0.595829195630586,0.19900497512437815,Positive +2019-12-12,1472.3,409.86,-0.18,JP,Tankan Large Manufacturers Index,133.33333333333331,133.33333333333331,Negative +2019-12-11,1475.0,251.73,0.47,US,Core Inflation Rate YoY ,0.0,0.0,Positive +2019-12-10,1468.1,228.83,0.22,GB,Balance of Trade ,1.097918675666989,60.91794158553546,Positive +2019-12-09,1464.9,177.22,-0.01,CN,Inflation Rate YoY ,0.5519779208831639,0.3676470588235297,Negative +2019-12-06,1465.1,317.32,-1.21,US,Non Farm Payrolls ,38.47874720357942,41.17647058823529,Negative +2019-12-05,1483.1,240.01,0.2,US,Balance of Trade ,3.1612223393045307,1.908801696712616,Positive +2019-12-04,1480.2,319.73,-0.28,,,1.097918675666989,1.4835862307477667,Neutral +2019-12-03,1484.4,400.9,1.03,,,1.097918675666989,1.4835862307477667,Neutral +2019-12-02,1469.2,316.58,-0.24,,,1.097918675666989,1.4835862307477667,Neutral +2019-11-29,1472.7,272.34,0.0,JP,Consumer Confidence ,8.78828229027964,7.133421400264208,Neutral +2019-11-28,1472.7,272.34,1.33,EA,Business Confidence ,28.57142857142857,22.95081967213115,Positive +2019-11-27,1453.4,88.36,-0.47,US,Durable Goods Orders MoM ,2.80561122244489,2.4,Negative +2019-11-26,1460.3,346.36,0.23,,,1.097918675666989,1.4835862307477667,Neutral +2019-11-25,1456.9,298.71,-0.46,,,1.097918675666989,1.4835862307477667,Neutral +2019-11-22,1463.6,320.5,0.0,,,1.097918675666989,1.4835862307477667,Neutral +2019-11-21,1463.6,388.34,-0.72,JP,Inflation Rate YoY ,0.19900497512437815,0.3976143141153082,Negative +2019-11-20,1474.2,369.97,-0.01,CA,Inflation Rate YoY ,0.0,0.19249278152069316,Negative +2019-11-19,1474.3,307.86,0.16,JP,Balance of Trade ,177.7012214218603,169.99578592498946,Positive +2019-11-18,1471.9,331.24,0.23,,,1.097918675666989,1.4835862307477667,Neutral +2019-11-15,1468.5,251.21,-0.33,US,Retail Sales MoM ,0.19900497512437815,0.0,Negative +2019-11-14,1473.4,317.4,0.69,,,1.097918675666989,1.4835862307477667,Neutral +2019-11-13,1463.3,352.33,0.66,US,Core Inflation Rate YoY ,0.1910219675262657,0.1910219675262657,Positive +2019-11-12,1453.7,429.61,-0.23,GB,Claimant Count Change ,42.31464737793852,19.672131147540984,Negative +2019-11-11,1457.1,310.16,-0.4,GB,Balance of Trade ,1.097918675666989,50.87719298245612,Negative +2019-11-08,1462.9,447.07,-0.24,CN,Inflation Rate YoY ,0.9337068160597569,1.4981273408239701,Negative +2019-11-07,1466.4,674.98,-1.79,,,1.097918675666989,1.4835862307477667,Neutral +2019-11-06,1493.1,313.72,0.63,CA,Ivey PMI s.a ,189.60000000000002,9.393346379647744,Positive +2019-11-05,1483.7,593.62,-1.81,US,Balance of Trade ,0.0,0.966183574879227,Negative +2019-11-04,1511.1,260.2,-0.02,,,1.097918675666989,1.4835862307477667,Neutral +2019-11-01,1511.4,380.99,-0.22,US,Non Farm Payrolls ,35.77981651376147,24.45414847161572,Negative +2019-10-31,1514.8,390.01,1.21,US,Personal Income MoM ,0.0,0.0,Positive +2019-10-30,1496.7,353.64,0.4,EA,Business Confidence ,17.5438596491228,69.47368421052632,Positive +2019-10-29,1490.7,291.98,-0.34,,,1.097918675666989,1.4835862307477667,Neutral +2019-10-28,1495.8,318.13,-0.63,,,1.097918675666989,1.4835862307477667,Neutral +2019-10-25,1505.3,368.74,0.04,,,1.097918675666989,1.4835862307477667,Neutral +2019-10-24,1504.7,305.01,0.6,US,Durable Goods Orders MoM ,0.6116207951070335,1.0172939979654119,Positive +2019-10-23,1495.7,244.62,0.55,,,1.097918675666989,1.4835862307477667,Neutral +2019-10-22,1487.5,208.97,-0.04,,,1.097918675666989,1.4835862307477667,Neutral +2019-10-21,1488.1,284.29,-0.4,,,1.097918675666989,1.4835862307477667,Neutral +2019-10-18,1494.1,232.55,-0.28,,,1.097918675666989,1.4835862307477667,Neutral +2019-10-17,1498.3,305.67,0.29,JP,Inflation Rate YoY ,0.3976143141153082,0.3976143141153082,Positive +2019-10-16,1494.0,367.9,0.71,US,Retail Sales MoM ,1.2,1.2,Positive +2019-10-15,1483.5,317.99,-0.94,GB,Claimant Count Change ,22.222222222222214,12.58134490238611,Negative +2019-10-14,1497.6,228.32,0.6,CN,Inflation Rate YoY ,0.1888574126534462,0.1888574126534462,Positive +2019-10-11,1488.7,485.96,-0.81,,,1.097918675666989,1.4835862307477667,Neutral +2019-10-10,1500.9,417.88,-0.79,US,Core Inflation Rate YoY ,0.0,0.0,Negative +2019-10-09,1512.8,285.28,0.59,,,1.097918675666989,1.4835862307477667,Neutral +2019-10-08,1503.9,371.44,-0.03,,,1.097918675666989,1.4835862307477667,Neutral +2019-10-07,1504.4,257.78,-0.56,,,1.097918675666989,1.4835862307477667,Neutral +2019-10-04,1512.9,344.79,-0.06,US,Balance of Trade ,0.7380073800737981,1.109057301293903,Negative +2019-10-03,1513.8,408.74,0.39,,,1.097918675666989,1.4835862307477667,Neutral +2019-10-02,1507.9,393.1,1.27,JP,Consumer Confidence ,1.097918675666989,4.60081190798375,Positive +2019-10-01,1489.0,450.17,1.09,,,1.097918675666989,1.4835862307477667,Neutral +2019-09-30,1472.9,439.71,-2.22,JP,Tankan Large Manufacturers Index,75.0,114.28571428571428,Negative +2019-09-27,1506.4,451.93,-0.58,US,Durable Goods Orders MoM ,2.4193548387096775,2.8282828282828283,Negative +2019-09-26,1515.2,378.29,0.19,GB,Gfk Consumer Confidence ,16.0,16.0,Positive +2019-09-25,1512.3,481.46,-1.81,,,1.097918675666989,1.4835862307477667,Neutral +2019-09-24,1540.2,424.86,0.57,,,1.097918675666989,1.4835862307477667,Neutral +2019-09-23,1531.5,359.88,1.08,,,1.097918675666989,1.4835862307477667,Neutral +2019-09-20,1515.1,284.39,0.59,,,1.097918675666989,1.4835862307477667,Neutral +2019-09-19,1506.2,291.3,-0.63,JP,Inflation Rate YoY ,0.5946481665014867,0.9891196834817014,Negative +2019-09-18,1515.8,364.96,0.16,GB,Inflation Rate YoY ,0.3861003861003858,0.3861003861003858,Positive +2019-09-17,1513.4,336.63,0.13,JP,Balance of Trade ,89.41368078175894,103.90942862197063,Positive +2019-09-16,1511.5,349.61,0.8,,,1.097918675666989,1.4835862307477667,Neutral +2019-09-13,1499.5,364.42,-0.52,US,Retail Sales MoM ,0.3976143141153082,0.0,Negative +2019-09-12,1507.4,491.47,0.28,US,Core Inflation Rate YoY ,0.1910219675262657,0.382409177820268,Positive +2019-09-11,1503.2,308.79,0.27,,,1.097918675666989,1.4835862307477667,Neutral +2019-09-10,1499.2,397.92,-0.79,GB,Claimant Count Change ,6.081081081081083,53.98230088495575,Negative +2019-09-09,1511.1,317.52,-0.29,GB,Balance of Trade ,1.097918675666989,273.9960500329164,Negative +2019-09-06,1515.5,544.87,-0.66,US,Non Farm Payrolls ,19.377162629757784,14.893617021276595,Negative +2019-09-05,1525.5,606.4,-2.24,,,1.097918675666989,1.4835862307477667,Neutral +2019-09-04,1560.4,412.35,0.49,US,Balance of Trade ,0.9389671361502347,1.127819548872183,Positive +2019-09-03,1552.8,0.0,-0.2,,,1.097918675666989,1.4835862307477667,Neutral +2019-09-02,1555.9,554.83,1.73,,,1.097918675666989,1.4835862307477667,Neutral +2019-08-30,1529.4,330.85,-0.49,US,Personal Income MoM ,0.398406374501992,0.398406374501992,Negative +2019-08-29,1536.9,455.6,-0.79,EA,Business Confidence ,5.042016806722689,68.13186813186813,Negative +2019-08-28,1549.1,353.91,-0.17,,,1.097918675666989,1.4835862307477667,Neutral +2019-08-27,1551.8,347.05,0.95,,,1.097918675666989,1.4835862307477667,Neutral +2019-08-26,1537.2,411.67,-0.03,US,Durable Goods Orders MoM ,1.7424975798644728,2.526724975704568,Negative +2019-08-23,1537.6,473.0,1.93,,,1.097918675666989,1.4835862307477667,Neutral +2019-08-22,1508.5,279.41,-0.48,JP,Inflation Rate YoY ,0.0,0.5923000987166832,Negative +2019-08-21,1515.7,245.9,0.0,CA,Inflation Rate YoY ,0.5785920925747347,0.3853564547206169,Neutral +2019-08-20,1515.7,247.54,0.27,,,1.097918675666989,1.4835862307477667,Neutral +2019-08-19,1511.6,295.83,-0.79,,,1.097918675666989,1.4835862307477667,Neutral +2019-08-16,1523.6,322.46,-0.5,,,1.097918675666989,1.4835862307477667,Neutral +2019-08-15,1531.2,436.12,0.22,US,Retail Sales MoM ,0.7920792079207921,0.7920792079207921,Positive +2019-08-14,1527.8,484.19,0.9,GB,Inflation Rate YoY ,0.3846153846153849,0.19212295869356408,Positive +2019-08-13,1514.1,616.74,-0.2,US,Core Inflation Rate YoY ,0.19175455417066106,0.19175455417066106,Negative +2019-08-12,1517.2,355.1,0.58,,,1.097918675666989,1.4835862307477667,Neutral +2019-08-09,1508.5,332.61,-0.07,GB,Balance of Trade ,1.097918675666989,7733.884297520662,Negative +2019-08-08,1509.5,402.96,-0.66,CN,Inflation Rate YoY ,0.18957345971564,0.18957345971564,Negative +2019-08-07,1519.6,651.55,2.39,CA,Ivey PMI s.a ,2.2181146025878054,4.485981308411226,Positive +2019-08-06,1484.2,381.92,0.52,,,1.097918675666989,1.4835862307477667,Neutral +2019-08-05,1476.5,534.19,1.3,,,1.097918675666989,1.4835862307477667,Neutral +2019-08-02,1457.5,493.05,1.75,US,Balance of Trade ,1.1029411764705908,0.9182736455463728,Positive +2019-08-01,1432.4,587.56,-0.38,,,1.097918675666989,1.4835862307477667,Neutral +2019-07-31,1437.8,419.58,-0.28,JP,Consumer Confidence ,1.8111254851229053,8.020050125313292,Negative +2019-07-30,1441.8,259.62,1.51,US,Personal Income MoM ,0.0,0.198609731876862,Positive +2019-07-29,1420.4,224.27,0.08,CN,US-China Trade Talks,1.097918675666989,1.4835862307477667,Positive +2019-07-26,1419.3,306.02,0.33,,,1.097918675666989,1.4835862307477667,Neutral +2019-07-25,1414.7,489.39,-0.63,US,Durable Goods Orders MoM ,2.5316455696202533,2.5316455696202533,Negative +2019-07-24,1423.6,318.16,0.13,,,1.097918675666989,1.4835862307477667,Neutral +2019-07-23,1421.7,386.68,-0.36,,,1.097918675666989,1.4835862307477667,Neutral +2019-07-22,1426.9,255.35,0.01,,,1.097918675666989,1.4835862307477667,Neutral +2019-07-19,1426.7,530.02,-0.1,,,1.097918675666989,1.4835862307477667,Neutral +2019-07-18,1428.1,481.33,0.34,JP,Inflation Rate YoY ,0.0,0.1970443349753695,Positive +2019-07-17,1423.3,358.17,0.86,GB,Inflation Rate YoY ,0.0,0.19212295869356408,Positive +2019-07-16,1411.2,334.82,-0.16,US,Retail Sales MoM ,0.5970149253731344,0.0,Negative +2019-07-15,1413.5,243.38,0.09,,,1.097918675666989,1.4835862307477667,Neutral +2019-07-12,1412.2,284.97,0.39,,,1.097918675666989,1.4835862307477667,Neutral +2019-07-11,1406.7,400.09,-0.41,US,Core Inflation Rate YoY ,0.19212295869356408,0.19212295869356408,Negative +2019-07-10,1412.5,443.5,0.86,GB,Balance of Trade,1.097918675666989,14.067278287461788,Positive +2019-07-09,1400.5,287.18,0.04,CN,Inflation Rate YoY ,0.0,0.18993352326685678,Positive +2019-07-08,1400.0,318.69,-0.24,,,1.097918675666989,1.4835862307477667,Neutral +2019-07-05,1403.4,0.34,0.24,US,Non Farm Payrolls ,33.246753246753244,26.767676767676768,Positive +2019-07-04,1400.1,577.38,-1.46,,,1.097918675666989,1.4835862307477667,Neutral +2019-07-03,1420.9,419.61,0.92,US,Balance of Trade,2.7649769585253456,2.205882352941182,Positive +2019-07-02,1408.0,383.25,1.35,,,1.097918675666989,1.4835862307477667,Neutral +2019-07-01,1389.3,389.76,-1.73,JP,Consumer Confidence ,1.2674271229404308,5.217391304347812,Negative +2019-06-28,1413.7,306.62,0.12,US,Personal Income MoM,0.3968253968253968,0.3968253968253968,Positive +2019-06-27,1412.0,336.36,-0.24,EA,Business Confidence ,8.571428571428571,11.267605633802816,Negative +2019-06-26,1415.4,421.95,-0.23,US,Durable Goods Orders MoM,2.434077079107505,3.0333670374115265,Negative +2019-06-25,1418.7,643.59,0.04,,,1.097918675666989,1.4835862307477667,Neutral +2019-06-24,1418.2,375.15,1.29,,,1.097918675666989,1.4835862307477667,Neutral +2019-06-21,1400.1,518.89,0.23,,,1.097918675666989,1.4835862307477667,Neutral +2019-06-20,1396.9,542.9,3.57,JP,Inflation Rate YoY,0.0,0.5899705014749264,Positive +2019-06-19,1348.8,332.61,-0.14,GB,Inflation Rate YoY,0.0,0.19212295869356408,Negative +2019-06-18,1350.7,376.27,0.58,JP,Balance of Trade,1.244024057985917,12.778603268945025,Positive +2019-06-17,1342.9,238.71,-0.12,,,1.097918675666989,1.4835862307477667,Neutral +2019-06-14,1344.5,358.45,0.06,US,Retail Sales MoM,0.1978239366963403,0.1978239366963403,Positive +2019-06-13,1343.7,204.83,0.52,,,1.097918675666989,1.4835862307477667,Neutral +2019-06-12,1336.8,234.46,0.42,US,Core Inflation Rate YoY,0.19212295869356408,0.19212295869356408,Positive +2019-06-11,1331.2,215.15,0.14,GB,Claimant Count Change,1.2738853503184746,9.73451327433628,Positive +2019-06-10,1329.3,228.03,-1.25,GB,Balance of Trade ,1.097918675666989,18.623481781376515,Negative +2019-06-07,1346.1,331.29,0.25,US,Non Farm Payrolls,84.2911877394636,86.46616541353383,Positive +2019-06-06,1342.7,263.09,0.68,US,Balance of Trade ,0.19900497512436677,0.7920792079208033,Positive +2019-06-05,1333.6,413.47,0.37,,,1.097918675666989,1.4835862307477667,Neutral +2019-06-04,1328.7,319.96,0.06,,,1.097918675666989,1.4835862307477667,Neutral +2019-06-03,1327.9,363.4,1.28,,,1.097918675666989,1.4835862307477667,Neutral +2019-05-31,1311.1,341.18,1.45,,,1.097918675666989,1.4835862307477667,Neutral +2019-05-30,1292.4,284.02,0.89,US,Personal Income MoM ,0.3968253968253968,0.595829195630586,Positive +2019-05-29,1281.0,189.69,0.07,,,1.097918675666989,1.4835862307477667,Neutral +2019-05-28,1280.1,0.78,0.23,EA,Business Confidence,11.764705882352946,7.228915662650602,Positive +2019-05-27,1277.1,362.16,-0.51,,,1.097918675666989,1.4835862307477667,Neutral +2019-05-24,1283.6,218.71,-0.14,,,1.097918675666989,1.4835862307477667,Neutral +2019-05-23,1285.4,330.16,0.88,US,Durable Goods Orders MoM ,0.20855057351407735,0.8316008316008316,Positive +2019-05-22,1274.2,191.37,0.08,GB,Inflation Rate YoY ,0.19175455417066106,0.5774783445620795,Positive +2019-05-21,1273.2,213.17,-0.32,JP,Balance of Trade ,107.93650793650794,126.93461307738454,Negative +2019-05-20,1277.3,212.18,0.13,,,1.097918675666989,1.4835862307477667,Neutral +2019-05-17,1275.7,264.57,-0.82,,,1.097918675666989,1.4835862307477667,Neutral +2019-05-16,1286.2,282.07,-0.89,,,1.097918675666989,1.4835862307477667,Neutral +2019-05-15,1297.8,247.52,0.12,US,Retail Sales MoM ,0.8,0.9990009990009991,Positive +2019-05-14,1296.3,222.05,-0.42,GB,Claimant Count Change ,2.004008016032064,1.1834319526627246,Negative +2019-05-13,1301.8,379.44,1.12,,,1.097918675666989,1.4835862307477667,Neutral +2019-05-10,1287.4,238.64,0.17,,,1.097918675666989,1.4835862307477667,Neutral +2019-05-09,1285.2,306.55,0.3,US,Balance of Trade ,0.4032258064516186,0.20181634712411992,Positive +2019-05-08,1281.4,302.69,-0.33,CN,Inflation Rate YoY ,0.0,0.7648183556405354,Negative +2019-05-07,1285.6,251.09,0.14,CA,Ivey PMI s.a ,5.27752502274795,4.347826086956519,Positive +2019-05-06,1283.8,244.34,0.2,,,1.097918675666989,1.4835862307477667,Neutral +2019-05-03,1281.3,280.32,0.73,,,1.097918675666989,1.4835862307477667,Neutral +2019-05-02,1272.0,282.5,-0.95,,,1.097918675666989,1.4835862307477667,Neutral +2019-05-01,1284.2,275.43,-0.12,,,1.097918675666989,1.4835862307477667,Neutral +2019-04-30,1285.7,239.44,0.33,,,1.097918675666989,1.4835862307477667,Neutral +2019-04-29,1281.5,208.96,-0.57,US,Personal Income MoM ,0.5970149253731344,0.398406374501992,Negative +2019-04-26,1288.8,278.89,0.71,,,1.097918675666989,1.4835862307477667,Neutral +2019-04-25,1279.7,237.15,0.02,US,Durable Goods Orders MoM ,3.6714975845410627,4.263565891472868,Positive +2019-04-24,1279.4,246.05,0.49,,,1.097918675666989,1.4835862307477667,Neutral +2019-04-23,1273.2,280.34,-0.34,,,1.097918675666989,1.4835862307477667,Neutral +2019-04-22,1277.6,136.44,0.13,,,1.097918675666989,1.4835862307477667,Neutral +2019-04-18,1276.0,229.63,-0.06,US,Retail Sales MoM ,1.3658536585365857,1.9569471624266144,Negative +2019-04-17,1276.8,223.36,-0.03,US,Balance of Trade ,8.047105004906774,6.719367588932804,Negative +2019-04-16,1277.2,326.51,-1.09,GB,Claimant Count Change ,33.67139959432049,135.86005830903792,Negative +2019-04-15,1291.3,232.99,-0.3,,,1.097918675666989,1.4835862307477667,Neutral +2019-04-12,1295.2,192.49,0.15,,,1.097918675666989,1.4835862307477667,Neutral +2019-04-11,1293.3,324.74,-1.57,,,1.097918675666989,1.4835862307477667,Neutral +2019-04-10,1313.9,218.88,0.43,US,Core Inflation Rate YoY ,0.19212295869356408,0.3838771593090208,Positive +2019-04-09,1308.3,200.34,0.49,,,1.097918675666989,1.4835862307477667,Neutral +2019-04-08,1301.9,207.57,0.49,JP,Consumer Confidence ,4.295942720763716,3.592814371257485,Positive +2019-04-05,1295.6,231.45,0.1,US,Non Farm Payrolls ,8.488063660477453,9.6,Positive +2019-04-04,1294.3,262.54,-0.08,CA,Ivey PMI s.a ,6.015037593984954,7.379375591296119,Negative +2019-04-03,1295.3,190.37,-0.01,,,1.097918675666989,1.4835862307477667,Neutral +2019-04-02,1295.4,196.4,0.09,US,Durable Goods Orders MoM ,0.41407867494823986,1.8423746161719552,Positive +2019-04-01,1294.2,236.66,-0.33,US,Retail Sales MoM ,0.9990009990009991,0.8,Negative +2019-03-29,1298.5,270.18,0.25,US,Personal Income MoM ,0.19900497512437815,0.0,Positive +2019-03-28,1295.3,426.82,-1.15,EA,Business Confidence ,11.872146118721462,6.5727699530516395,Negative +2019-03-27,1310.4,206.26,-0.35,US,Balance of Trade ,11.017740429505134,14.48212648945921,Negative +2019-03-26,1315.0,267.17,-0.57,,,1.097918675666989,1.4835862307477667,Neutral +2019-03-25,1322.6,251.98,0.78,,,1.097918675666989,1.4835862307477667,Neutral +2019-03-22,1312.3,271.38,0.38,CA,Inflation Rate YoY ,0.194363459669582,0.0,Positive +2019-03-21,1307.3,332.61,0.43,JP,Inflation Rate YoY ,0.19900497512437815,0.19940179461615157,Positive +2019-03-20,1301.7,370.4,-0.37,GB,Inflation Rate YoY ,0.1928640308582451,0.1928640308582451,Negative +2019-03-19,1306.5,206.9,0.38,GB,Claimant Count Change ,158.30618892508144,96.49595687331535,Positive +2019-03-18,1301.5,176.49,-0.11,,,1.097918675666989,1.4835862307477667,Neutral +2019-03-15,1302.9,234.65,0.6,,,1.097918675666989,1.4835862307477667,Neutral +2019-03-14,1295.1,248.21,-1.08,,,1.097918675666989,1.4835862307477667,Neutral +2019-03-13,1309.3,214.24,0.86,US,Durable Goods Orders MoM ,1.801801801801802,2.613065326633166,Positive +2019-03-12,1298.1,203.89,0.54,US,Core Inflation Rate YoY ,0.19175455417066106,0.19175455417066106,Positive +2019-03-11,1291.1,196.86,-0.63,US,Retail Sales MoM ,0.39920159680638717,0.19900497512437815,Negative +2019-03-08,1299.3,283.84,1.03,US,Non Farm Payrolls ,159.2039800995025,161.13744075829385,Positive +2019-03-07,1286.1,257.92,-0.12,,,1.097918675666989,1.4835862307477667,Neutral +2019-03-06,1287.6,192.93,0.23,US,Balance of Trade ,3.256212510711223,6.620209059233445,Positive +2019-03-05,1284.7,216.93,-0.22,,,1.097918675666989,1.4835862307477667,Neutral +2019-03-04,1287.5,268.39,-0.9,CN,National People’s Congress,1.097918675666989,1.4835862307477667,Negative +2019-03-01,1299.2,343.47,-1.28,US,Personal Income MoM ,1.183431952662722,1.183431952662722,Negative +2019-02-28,1316.1,252.24,-0.39,CN,Caixin Manufacturing PMI ,2.8169014084507014,1.801801801801799,Negative +2019-02-27,1321.2,198.04,-0.55,EA,Business Confidence ,7.860262008733622,6.956521739130432,Negative +2019-02-26,1328.5,185.56,-0.08,,,1.097918675666989,1.4835862307477667,Neutral +2019-02-25,1329.5,181.78,-0.25,,,1.097918675666989,1.4835862307477667,Neutral +2019-02-22,1332.8,241.8,0.38,,,1.097918675666989,1.4835862307477667,Neutral +2019-02-21,1327.8,285.81,-1.49,US,Durable Goods Orders MoM ,0.5842259006815967,2.507232401157185,Negative +2019-02-20,1347.9,246.72,0.23,,,1.097918675666989,1.4835862307477667,Neutral +2019-02-19,1344.8,348.64,0.0,GB,Claimant Count Change ,128.49162011173186,89.65517241379311,Neutral +2019-02-18,1344.8,348.64,1.72,,,1.097918675666989,1.4835862307477667,Neutral +2019-02-15,1322.1,200.28,0.62,,,1.097918675666989,1.4835862307477667,Neutral +2019-02-14,1313.9,228.46,-0.09,US,Retail Sales MoM ,2.8282828282828283,3.027245206861756,Negative +2019-02-13,1315.1,213.96,0.08,US,Core Inflation Rate YoY ,0.19175455417066106,0.3838771593090208,Positive +2019-02-12,1314.0,146.45,0.16,,,1.097918675666989,1.4835862307477667,Neutral +2019-02-11,1311.9,150.61,-0.5,GB,Balance of Trade ,1.097918675666989,64.37394042140956,Negative +2019-02-08,1318.5,150.61,0.33,,,1.097918675666989,1.4835862307477667,Neutral +2019-02-07,1314.2,166.76,-0.02,,,1.097918675666989,1.4835862307477667,Neutral +2019-02-06,1314.4,137.25,-0.36,US,Balance of Trade ,9.188660801564033,7.305034550839097,Negative +2019-02-05,1319.2,129.01,-0.01,,,1.097918675666989,1.4835862307477667,Neutral +2019-02-04,1319.3,159.56,-0.21,,,1.097918675666989,1.4835862307477667,Neutral +2019-02-01,1322.1,200.0,-0.23,US,Non Farm Payrolls ,59.148936170212764,56.42105263157895,Negative +2019-01-31,1325.2,224.75,0.74,CN,Caixin Manufacturing PMI ,2.4291497975708563,3.4239677744209525,Positive +2019-01-30,1315.5,272.11,0.5,EA,Business Confidence ,4.9180327868852505,4.9180327868852505,Positive +2019-01-29,1308.9,213.61,0.45,,,1.097918675666989,1.4835862307477667,Neutral +2019-01-28,1303.1,243.07,0.39,,,1.097918675666989,1.4835862307477667,Neutral +2019-01-25,1298.1,303.84,1.43,,,1.097918675666989,1.4835862307477667,Neutral +2019-01-24,1279.8,225.77,-0.33,,,1.097918675666989,1.4835862307477667,Neutral +2019-01-23,1284.0,217.13,-0.14,,,1.097918675666989,1.4835862307477667,Neutral +2019-01-22,1285.8,1.27,0.19,GB,Claimant Count Change ,3.827751196172252,67.9245283018868,Positive +2019-01-21,1283.4,318.85,0.06,,,1.097918675666989,1.4835862307477667,Neutral +2019-01-18,1282.6,225.57,-0.75,CA,Inflation Rate YoY ,0.5785920925747347,0.5785920925747347,Negative +2019-01-17,1292.3,191.98,-0.12,JP,Inflation Rate YoY ,0.0,0.5946481665014867,Negative +2019-01-16,1293.8,181.39,0.42,GB,Inflation Rate YoY ,0.0,0.19175455417066106,Positive +2019-01-15,1288.4,242.07,-0.22,,,1.097918675666989,1.4835862307477667,Neutral +2019-01-14,1291.3,221.89,0.14,,,1.097918675666989,1.4835862307477667,Neutral +2019-01-11,1289.5,210.64,0.16,US,Core Inflation Rate YoY ,0.0,0.0,Positive +2019-01-10,1287.4,239.92,-0.36,,,1.097918675666989,1.4835862307477667,Neutral +2019-01-09,1292.0,245.97,0.47,CN,Inflation Rate YoY ,0.3846153846153849,0.5763688760806915,Positive +2019-01-08,1285.9,221.92,-0.31,EA,Business Confidence ,12.099644128113882,19.17808219178083,Negative +2019-01-07,1289.9,204.68,0.32,CA,Ivey PMI s.a ,4.936170212765967,5.110732538330494,Positive +2019-01-04,1285.8,316.06,-0.7,US,Non Farm Payrolls ,55.10204081632652,61.50627615062761,Negative +2019-01-03,1294.8,244.54,0.83,,,1.097918675666989,1.4835862307477667,Neutral +2019-01-02,1284.1,235.33,0.22,,,1.097918675666989,1.4835862307477667,Neutral diff --git a/The Effect of Economic News on Gold Prices Analysis/Images/Accuracies of Models.png b/The Effect of Economic News on Gold Prices Analysis/Images/Accuracies of Models.png new file mode 100644 index 0000000000000000000000000000000000000000..d2769445f778ac6f3ba7f832b5464f9c541d060d GIT binary patch literal 29773 zcmcG$byQYc*EhTYX%G;R1_42(Ls~=uK>?-X5K2jxgdiv(Eg+!?NJxmJgmg-WgdiOk zr647tlt_GY<6Y0WpZ6W#_s7Q==jgb+*n6+F=9+8%V(t*t+X|#abVLY(klwr@r;Z@l zh6sXHNPq{QJTL5Bfuv%E4ZUSCm(f z`>dsli=(pyAD`X7zQF6?WWjgQaLyYpLg;woFJ}ZHGe-Zz%975sLJ;Swn{wAQ-4nlK z+}t&`4)NFBqRVdXq*T8+NyJlfPj>W+x+N9`ITh8tbk>yiT2=xKYoxR#t@Z${eoZ==TX_2)@qEH4F|?IXyg>)EO|6(XqDXoWNi*c>Uly zOtOlKM0BF|+^)1LZyNl0m6Vi_G3i$^F)_`9a<-WQQ5uaAMQb*}A&ADg;DSWe856Im0R> zM2Sq#&a&Qzc^FXTce(ca`7EY>FiVXsyEB!}+}fH5Y47UthhOuyJ_i%lfU}5&5il?} zH$SB#Q#!Xg^{Q9d_XC+8MOi_{!!kMADrOch!6b1;ZG zBH7v5?(^{$IeJ$HDSv+Zq>vzDcRaaSd%@?CtG1Y`tyEL7bvOBYjtuMP|WM(#Xblh}!_53-dle4p$rlx;h z9(UH@5>eZm%*^GN#wI4%^z;e%&wgdLgi<$+jp?~LySWvpV<6yOzEpCel+nx{+TVX< zJ5fRLoa0tw$~C`LN%Pg6DQ|_gXN;-p*+vcy5ynk{i}NurUQA=$rUI&~t5@TywQ{ww zkfD4-&ncTayK#|Pp`+D9k_x9eMfZmfuVtuXA&rfVy|tchBO@azYU%RsOWB!@TT5EC z_YA8akn+{-vaYPG7}?uDJIN?jvB(urNK#1bn;5f^4>f9mMqwf!9{tBY@y zC| zxunhy%aQ6!t##AAkE+9CVfLp(ejC}n%qSE=B$w;Ab@YAPH40sj1ysmg`E#ZoairP-qG4}NI zh&|rBbcya(z^9Eb5z;2B6P3Gr%LRR9cKV6p&UlpPZ~IqPipxhZh2QIZY5aTp`|j58 z-M%+BDc`(#bC#VwLvi_ALFjd0H^ydsE^jV55J~3fb$|onaj_O~$d^ro# z<>Tk)XFs++)3nu^cc+%_Amg~Y|hr9A$_#JCazgu^Uch9nCmW|=^_^UGn;yPPHJmw$4R(yR=F%b=}D55UbInV ziC5Onc)k1PJp{~)*jPA1v_x+aU}dO>6nr?;b4zM?dfApKMJjdXbz7{K%P51h^UvRJ zNtrIwFflRd7Mb807#gPbS(1~Jr%3i5s(pG~09gmAe@ewge){wq(Y4i2@!!WvWnq6E z?*CL-!BkU!l0Lfp#LsWz!_h&(=TEW_^gs0nT+QZU8wd3Qu&}6(e#m*}I^~Ex{BaJ> zlk{ruor>(fbOlqm%ncftcrcUv`pRGEG&L4<&qxL>m3@aHG#AOqeu2xm2Q^(TJCwsp8M>!nL2>Tu+yPPJF@N2KLibkl<^$u3Mtpz0;>Zq0f zf{6Xn6)!|)xccIvhKuxhZMh6}<6l4KV(dSTk*|yt;gmZ}weD_wag{E{2tV3&%+o6+ zQhLdKZL02ZUx}4Q&3Ys81wOtuX77Dpx2ea}$;rtyQXZFJBWFrRUb%RYFg`xs{qWZ} ziqof02nh+*>`Z#P|Lhi}pr!q5W@_iPt({#T)GUvV4t5;x-@oSMBxv4~m@PWrLVdSc zf%&n2s%(%6By#w-hIk>1>7^yT8I@K@H1!D%b%ZuHHvWNuX>Z<~IIoi2{C&J!;PIXd zw_(+3US3|y@iLyTPU0eVV<(Q2T^$rbOGQVYNez0sf&xAhut{jWlf5e2qN^A24n_oL z?hY>RRr;#i$(IQwB_-kTCmb(#KnscW0`CK*wNpw{kA9LSKi>YUW}}sU{pZi7<`7CX zRaFEjEG}+>^I#pO;4D8sx%AP#(EO*@N9|Q`d#_(})QJ+VL|9l@?!Uj67nyaOsuh5m zVx-nnl!1{^z;XKO2|T=6NbW-i2D>Vh9Ln_{W4MaUyXoNLG@XJwy44SOYHDf_0ly0--IrlfetPOv@WOql9!#4A?DVq;Cpxw6kr*Oj;iVRaP{b-45Dvbq_Fk^` z_GD%CDCy43XUWVWVG8f+Ey(CkXTIvO8 zG@?1G*qPWb7ZD$ruC3-{fRiOdukz+>!5fBKj9q=zmFe*0p2t^ldF@n+XY=eFHqz?0 z6PVbo`kLk#31QB!$VlW{P&f2UocL7Y{Je_6?+;?~@F&;3pGmvanIx4WXnyo@=^r28 zX2-OSzOap>>DW-TAj|F)pgF$&n{TV^-hrj}{roc2XRS%_k1xJ>4#QoaAG(N)kd#&l zptvlm=M`HBIrhTf1XgzvcLr};${)CfoXspG`H(yyBAYbQqz@M$JH7xG;w6zB)~GJL zpUBhKof$PSN5gPDS29+Wcs3E%WGSzEo9G2;6H>KBk3VnhS0@hVj&GYiPQHSc zxBO4u?U7mkjN|?@R_FrH@D0P0XuM)Dox*2(aaSJzDC{rfcacg(M7iSPFF3LbF;6kq za2|tZvKR6CVc#tZa1f65Xz9{tsmp|;aq-g!nR?jB%L7+j!oP4&>7c2h$dw}Gf(Eh6 zdg1kP4w%SsnyQ=z*bRN@@luMN!g0ksbTS0lO0aOBHFWi!F|$3#LMS~P`C?DQ7k!mE znu26;QZ7Y*X^%-5Ipb=$6b(pv)Aouh>1e<`OB0JgFP>2nEg}-b!RGWR@yV5O5~R>k zfyAErg`xo(gD>UT3YQAEk-htv%c+q+qovhhX5=Y7-P0?diI7#&`50WG3;#J@Ym;$?i?Y}G9fV(p2m<%kLX{x zza@`VhhgSJr*gmtV;3kl$0Q z&>=>b6H*mdi)4oXjWw^thWww5Uv8N&|`ezS>*(F_+X?^F|!l3v%-d$qa^<&#e7 zzMgZrTkJ>OXTiG(BadFyR>L;i{t8L(n`F1@`R%WF@~f_Lhqgvz`*h5TZtqZ`NRI@k9CWM5ATcEVVLZHl7%^f6TbRLFznps#NxO?}m@~caP zq7GLo*qdfsLXGY0-c?stEA_{kJ#ypQ71y7AU`%^u&+mA)=3{b&bsuNmYTjL)+!Ar5 zeZ?7&e+=!d#l*!IZ@D=+$#{5p1Vj)L5;g!byZ`IQJGK$v%RMGYP(5GPiF( zTYVWFtsbNGPNbDc{0u3vzcSwb+JG=a?JM@1j1cvXD^-!ca0nI(i8cs*pLoL?w3@Y1 zO#Na1htegRArb)D`~m_EP<^84qJ7R=dJAHP#os3(fgZr;OCJ3|>bsBB9J+}4YJ4(Z zd(lDlOe5iP;lav?FNC(y(cuBrl>+r_f1v3mZ*hK?vK9Dodo5pF|5JKJ*zx?B6R;G{ zMwS`&9iMvIHw-8+S{c3f93033WPHQINNN{pX=xoFyVY&{pqUPTD57bWHmkp*oFXQgl#)&S&f*G-tGG)9X8 zdiM1Ed>~*5+sPVQ*+7y?hcH0-1_lO>zqjpH#!7P=1>8_-MATu@KQvTHOZ%FjHm7M9 z^9mWVYks6<&|$U)9BGah*GcP$Il7@%(vvS0Lvm9+wSIkT0mx?B@{~%q+@8_I#Dw4K z^SRTfPa8p%kN5!ff)X568&OeFBk%7K&wlxGf1#HJ3T&D5J|n=0RRYxyzRT$9(wsVV zst|xZ@F)1Nc2)Q0zkU0XqT%!zn`~BrfvIckR~l zcgp08-GD9C%6*f7JL0P58Md{{WJ{?wtobV^_J0Rij0Ue06Z71-wSiQe?~3=^-F1g0 zF#_&E_k))d)PF9fPEJnzHbdM7FeeWlJfOMqNDLT>6Q-u7h>uKaJuobV_818>3k#IW zJovrS))+vXsyX!fG~e@%^@d1f^JxFyDBmz}mE4^_jo@ z63&bx)wwH%TUv%oKQ|5s9EoR2PzjK6sB#fmG$|XXn!kHA$r{lw5vVopTk} z#0umkq~ZFiyB}8OHvCd(`2JTSPd7NGzi{yk8+}*%jfWLrOJ}}vfJBveEl*``RNZw6z|cq!W9qBH&fr%Ry;S!-TdS6R{9hTu;@H8 z1cnL00)|qlmrUSlPg9j-UUHgpyX%ctFGIS!FV3bi3lwEmT}beUkWi~iRoc!C^-K_9Aj`ixcIJa`Af8weR|RE$Ny&-oWvHOPlHQ>YPV@t)y-Dt#kQ-Oo6FNCO{n% z2cD?!lJlhuDc@MWX~o-h3rOuxFc7Y0`n#6yIW89{}#qa9&N&@ z{xt@+DLg8E?n#>+C){$!C$Y7a&4az^{4RqOP}ek04H8wh%KAK&!|)Vb&Y1ogd-@v#Kke{$eI1>*mz=Ur z(Nrx(YKPnLSLL2ZjC#s`u3(^4qvGV%Fg+-eL+W=|??5f10=E@7T3sWy;G&9lpfdSu z_uik|E|h02w}0dd$Sozp!5Jkft%IV&l>3FeF25X1=5N1^U?mH5Kkg+Qmw3veDl}Xb z7Yq1yV{`mu_LKTPWKez-KECDNNrNii&iG&aqH5E)fUb1l!Loj-{BD|%^VPUnzR^jD zp3dYn_z?-{KE2c)N_*`aP<- z64Cjh>KxGaH_Yt?yh5u^0>|VB>%|7^#arJ^XIgC~ZLoIqfa!V$I)(xA1M(<;!P2Yv zWcnp`CS0!Kn>27e-^GJhO~Ayw(7(PLjb>!J#KzA~w!zBS=u*+j>Hx^P)QB&OjUZfP zEo>rEI>*r`Vt3^+r6a5IBsDkrVP!GCo@kl;otxrk_Px}W zoM4OKB~`x+|3X-9bS~CdSw{uLm-EfNTAwa_6@0X*eD<^x?F0EtKo=xv-J3?|w9`1` zr(fMTs>gm`c=HY1oW)zmCTz_s(`~qn_yRZ2as8KL5B2;AZ4w?*we~1y3ci(X)zCd{ zZu%63k|um;R-k=Vsz8}KMBuVv?~jPuz6+(XpuMHNF1 z2Z`a<#6$y+arUJ~K!>(sFCk9>?~3rXyeM z&9_3BL$$|c%QATX1BB+tlNjO|nMLA{Rg9ng@P>id>%-aO3ASD9z=xo!J=)MdGU zT{DTMip0l&w`o?gw)*h$>u0spqt&6oSyv>I9?`2^9OV~?{u0x}1o>z%EVc7$iDOZt zKhv0y!TjL^CR}zj5;dpt#ImGb+UU}Yis^E)=LhD{%f@2G50#74jlW_Q&ZK$0R(U)Y zP28KJ#D&Wy5{S_wva%3G?}~1_9KIojoBrfip=7pPHM8IbQe$RhlS$vm; z^*Cr2DEfqyGC#SFgY3KMFsK)YoTNEW1;5kqDVf>jc_o`O~;(zqf6Z6 zz*RiB+f|=Wyr>=vSncSnfBi?-(!6_KxqV~QBq{6b$WlrQy_q}xr5JM`?j$F-qw5MlsrWm6)6j$* zq>;DqJ+YV~Z05;DOew$$fJZOO&a$#%BL*E^3huTXW`ahK+#DcmLCPIOHf>jZSnLc^ zDe64|ROJt$$y&{?d@uL`pN=E(dH2x-B?Hnyyuf@slb)29C~n)|GRTv9bpeeY(y{LS zQz%YE_){elQbkUa7?S$KA-G0ri-qV`eLIzpPEeGYSD3Q=%}Ts?bo%MfW0MBvRC$aS ztgj}oO+R~=Pdf*yasvu!t(zKq2Yn{KWA5ce8apU+pj+>z zk*6l-`yWa(*6$kYuTrC9*wjt60nT)NbJJfjLq=7V{28G5S`K|x>XxjJ%!)Vg5O{^ZP?m+W-yZV2i zv*ouPb54NL*dRwYw!L`q;%bKa;;sKeXU`)eeKt2;YQL2NtE#HnEBhLhI-NCn@8x;Z z2#c|*YXn9^XO6RlRncOln2R{E6D?GJnFDi?Cvr|#ff|^iojddO>l;xFkoSv=RLn0J z0ZV5n#m)l02S__oY(Z9LJNl%g6+|!wR z2x~|J1URM}gQ?}r9Xs2_G=ME)-Wq(fvjxaFbS2DsSMQ8?T=gNI_}&He*c;U^3hR%5 z&Ba;{<Lm4s=S-Y&97uGA^zk{S085NZ( zD#gZz14<^dI?p1prB zh>5H2%>Ve4Ge%MOufG;C3tpdGEyHf#d2oSK!;}}@hl9b)tkJ4(&seS*hnC&4h5F!} zI>0&@7NC5#%a;vAZ>9I0y?mJg6u*ZHrdpg-6B84vckVpvP7pP1k7U^i7Z4Q<3JoQ; zpQ;OoKwE4DMY>^h^slvtAPa*+@vHq?M$q$)!&OWv-zwhWZjG!s-#5Fusu+GQzon0mIbU>QayOazJ#VBZDGx)Wc&So+?qeT*PK z%kN%2o)4{rqolgPl}5o!MMAP4UQ!)N$ddZ0X)*JgG!slz+{bbL)^pv%LjuSlzrsR( z%(c~yjt-AD6OaW=dlJP#ND2xFz{NYs5Dbyf)Y>X9%5nZYKB|VhF+nA<`wuU+`}u~_RNa_bxyEB;V;(lLc{#7DSSc|$IEQyn?<6aweZvjjriFa8 zkZ?t0sTYfYp@8pVA$M2qLD8PpRyx~rC%*v*eG@y*`@)*k{4RZu1IwLdEgU3I$6E1Q z(4)80(z1R)@j%|DAV;uHa$GL*j4U-qf#bPxU*Xlb3tzDm{lXI?dzW_ddBS zVQj-1dY1ZbJvjHD87-s{3A+~7f4wp`X$bXDa3bq*1_|4bcG_o%C-I5hXL(FwxOuf; zXFCuoGdOqFZ|dd^%#l+J68}RLm^?YZ@MRg!Ld_s}K%9%=r*|!N&mz;A?PiIJRqQAn zaMiEW^AlDmvG7962=Ro}&r&p13#k&GqK!Wp>2Q$Aai?VTz-KZU4j?h8Hawv(WD2vY zi$0?9LYl%W;S}7Ju3O}>Q9)~Dt;cCKsq{zTw&V|}!&GUxAipfp1@d~F(|4xqq8-3S z3c2?MqwUY2AWjYA%(-}`=bS}T^NnXZRqnuw3|=EK)V$aF za9%h)5GYV`yHdzfYd!r#3mXGDo7(x;h?j^KN((QAeN6}$ab;md_>=8e7qDomvOd?W zbPH?&?-L-&%UTUJ5a8FPz(IvmDHQ)vv?&ONZNNW>x_F-P(QFavnH>)0vDng5uE&s08 zTp47krOwa`QPv!3Dk1gnKjfbk2!$odGNzC*YGJVx8t5~;oC0`V(?bj<+E%6f!Sx99 zZ6NcFw#zIbX43HHboY4-Zgd9#ml|~q4eBijYAF#QUXTmnU&Wl}ILfXY#-f3!SNsD4 z+hSZa@LgpHz{tlSWvKj(R!3`i+PYlP9~4Y~fO@zcYnBs4O~|d4neh4BXDYN*pSF0n zqFRDlxW20{=w)?Yx7QyOMpn?}@S$Ifr|Br#rG@+7Rk_ntw3~qH1e(q$7ymQc1`;UD zxE9=bFs(L-@eYwSHWF7WOvgTFjaE20v;fsp0jggWwQ>3J9we+B1z6{?8v0p$Ph$4` z$qV)6zrR4z56&8+ip}1Tm19M|vwM$_#N<3l4b2HJjTe|dIkdg1SGPtq>+n?x4aBW6 zrkJOB`|1_Cx%~XS*CDu*A-JuDD`JQ}gx#)Y>-ml9e?o(imW1VmHq+2*3-fq4Wh;@r zOt$szvs7!>zY*2#{Qs_XjO5x-f@F&vqE^yPQmAIITpTg#>j|xBfhaRWKzd^ADDk1eGfunDAQarkVExp%;-_{24$V0&`Y_a_CbZilfV^BK& zVaqNLClzdzZq-FX^n$M_mhkbF*k_B0*1HdL(LzD#(vo_2N6T~gu zy$r$D{f0xt$6@FS-D`U{gFT#lD#&WKen)rQECU3L*6h-p$kIULk0yA!Pu_;naH~qYS}DXT}Lwd=iN8!B<6?n%>41BH#*i zOP-^9#=d%-WGmw=SsYh5WF``@hYr%21~7!a29!VMG%xYYz!>s-PC{D2+*!eyGhtr^ z!&aAonKe5LA*Nk=zq}!#N2E%Ru`EJJR# zTZVhe4MGXDsyF7;#%-0Ckb3vBkQD3Y-s`13>i5EMRct)n9(zu6@>+bo2~pTLHN<$! zUyrS~rJ4eJA`cw|fh_e+*5)bN1|9|w(%l_w!1RTl0*iC8FTP}c=>RPl=0!^=kT=>N z65MNM98W!@CQHkt$ zI}KI=fpwoloSuUSDDYW;&t@qw(YI07N=!dH@=-4N-2+#M6A)M{A&sQk8O|7Gzo?)S z)P!^5yzYhYLZe_HMcwdcDPntIJ84QrJDh=|$_1(SXPQLUWaa;pNR~BdU2}B!d;Q0c zCm@o&60v&dwncRZ9MsQVbfWOKV z{C;B2^I`T~=U+d1;!yVs53Gj5K*z6loPRwHF1Qw*yN@%<^T1^HCL?3f9t!hJlEN=_AQUpLoDX|?rg(5c4=?cM8 zNYqwv_XE>f?G6*vcLWX&4yd?X4MJanfJklqbndecH%jVkDQJs{f zV#X<`-K!Gbz59-{%zg3VHGBK~$?&BsI`kU*)gSl}BhXaaySPvdRM1SCS>=D6l4jEY zdj78xn5IWRm=Evot{Y_}ISQXL+8pIp^DNEc z{|$mIQeELVckTo_b6`gX*BPp8fKw9}9JN&fAY?X!>V$yHl!l%@9SnMLB6f80&ls}l zDe35*LT!!(`pxdw=PF?3!XlyJN3302zT<)|F(5IK0mH){Agwh>O;o8oT)n(goIS#< zv!OC9C#Pcat@6^FZ)chsz|SyV0rikDBJ8z28++F)1b(;S(2vS-H3Fv8R7f(DGZWOLXvOIxG*_<2=QTCm;!a?CdN8H!Z}goM=H|p{m0tYUILc zBFjs!@Ojt9N^L40{^S6$EayFuW(1^vRN+C!S_6s}FVj8=&S}e$^sG#_o1!V3=YX_9 zdOgPbPU4lv654sXzOKtdEF2to5M(ldQPHVKXoRg#!-{0kGt<(B@aUJFy>f*q=p>_z zrR4?aE&xY)D!q{Vx)HZt34x^Bs+@@lYneUfDFAxZ)Qk9lZ?WcQkEGax6`E6&loU)% z&sbyw>%lq?`9WomPL=V@-?;3}ulbYhZIf}wW)yo{%4?-g1+!y0MFJBf3JNB7oEHc zb}2AcZj9L!7=w`*DecXB;UK{_~ifeE$2hTgzNlouLcyZ?p*W^&!Fv~_pY&BM*E z+6N>Ds4LU<%>J-<(QaS~VCW4Y#6`dFJA;~~BRy$7N3nM3n-nOE_2c08>O3wJ@{u!SMEHvI1&FDr0u2W+?laL%L8(Vxf*2-J& zTr?5-t=rn1T?AXW2=^#e&}O0uI*=;sK@=5WVevYa3q7x(vu;O6Oh^0G7hHJld>7lE zO!1+$`QWvG)qr*Qe7|Hrn=GVxDDlP`ZzN3`dMB&2O@^Yi=iZRQxm3+}*E~VGu|cJq zfqDQrwL?%>QLgTg$ z7Ecckd!WjM@?qn162VPU3dO$o5 zn4XU?R6!+)tSG>^D0jE>npqwSr;ful@(IZUIXZ#iI8R9EDt9m9$O+=$G~sp0mNT&QDUp zV=S!@oyMdf@)|kvC>HS;7y8WS#l~roU*>pGfVz1V?!Lady(*~PUMR|e*6t)-IZ#jr zmAM9_XDH5E2Q!7GhSK?)-+t*{tD}L`*L+KFOPd4&Go<%?BxiLd)-%1sE%id7Q)pakG#LG276)y-IWffqWsSsaRHm zOVLN!agnpB;5_uyfo1Hb0cl@4gumbC+IXqJQdd9n`aB+3JI&VzPM2wMGpxaZlU5y3 z3$r41N|st!%o(rL2S_oK&rU`2H`3taKGO>tHZHY0;LCh+Tz>4Jm+Su$! zl4t@V)rJeb4%FE>rvrJdBa@eVX_9JIR5jnW8UPZ=(fNmObAgvhm97YujSL2Rw!_SO zXLXF)4aYkfMCP=;Ss(xsKP3NCt%+G8gKHH6*TJ7%PKFpAZWFfyua)L8V=pxDFYr&U z#RMa;bl9{fa`1FEn~yQNshfz7fX$#bDxy{(KC;8-K4ygD$r3eOtyi;^=#dyV*q&Jg z2{WHNptxG9>wg{#X*qzZ@e2Nnm>axVPNcZ;L1P%^7;yR$3z$2RV*FB{cQAAPKMR+7 zj^2c1+5g(mJ*D_jn82l2J`&Yw$hBy}Hi}3Bv&1xT3R!QtgU*NzNHn_CQ75ie$A&`P zas|wsRi^HeqAuHIviIZhoXgO?Yxw@a7L{uLBzur*SUkAFafy0F?I3|F3XAe zo+M%rir`~ba1h4w-StZR5t7r~Imw{0wz;ZT@rCt0u@cxd+Y8aNWX%A_)j$+#1VGHR zft*44|7#cF31~~8diEO1rn=v&l8?3qbIYYQVqY;}iwK!?ev`&L&=zP+9F6j~i7MJK_oRBZ97^=rp-*Zx2<=93y4 z8nz>aSjakb|1^Mr1TADaj$!23P`m8{76?Du|0a$20Pq0UpE0zyxX%PoGyUaeZ_k_e z?p@UL=QvzkxjA`)6v(uDBhTd{!xM;6|FU6kU;k~02a53P>n~& zvDkgcEy>I+DLIX{BRV>+PZ39UQZO)tfiO+Ptf8)s9ix~b+6{6gptT_kl;2#?;c|cR zGdofb?QtluLqQP|`F{}3HqS{s9GwYxHg@Ftp`4vAV-B4x44gs@MZ2h#mj7)oh-c(l zx&Pk`jbl^Pl*!`G94Ic@{q?J1WP}EwTT6*mKflx08%QrtHRq>l==Idq*I%|@U7fgo zOT~U30k>}4w3GRjI%#(;*wG|C81t-uANyJbbkd$1&0j%3js5DZA@zf?4;*PoZCr+r{BsnAAv^XARq@bCZ-ZE9+d4zJb% z(x|F61b3wST#U~8_PB#7bj~0t`VX{{b)aMS<446cc}>P-`|nSgx>wYIs9v$_Lnr*! z5YsKWO8J!Ha>hS=RMr@P!1#Z4$PM4>x4Zk>pl=<6~CnVCk=EZF{z zv2p5TG9LoXZoQTzZC(E@qp|1MgS>&IO4o7!>&IKRp;c(Tv~>q9Z=NdS)x&rza`u1D z!n_rkv=HU#m!A|65Qw{Eb?TozXZ2ZX>8QyMv)kT&1I6bX8yjLS3*^uY2cVtbw3P%C z2i?l3K85yY0@^BaUDif>fuJ`BCk4|EJzM{0Elp1ATVFc^6kvD=&7E<$wD9S72nqpNF+O+jrSpt_~jt~dc4X#8`BL==^j6uye7hOD?!C&U(F-Pz1E zxy!R8!F%tkDbOvuo1;UJaW(m}g|TxZEE7_n{SkDceRG^%=kI-t+=~rl#avc>G6XNIN~%5Kw}E;?-=D*Yu|99hTajD z95py&Roch8Xq@qZ`{bE&!`%@50U0{$P}f!WH**Zi?^$-3x^#dA9_q7(cLu$=l{kun zbX}7ks0_u)GN;Yb*ke<``A1Qk0Z5R8=jQ2_9X1yXmc;H%pk)`-07dx7BT@;H^~0k; z#syo0grX*Vzg(zE|8W8ia^`zYus#I%=2h|Q_jb4Zw}04DR(V2cr}iD*69BCN|4F~2 ztpS=A|E%sL{z_92@yLb?K?1TxV99;-sMTxgy{?I4?!VUn6c7ld zkBX0S&;X;AApl?1KZPD^F(?GAePTY+{KWr_gVc?BQ|So8$O#aTE>QOxp795kkPf7vVW^Qh!90#1yuw1R?6KjA{!{`x(hZ5+ljjlSiN09lcmuG#!Pd;^H|fW_ ziFpk2A`Nu|uS>%7(Y@8j%@}#4S6%KVLw4s!5FH14WAnU7(+wd=1NuD%ZBbnCfTW)y z+M-nr-d^)bpn6iX0+8p%DVXlkl<;a&d5pM*%{Hnhq~T?}F$j01KoxhXno*J%I&Qd} z-jCPhcg6m?7zO=YojZn6=%oJCKlbJPyV#3{8cB_(NR!sIp&xEM#Z>XMllCE~P?|rX zo_4+Ai5&c?^@?RlsizL)N-z933E%W!!RgGb;147Fw0hzsXeK%t1-`vt>!|;Yh_@d2 zC~3!07+!yh_3K|)Ripa7< z?HXMVPXcs>jQxFa2wc?IBy2Kh42qTvPU4Kc1qW1*C^C-r=>zoVL|X`=P7v=@WYxJe z>zH_*Fgpu%tU_AOK0}zmQ&xi`c)*BaBjyfLU|KL!6_Go}_SGCBfApQ;r4vwl6CMDE zoA^%iMx9o0!C@8ZksM3|eP^rf&^}O6P7l4*dsRB)26B+_)=oCF@g~()XC00^&C}Ua zzihztoIW@}ZJAj;u%DuJgFguEmAlAP2BKf;w}fj*m*5Md+ zEE@j0IbrJt_-^Qa(}1~MLjIdyPHQU$3;(TVrE9m0QZGeAX0l(}Vl*XaZ&DT3ea($cZ5~ z$h!rST-GYOhh*Ud6xi;WQ=dHge)*{)1oINg7p#cI;`wx|hA{b~_l%z`5I1?&`GGCffF4pW%23q6t~(*vTO>1U`tNh zi*WnSv3*eN5j*j{r4Q0o_9AZ=*4F%0y)9hUOH8R9bA-L+GmSq-WEz9hB3rFEw606_cknG6j&cqtuwdHtVc%$vGg8o9yH|{q1c@Fdvzz;1z7vu~12?F)*hx13z zrd^yw-X3-;3{S^qNzi`YPJl^I=Hk`((mTiPp9F+e9LZNuKIZ@83|}ue^Ne7_O&)xi z{1!ouIr5p&_NKd{3Mj>}-gU*XMDwQMDcZBLV_rY$S z53Vp)^S)sdDmVeKX|_B|6O{6W(FrVY7%z-BQizy?sC#>BBByE0JWF=0LeP;y3wy_f zg7!kV{MjWvkq7WNufO$2Jz8FSNeL!PFjUCg@DY;HlW6FBO0S&r>Vy0KXNZv7E#a3xk83*dVp_vENvyD7fihCwZvw!`&7HuF<@OZTUT(0RQI7_(&69~E*zcDx>lO5IBI@DC*UQ8oF)tGF1%8wh7@hy z3m0|1EW{)bNWOk1B|wYv%;-4{|KR~b_xNq)>ASVz>XY$Ncj;GbroTg^bFkQm5m zHA{h<2%ZDd+Z>poB*OTY8hHs8X_4ukLZ1G6l57!k6(2@A#3 z+*GV}0Kg;Ks^EnpLKgDJQuxN-N~!0bed6rxe%|Q=J~e_ZH+gSwi;A&0Mcs>9L4?b< zO&pZ*y`zWM++6iMTUYKEAgA^D3wkuy zDUn?zm@e?%nVpKX4u{`kUfxUx!K$ghpOQ0%2wNSyvKg=+3(D6SddIXA+H{j?jJm5kufy4BLw{X+5Y$-=ed1lnW z!zg9P@*K;eU~am7-!+=7uKUP$&-*>Q+)S76in(rK8Ga(4YCZh6~RmzF+0aP zXu5oOBfLT(6y62&XrqOCq{NDHc6N4pVZnWB7kxbdco@+aIRJnP0>_;(yp2K3WAnmT znH@2L7S#jRrK;B`>wFm+{f6+`bM;v(!Y$pD;zuYF>C{9hRw1uX3M()Q-% z?+|VqbX^?@aABy84*22e;VWDwT-zTuNc;WOh)lyBBiEkqPt?(_oR)iZ`#-ELT(<4c zx!xS`LH(cbj*R~o{e&K#@BWRvQyagb@*moF))~vU{AzUzo({yA2DCjbTS7@uQB_?% zt@?FB0XA1k_nD6e<#Mry9&lx0RnhM4QpX?U~6(H$RyXVcS0Xq)YBTy*rQEX_UY ze&IjugUq`O=(NK8t^PJTg4Y5RmX|ABy^5eRB(#JQ#bP1w-ju-7($dxW)gC-AIalA( zY=OWs*QWAzZ zAxaGLv}kA+SfRYx(hC<=IQY@YCvbmO4yb`^9M4mMYNC;Rz^z?y$8csBURGob{h@%( z1``f}=vg{sq@f`I_G$C`I5oVF;X3TBHT`GMZK$4|HyOi{MrUerP62W&dS(y@otRdB zUq-D9AqmvEf1#wsb-Ipw3rp$Wafjg8Vc`BHUT{%{0NzK0AfP!=w$^M?_EBc5FT5`= z50Xi}DlZ>6xd{!4Vv>?NyEORt__pI^q#*AdYnq0J0?zZwAgWG@iokm{;Jr7Grzdkg z0X1SF`39BhP`;$?DY3++`eiZ#lr!E=Ia3k$GStuwdn6<55krj&4n7~I9xy+=s3CV; ze;#T|*G0U!^%!nAg&LsAh+0AzEu%dO6jM8!n@_;|G!)$3#R5+<5^XQ5gMucT3w^t*)oZ=k8t2ixg1%gc0vyEW&!0zKvG(@%x;5?s$XP+bQ}BKp^sOC^ z2Yaqvuceux=M{a4651%(IcRwa93PFLe09MQ(ucZh;stkVpT73mL!A(EkhvUJC&bY= zi&;)o2%KaPQ_Zd-U0lIu{jAu{+qg=+2!=zPC_>TuD(8uS6JTq;J04c5Wom<0$oW+1 zlWaRRK1(bX{^Vj)ZSXl-IO27F#pP45$xlNAHTuS%&;9*gp=m#Hl+S%pROl{< zORw^_UdGD*iq|vrh;+D%AIJ48h5%V+JEfL0lwwFpkH?#4-RwZaDrm`Rin~|lC^L2D zHt1KVY3u<;{3N$jIn9UHw_4ULG)j56UX4Ow49=-UBO7~G*Tv`yXyYErSQAREN_Qp( zGckMLIhTfaGo3=rlZW1z`g76pBZ*TEhmQk@0}KLtCLf^X~&;REl27 zVg<9;zg(twpM>PRS5oa8qcs&&ti4V(E39jZI?C6sc+0U%RXUt(LKP_)rl3Tr#=Dy! z(a7EgVb)xC;`|y7&;MIXIKOwN;5c+pBVWcg*t*;9p0U27=0n|${kub-J3EXsFB0qP zXk~9RAfc5x{g;<#G%RujxRpTl>BL8E>)COs9`xkUpiou**o+2K;67cmk#?5Nvg#Ea@xgboNTTy?p>5z zmVEkl>BhO#$8*nczD^fEyca&2fP+o5SHHG`eCBfKQRjNKNK`aynH+T6@Y~1kncuCq zD`*UD&1<#MSSPtH9486V0dj~_ z*)3k}{OONPcRiD@L<+D1r9|L0VkPA5sb?LQ$mm#f^SL5_SB@w-31_T(lmM}+6!y|F zb8%GYG}JGo73Nau{EclDHw6?IdL3+>`PIh(0nUJ_@5af9ooDh5!#(xBlV#<-O%e2k zbX6$|$=LnrK7j^gnGkn(Yy+Jq@=3kx0ay1hg={{W?wCU&YjmmQ~fzMESyn<%-&$ z<@W0Q4CT=Y`I4`%^8M+#^q^S^OQe5!`=Vx_n!XzLm7WX96YgGr<%BTLH#ImeZKff2 zSYXJ%ATyul;2vYZo$BBGB3nLS{aOl|;qIL8l%p?z&ixP2PA=H|48q{CQ?2js%9!LI z{_v{GqA|LFb>>I`EupifYwh+QgKHt!^YQ(|KJn_ii3iGeTS;;cF8gk&3$}LQf%#X+ z8{j*7-MF(oJL!)BZ5*>4|=j^^7dKKK199I z&R&5CY&s=ifNy+H??N#0<@u)q&RL`{v^@Kd-=4e0&?-bV_`2EahNQ;2XLFDV$!l}a znX|Qi^q`$0`q^Z6+%$@J{uS)VPmfRD8_gCk(BEXD@bS+d$$vPM?o61S)R0z14;Hl) z#}XMbpv%io@9@ZedPg-`qW;;!LgB6XS|-i&rVtdolwhJpB8B5OLO zsJM8Woe(;s4TXyUSLqC(V#=ZhoZHR?%f^9J~3yF`n zEKqHJGfWVapbtH`}s|O2xJ8)_w9XPHbk#p1YNh zXx^|;0;KcxuU}G%%eCwnEXZ71O2gOp)GmD)GEAP+o;H}R|K_P~I{n*$Uo_N<%(?O! zYN&0FwneR$<_`jf8Wt0?qoCetOY(4mrZ1>^PoTx~$*3ZaDfqe;U7o~E2^u7*ZlF)z{e;5l1qINqmj>P27PXMb~k6fl4aR4El-EKTV}3x zw}e2%fF6$^Sm3mj13Urnnon4qZIQR!wQJXQSy_dnTgMP?t#Q<1UQ9FMFVt&wbafA( z*wItibRste!a%eDx~ErJEs{5hmI#5iPWSszOJEAQn2w`pKO_~7EjxFf>T_ujvpjhu zJs~+cwva;?2GIe9TyM}s3O(7RGI}E~FVD)Iz#^a9COPmR?CiAYP+vivB14(8TS&(+n{iO9&r0o*4^2r}T^Df;cx?C+auYS04t8QI3bq{Od7s+=1=GY zXc-!7*5LKu)H+_DX^E$1mVHlH_Zk$8ki+6#Wn^S{`}zi?E`>1iTtY&4Z(}a0Wf9`u zu^L^TQT4rO^y)1=FnO``QNiz!{E_M*N-~4BrZS{o5<93IK*l`iEI}XSg~VmQZhQk0 zB1kj!k4iF`{}XF6J<10^qU?$bVyNQ=d~4RH|@{zM`i43ZS8I(2cu>R zFOEQi-C)Ypxas?*ra36*EcD;a69 zO$8?;)t}2jM`mhTnz5_v9X0Id*x1;%j?4CowLCw*(e*@(Brhv#Pn^mTI3HRQkwp_W4VfmM5S3;f9V|Rb>^GXIPqw2qOH3I&mxDC##$q zZ52dlEr(T%9ZNOx^z5H*U)CeCV1YbgSc6ov>RN8CtMAk-*-0*7p>w5mY!a_ri3CzL z5_lPP&yVXtZeD4j6z|F@c}(osaKdgHO_eBk$-@UUw34hmY^-$Nnt~W3jM}!a%n7~JRMIC6_UDxdtq9qd<^2mE;4Q*z0A zf&0;J8wr^=NZ8~CKp+yuHrlYck*d?(>Gd>J2ojIYuzS|%6pum&xzM(4)q>$UD6k8y zTD1xih@gmDx0a)Qc4g_*Bmkp9%;-2Bhol?Kmh2m?GZ5TOV|B`5o-&RXH@460veP$(~{3g^4uHW9H`Ob~Wav zfStU6tg`DH{W8^jPtxgU(IOB9PSE+QSCxRVl7$-F_w70_&dwI${T9$b6?y3>8>r)u-ZSQgLv%L3`8oKHn)7hKv{%<{*xVg%G|ox!>`t zbFkzFISj7uzzAc{zJ2>}>_(!=!`fYk0*2QLWRz6Mb)(za$j$98k^nh?8;7FNmZU*N zfMR!SuZm$l4+K{0X+wh*cu)I)QQI9YqffKhzh7^y?~X*ZO}<~7EG2bL?6P}&)Rq@*&Mh^ets+6rjv{~bri?`Y%bweH%pV$oB$h`7XQ2Jj^akC%HhZrNJb zb3~w&UEGpoy}A~tZ4ltCz1{J%b}*cXy&XI#5d#8k&RWUVgBwlAZ>Pn#|Gu;o11(@fbF zp(j2i=LGeKxHUcO4lLWEY*(}kI5*?jazEXNvdNLvtj4jN%n};7zl5%^Tv4(2i+z#z zCW;6s*5Zb)S~>U{I^z-NWTzBs>Z5fbbWK7O$La(X`rBoi?zi}_Q`DWpJvUO+aigZH z{@*_T?KnEn%H#vJ+Xl%~J$v=4RSU7pPdRjfQ@;S;;bpr5Ym|s~kR9M&2f4WG%WC^l zJHn*vw?57otT`e@X~hTwtfBN}d#@bHh5uvo(Dgj$zBW7%&WZMUa+MV==7tgcQ}qi{ z(Qt;d4zY&c+hj)n26Z&G%Y`1#T}|<6s}y37<24IYEax1!AoI5Vwz&)}xEzv!X{K>i z*uU!F7PA8i_Qw#I0{T>d34`lej+Uc-ZP|y&`O#>z*3H~N&fNmDFec9M%Ip#@^j77!8neN-SWTRittt77_N9Nhvw+N~ZJ?>22ynDB3 z35!Ki$cH_RV0y<+;|%v&SJ(Y(vTE4gYoG zdLMb5I=gVn6cw$9d946TftQG2h6c~-%|tO$moTEw0Fxd`m}osC)7Dd;MR_P_V`^;t z1l?U|g;Riy&t?Qz(sGMiz9L9ux}oVNG$v*q+T(oR!uXHG9%lOUcO?-<1Wt`nK0oc& zEh8@uE4TFkmVhZ9YwM>^6p$qdQkr?h9w0{&YrrvB=H={c(R#H1Y;0`!{%jLi@{!4P zcsy?=j!?>9zMKo2U(XJ@(Adj4!iG|ngjmz2&yq!|y*#auh1ZWD)))(5IH5V)R*T&- z3X7RJz~dot|At-W&uVXLb8vPJh5OO{g+Dr4-q7%9YmMB=E)75?;^O9$_gkN3O~tB& zaI@}}{e5SlQXmjZ`2EH23%z7gQ&Zu&9c_8i?mu6nbeqD(O=-0j43?N~O}h?{4byha z$LH=IDPHNOX|kZZ!NX=-MF8+y@kbaZs|1_IASbX0Bh?~gXS zsL+iC-s$w@&zbZV@!Hy2a?pO_X7|iyWB+OJh zHGZOx!&-(XgQ`y7!t3kfQ&I@$5gvc{#1YbFi9n^N%5s<<`MkvO6RVktbIh^hMf{2t zD@bWlnxQ+{OQkx2*yx{4i>6`_bsB6kG%N9R{VIntqv-FRCo{b$F< zfcWXjY2qOhtAda@A~tr`uE#YrEYalA;qMS46CZ_CP$*yhP3-JG2DXSJ55VNIE?rvW z?Cji?;KQZsM_{A~ET*W8Oi;^FuI}dMf3WEBIP-ucA|Oj_9D#v>#$K9#Su=#gzHe1& zB@umn9=MHf`Sw|gWOB`LZ{vLQ!WM8kiHq$x)Flsx78+yCZ;tVsD?F%JrSf3LMg%6;^B%e zTzI;X#@NB#c0&VhS8d73W6{#OOA+Ti1EyY$@!f-^PBo1M0qQAY10O8uzUIRDSa;7> z<(3F2D&BUtEi*ldUOci;aOv`BqAZ*Ez6_!18B*$;xHo1F^IC<|W&puh8(tJS7+_Gs z(9%h65w-&nq9|hVNYsXi43-4kBaCmu!^v_Vde zUy?vOF)W7&*netv?P`*B@la1AoG1OJSb>3EM-c@?0UXOV|Jwo!WCQQ3*iJJu#6LB4 zbw7_%M1!Ys8enq@OX#1{`F!*-$NU0sKawwG_5}v-P?0QwZ%fF-DC|;P^%;Wmr7OXc z!LSRK^aaUS8K0rw|C%IQYCac@EQ5?TUgC zDv@}av^Y|3AO>=6dbpCzJRv1x5TlqU=kISUUaV{r4Ak;mT(O7id;X{v_27+MiFy6ov z0R~ygm6esUFoC#5131l`8XGY;z?8`QzyoXrTlWM`9j-9Ti#4)XZ*tU$)Nc_Qo**y% z`t^x&7la{_SR<8)x$<197sJ$j!f{B7ml!^=uiG!{#dk8#pu4-941~fnLOVbv-(}XF zkB@kSu}WIT;bqC=B9Ij`!e|c;y;p@YKS-aQt%de!{9;_7O-xFP3~p=?1?)C_Ji5*2 z(gH^;(Ltg2ZRp1BI@6%~U_q(qLTKP|TFN3*@C-52vvYErQJxG#Zfp@~VJAPY%r~6< zGgtLM1|g#nf@G3DA;|)azhLwwi1ISK9?SU6ar1i^J=%F}&dnoHp~Ia;myZ__y2AgANe;S3SICoj^*xE!HhwJAEwK6>BE7yOQwqe$SZEBL#vJ;pfQ-O zo~n<0sXT<($O$aRrog0}$6X&EKX_m4pX=!Xj26am#P>VP%PCE2dm->bUe*LdVP-QJ z3=-(;cuUC)>tU9c2*vkM5Wq;0Fh+B5>XCqyxK93$8rTVj zhu~dG@gyTKj_DL6!5Dx!7h*X<#?FR1U*;F!K_iubd=DAo!|1Ac68;H$wu{5khGZet z|Ar>oE0M2(v*^U-u;TS+7s7_%G)ONIvoBzs#chPnDOsRfs(0F8(b|UwJ8r7;T~)a?%tPWur;er~v)s z>c~cs!93g~EoilnlE-~yd>5u-rX4=VA`2-@(u4x8`4+A0q9O_XiQ$D;*Sg6cbTKm0 zj6!k8-4dSpr~dv}IL=)e2t#Hfueb>(sNY+}WdmQ5yzr7l;SK`X^_*Y_6Go7+xq&bg zsb}L9y+9zGPqYk4!Kc91B8HrNC4Max%7dp(p(4a9#5W40?-9bWT7s~&{z043yH8N^ z@6JY{LJ~RowBj=Qi2Kj%(o2#kN54Ml=>R`I9Gv|{8eqlK zq!|TF#V5c9ICyy2Q8gFru6P1TD8Q@V& zqp0kESdMsUMB2aay*i6eLQ|Z?@GXwDysE6c^^}RTK%GDmz!U_M!W07-a6D%@#Yf%= zX-ApuLMQ^L35z?sRt$f+l9c3xa?Od(>;8l|r?BHH0iqZmJSc~OQ}cg~tom>$rIj3o z7!&A?k$LwH6kB<1KrTs@L>vTYh!iFACeLvZWd2wHb`!7u;qkBg0e!*4eS%Q$-!6*# z7h~DfSz!ats~*{0|9K BejWe- literal 0 HcmV?d00001 diff --git a/The Effect of Economic News on Gold Prices Analysis/Images/Avg Price by country.png b/The Effect of Economic News on Gold Prices Analysis/Images/Avg Price by country.png new file mode 100644 index 0000000000000000000000000000000000000000..d7b1cc1854e8139c1c53f228126450f7f87a2915 GIT binary patch literal 21705 zcmdUX2UL}3mo+9IF%e6!04hj=F&3JLQUoE1pixwU(yM}iQUsJL&0vglVxcG~2?UYe zq)59Kii&`!bOfbK6)v62z5hPfOj~Pa&3v<_{PV5#B>`@E-{*bKIeYK3&lB*|k^Re- ztXsmv!?Wzbk7`GGcs}jp;rXQG^Uv^`eK8_8@GnJYb$#b!4pz=?C(c^(96sUfXy@Q; zciQ|bSIe{KPCJ~Dm6Dg*A@S8IXJ^NAyQQV=|M3M<4ri^Ux0>|$;zPc0{L$bX56_Ad z^#4V7RTEG1@My~&Q2SonJ!bfgTa-@yebo=sJdc<9$@+h#enskY^DnaYf2sb^^u?B} z3+8rBwlA78zPE_$t?-f77n_m_{M>(&xjMhN-^0*2v8A8CwBoQoRNmk4{&R`rDzSZv zwT}%vhf6xnHQ2pXvW+y3ur$CW@I2K%U_$@ac73FXe|__9%%?m&-uI?#$K$kO7W6Ax7^wlUE4kS!b@W<>+hX@)#N!^ax8KYPt_rX#mAH0 zI6hu>rK-og)jt2Q$upazxHz$qg09de`}{X?XWkTQX=|@uZ*9-xm8I@?Uu`lEl8n<$Gt`RT z7t&;xQ{CBit~NxP!P?>C!OuU|eND5XT+l40a4Ap354o>-c`|#26daH5v~SsI>OEO6 zr0U~!&#rlg%Yl@T8?x3Fixvxix%bzl0V1wVU)Ss&OucKy@Huo_S@E{#$bE&evQ=H- zdZq#Fh51COU85E29fA#WZOSL!zv_CQ7#mt8%}~DW(R;&vtXyzoWR;}ro5Wb3^J{eO zpP#GsWv?-q?QPhhSmF9UIQ~|Dk|YGk^QwXQw)K!L*m_wr$&HJ~h;=b@XWV z!Rex%M^qOkgm#?#(b#i1*J&UrQ9we8`CQhbt-wjfx&MV)y=2?>i$zwu3^s)L`*($@ zsua47ZdkEr;-_NPcvaTIRI9Y}t+ldNWw`BC^(lI0;R)%wy*0PiFW%sO+-qU7acn53 zwqn$0y2!65(#*%h*rO*rAlb<0TwhH{U|`_EJ$XD^71Km6Bt9y(u(&&<2a3Rp|JG%aIe;WVTCP{zWr z!xhWsmD95$MWYo`MMEoh*}V1-k!#t)9%Qh^@oXXr+B=7`tEBkHUP+sa`4pym4AGH`h3$znD=SLaRO$~z?j14A5t|5gkgZpSD405cTChGP}Pg;A-y-&12 zJOy99di7Lmp1tzKi@md!oY`7mtVQ{*M&q0Z=Qr*T4K|h%bnEb*7Rz6FdvQgDkweLv zzF1%OCl8gy;_ltsDaBxo`{m)gRChb~e@QoqZ>qp<-C*W5rv81bx=Ce6ieAR4mV2k! z3zee2!uO4(*i-q8a>@L*m6C?{{ISYS=LgfeavM#>^+)FhGs6706a>GEY%Q2-v1PWp zPuA=rrSlaG&cY~#oyDue z@*(*hK1%8LdvDHsc)X(P%Ki;on?_}8l~+x_aWji?etAGE|I8b&A7?97+5Gb(MGnHQ zO($eLr-lmpZhLlOg+jl-_*uEB=Ww_gLodVB2`g95zh9Ui$<0K0y6qfqRo^^r(xPZM zuZr`-@1`Z^W!yi!?SE6`c0Dq(@^s>@yeFepAKpHcacD1AK;TEt%|FkUpj|2?W3Dza z@Gd6{p#7>2p>3Tgg^}d>079(x<#}ZW+w%RnLuFY>dtMU4-mPOJu zV>@&21im%a0arX~9=2!7fA5MtJD01nJ|Ks&e`vfV?_fGqGTkoYHS>WMrt9@F&5+Zt z?v%gyV{aF-cYuJTp_*EmQ>BPt{u@^#3R9Y3HR*~!Q40bTzCsUol>*b}ED|Y{;z@F)fx30bIG?#b8nnq9mWSpm(G}%N{VG~(@8#w z4Lb74uIeb6__qr~%{fRDtrD%4ktXBzC~D8d#FU2by;?FiHBc`e2Z-#p#C}taL^B10M3_HnxWueh` zLGR)2#Ujo>MO5`w@70kiF)`1caJ_N+Yu_GzhW};zKl%1h zROS=I9EmEa!u~i3vFt31N~;bp=3%)LkA4~IjdrL(*3Oxm9JI!6+Y7AGkaR2&FN;1? zc=~61=YiK-2VW;0V=r7-^eH|py>xDXcTQJZ`=mjHrF8L!A8@e`e*Tm%LKREMJG?@b z<%r)P-Q_jaW^F%wbLUfB(1(YMnf9n2)$8Q!qU>|)b!YRU9ZD6k8Vl1MwfWVz_b8

(DY+BA}#dB7r-YVBehII`ot*B;NQ z=XCeJs<;(g@?@i#YP7P)+0q4+2$Q!$L$4Aw^D;Rj)gAjzpFS;j`sJT~mdvo8hZh$M z-g79O?d3~babeBl)5AOxb-0IkY}2~?=lc9--mh-nyIk>`k^6nOqY!v%Ea!vHs489U zo}<+n)41kJ3cKI-E`OT;#+S2@_5M!uzGyl7&Q=FTHKRB7=pOSje?M?U+++S#Ua*r2}@dYv+8X3HNJLh1A!GPGsjV*Rj^~fH=&Av z#~@%g9ogIQt{4D`cUV(p_T=jnJ!y{3%Rdi1%*Ga{LU}Z^=7#m{wFVL8Zy#P1ywBJi z>$L-MTGV6}Z9i_07&q!&TiuXmv>&*STU^?lD%GnZB)bAO-}ZNDFxcFYSWw{pN2ECG z<;4{$LMXc?Z;L|wSxK*_JA8ewhliJ+DH_)OAmY~l;%nsgaMAf$*{2sjTNbEzu26A}`fy07f7z_VRz<~^ySrp97VGr~~5{HkOTTq`?#=7(3-UH}9P zLuq$Qvhe^gvB2Fpbp~t}XcIp{m_yFKrEHa^a+ZW>+Jmnz3$H{1F=a0tQ5s&&uX-zw zagT5hZcF^s;L8M!oi?xUzAf_TyX9v7JW8g@+4Xats(rw$S-sWKg2?8Y&LeG#2!JoU zD#OAMEtOcB^=7^cE=xsKl*Pobh62d!Vf#hBclr*`Am^?=*ZX|y=Y3rjAwejr`Cr{@ zz>3Q?pS({TV-P-LEhce;R6(V1ONMU-b;E~=v zn(*wC)|noYUdC*1bkq*ZgQyCUe6M$@MzOQgW1~f1-_eXUeNoyKs#Jl^WYPcPk1XVV zL5X=_-Z-EPzF&$D%fH#l@Y14>J5`@t|H&|bi)r_6J|@+9+JVj1u_1I*N~6WAM0PuG z>Cbuh>w2mBWsg+m`r}Vw$7-kK^^5mbgsc}t^o1;wYdZe(sK?yI``OU~{GzVJbGo4W zss@4hEIga?wEXtM*I{wC&DlMlxJAcun7cS@KjhjrhN6;f9zh-Pilt)y>-sZM9QC@m z>k$zZAPW)65wl$dnOP`D)#jBR2jtq_yZok^7w4oiI?Q4&iJ0jmYX>}Dt|YO+qx(vf zjKw}R*2EhuTp8+0aogl4neOR|cwz*;qZFLXK>+qR)$W;=$n-*unSJZg|HtKuYWWV~ zi;Gu;BKA~KyGl>Jx^vhrt6X4~y=Kjtx>E1?g1Lbd!9oVzYOz_9%WFzaLwI2wvRwgI zCGN!IUkPmFx1YEDzRA##>F}p3VB!AS+j|6CtdV5Ry65a$?gjYAS_%5H4F>B|1PSu{ z`(tg--54}%-t9UR#W0$WW3>!6`KE&cVKFcIt!<8tR=pTq)zb-t;}2l1xWSh-M%7=~ zd!lY^n!(v)>NDHJTl15?>HZBKC)tqeRv8-HK;wxHM|x}#!jl`%Y2 z$q&pqThzi!?Mofm&0850%)y7gXHK;0Usn$q1>jk$XX2ux44hOKzdx*CFullpv}8II z6(pfu?yvn%n43r$JH1wQ`o-QA<&RgW3d_H7K89%Bhf6=N zcZP|omi}&r1Y?eOg?KP~dmc|@H(7-3i9^Pa0X|4j$t?!#kg;pZjFPiAd^j|_Sk&t` zv(f^W%8>Q>-_18=Swv=yuSrx75*T|Xo>3N~crNbl-BVY*e_gg-KnY;^=q2`WUaJ%( zwgT{-uJodjK-yB2q7{0hECh<$XU4iVR%QFeX3W+Kb7oCyi(Cc;2;$I=rKp#+daj=w zT|A5w>jbD+3DmUKdw$Bqu4A@K!F8yK*Qy)9-e`Lb5>ERMng=+$at5nBgYEO0t+MKM zjml9WEaF4t0*M8(0m7x+M0g}_ylPpb|0i)4${kowH(}=&-}4n8+5P@cx>NQ@J?(zt zQM55;fF;&|a!D#A?CDIj^=5$C%*1kLV=s-2UKaJyH#gBq(G4+{(%T+CGgc`o?U*>7 zZc?;Qt!$Zm+fOgpRljNF+SK>Amv}1AyuCP9qckd!$v`2q%9^w*9;+bUP>Cwgg-A6z z6>C;wMax4#m3PkUT=g#E@PL;3-Rvm@nfq){WEWtmbA`?mZYs=IHU=I@#L6mZPXD zKs{YzBdYA~Sj=J1^J*?XRTrm@ZMc|M)d9>@w-~FYk$PH-Ff{)a&Y4IqfX8!jChkm} zQhLgIG3w2M@k3aY<|o_+H57?`~*p&|-L_PT-DP~g@A zz`0Ifz%c%e`^rL}a%V&>YjCTs*x%Y+tYtKi0*bH5TR@OzKGY z(`zUp?f%GA<@j$wqgS9@>sNhy$p4zAiXuJACU9Kyi_7Hv9T*F81n1o$-|(d?wd413 z*j7&L*}h8Ra7K1n>dFffug3c0!z#d8B77&B9>tuiQ5?(gT@dFOPtJxNwIvkMXBHlc zL;^KOsWVu%#$V6OdzWj==|rSPQF8!P%1;%j+JY!@fq0P=aH1fRPAK@!9_R+msDV4;n41bF z8;qoh=n}mV&nVszx_jVmKWgzrf89pTmRzD2%Fl+e7@;W{rMnAVhu5L>g%S}$ja?0G zqN>B$(V&`f`2k4}1ipwsh}sr>G{a&<^$j3;$!3duV4 z&p*H6oJza&9{d)#_`2^QeRXy9h61OqODf;ml{V*CTkDy6ST-P#Qws_dz|SYMmy7H^ z8EJg>fSk*~YcGcX6O`nf7xojQ9jdnV$vV2m#xc34UwvDI+hT@&K7U`-XXficU|HS7 zBezn41)BjTV?#ugGS zY(`qUIgEHVz_ZLobXo%IRdZi-C;H4b_v^Y5mdyy1>{ptqdu&lA=w^^^wiOK|r;LYf zh#rj$J6e@3fkb+UC<5JgE0n>UDybrg!43vz$DV`3fPMycj3c*pTVhd-y0gtxbZskw z*EY}g#m4TkZIIwBh#)^U18-@+7{#?cg(&e`JxY=h7-Y`WaI1A+%(){|kf^M{FC2=; z_BCL)*&!~tECmSWt5#&$9I#36tVye8&5nAa^2^rl_@>p1SRs ze27`AYSuaBI|2cuR;u{Jqf}&`W@u#B!mnRH8Ev0u(2(!YVb@s}!0U|~+HRMUmiLVK z&~BH3lb4|*{xIzZaLHwY$$A;L?eF(QH2?PXUV+&yxhd&|Ha|~x35I z!?LED@lza@ZFcjD555#S?(@U>f(4qN@`&HIty!d>QjL=Ma~{b^$=XRPMU-3*{luSg z4a=}+U)Tl_f))cub(L0aJ`%k7w!3-KnX8K*Wc1xU$J1cryD(^GfyYVI<}NnR(hbTA zpRL#+T)Dw>Xo>ey0ow?-c8|@_p4L#(k4N_5Yb(gy5e?yz673iRq8cG5;^zZbdA9LF z)Jd%er@kBos%7ljZ0Xc{!@2_TAq2s9><7_h`+G>sE7RI9vIb~60BKX{;K74OBk#4i zBa1;92qoN52JUO>c-fOjcSGYxCEKcI5f9H-GVg?;Zm&$ymj5LM2!piX1{1e8PkPQK zRpIZ)B_k~jD5n7;@zG06yz1pG5ByobM`eB}r|DFDh`@dN14)QtK66Kr zeOBo~FMrUIj!H#gQX3z1H0jYS>sYgfhQ=j``#icgHklX>|LTbU{4L6HIsO&!1=A-;l#6}S)tHZ!Ik|hOj*SdZ-NqqY2P=maR$DfIF3oJPB zdMdsog98i{y-vV$dXSN~?-wTapacqsZy6N&wfy{tqvb-78ox=WhK_Dfc(xW1~BhBsTZ-^zcgK1^RDN`QNdSL;|jC++P9pOcc4*CB|p&{TTFODW?+fd36H= z19m-fvCdDDc#A~zF0mN5p(YtNGnP~K;oak|-!Co?1ksbHqE`U9SD?rgSb&)NY$K{_ zUf?#gk}f1fD#t{E?VzLxo{9yT1269B5L~mSoOmguqBB%&o!%!zRzUX=$g!?9?am8= z7=G{Gy|=vh;*{v_cg4uJV`w`_ykO&>WzdSVpG?x?kOmJm%gHigF-gvk zC*<#Psz;T==MJqF6s!a*=Et?VDMOqC6w7(xInmEgLbe5HbQq*BX*{#y{=gN(>uBN)!Y!$lo7zsRE(60cp+@9C{P?^CWx4p!*Sw)CNNkMya4 zG4&%lNdGr}NHrYz&*i;`Ck zad&O%Ut8jWjdJ8RyIwTpTb2hJ24P-movELOSk1$6; zg_?+JbUxi28@y+_O;$Y#@5(&-%`L@PR5oP@nsteqv3|!@%m8MXzGoUz4TM4B>VO!) zef5)vYj5rne^yn+XG-rYJg}~&GE7v|AVM8lU_>&9x}8y|qDzGp9Fyjz2OFgkJL4IU zC^$FIQYB0Haa~Q0gwY)~(bSxp-QomLq9AInoSzDWsVM*VJXvzn;M3wuei-Byril8iU5^90*MrhvHVfk|&bv=0n zjlZNeAPTAd8tpIe@#1>p`;$z37bb}>l6cq&c_tVgvvNQuQO-gKM+EF};fF>=>VBrC zN{}9;V@z2!^&b)qv6q@#N|hu?61Jj-0d*`2koE)%k7#LW5nLEU_cFcHhE|}w%ChRb zUfwQ!4-XHdRP{(nBQ>r1WNx9qd+)ZFx81->-GILmOUVku@f(y=?hgH*Of4Vo%Tq(n zWi4*uOa6~wNAV-rS@qA6&ws}cSt!dtzKhvgsOF@V!0N{p9AI^2T}jf=PrIS`e?PbW3SA|#FW5j4p#Q+0*ZO;e&lRH?eVTJhA>^8$JOhbnhk zfkUl+YC&+xb0mYcsU57s9d(_{0jYC{*6z5sbjid^(ki{s0V93O9mKoq`mrMi^!HFa z2-P1QVNv427nM_k7u4r@zPv-bGBOt9Nw!2s9-?O-RCF;h^T*5NgKzKgtN^1fd1gy! zV~wPN0*CYh*yH5He*F2tXxG-V^^UIb~e0{RAJ!*f+lZ z(ZWk4>~+NVU58uNJU<_cbR+}vA_NZjQ9(x!I0HSBcCq|=q{XP+E;j5*km9t7If`$C zO-gAcmQ@j?JPkEv@eZS-7Uu6y5aV8Bnvpz7CH(wphPi>nZ1SK%Qxg?b-|~-n>g%ER z9R3q`Nfn-2)qw3Rkm-cm(F7+xaicKald9OOtnk~}{t+Am+VI3OWLfs&C>69OnB z-wxGPNXgZ%4UK{^q_yr(-POuaY&xkN1+3a!L3atX=SqNIG%b(7`;H)q06gS6o|4*fD)cvn6MITX8u+f%2Xo7w5z;L)b z`m+S76Co#hx$N>kbFW6}j_rWY6zh7)jmIu|^- z?-H_%-?1Rq2cTIjM%odzr{f`ZW`XyVeY!&VOB8Q|x?Kpj2Zr|dGZZsmNT8xV293QO zI@U@_qrBjap$cLYFw_}Fd;W}i1C?vrG&AqL1+;hn>K>6Y+=SLi7qEON$%$kT5wpSe zx{%v)_7W5Ax-x3;5wzcV`sFtx3=UfXjppKlk~-5iUG4 zzoBUxD{Ia556SqjX2P{r;CZXVL<4_9 zRgE{p5|7KQ9Ozb<(k{8Bpw?20nJ}3j*zsf#HIa4nOmdYi@nsKePT#kxaVUI$rvNfJ z=`=I-yyOtfg7Ui$7`Q7rB|Q)#T_y6Z`IFziCU}fS#ENn6#Y=_0B;}5z+!`n_W+e`| zIDHX3jMzP%uH^L+|MLQ+O2}iy=+$Xqb-g^{Jn4igTf^{$Fl65Q{05goi@3G%!`Nhe zVi!K+yMt9OhVwF&!mFSVHfFTXl1!eIcsme)fA!y(v#^oe;+*5K7qCA!kWRJd{DeO| ze$r0!^Z>`l$NdEHF{x)FY;`~AcBU; z;I=~f!*|6KFE#l2odBLIiRhDmh0KaU#&9_KI6d7IDWOA&;J0T8Fd2)AGKdkVXQRc; zBM-BUrSf05KFzjEntOwdhAI+7UPlysvUGiW_+}a8#`Tb)O}o#Nq#|3Ru#wwEfi_kA zdJEJux8ragkL&_ul|Nf5lqn|9O|vCy*43EdR?z}AxDw6HrtN3nd^tj9MfX@JkueG~reIA4 zZ~gdme>{OJ`N;sAURqpS+}#WUGjH!R5Qw^P;n~Uik7g0|o#^3);JL|Rzl-qmQ`RD;1=_j_?9u4TKNOLX z1|JB~l>}~(5JKp=QoxW!456UVbN!gEa|o@Mu2K38X5#Jh+qkg+uTNLn9F(NcXW?x@lE%L~{~;A(XPCG)Z#uGP^7RbZI@6xKgrvM>p&6Z?*-7`cgKiTc zs}62QhF!yZr}(M6jFd;eVnKm3{>R#vuIPZ=gdXO4>Jd{;L7}wm1}K)AYKW(NJni10cPs$Z5b915s(OGPc{bNj z2D)H+q8u;!&N34(LT@AxE(po9WCz^<+tytDU)dOc1cEp1-}t&0JqC9nvl3Qy+oYkK*(8Z^_IvyyIvJ3#pLe*^@C)2}z9r zqYx8AVs##F*_F;<&yi>F;MUc6d4q1%>Y9yWFiEW>`w-OyD!+IG;T7t1Kf6nnxZyl1 zaUb=j%*k(aB^ST@F5%uG`Cq6A=_>!5G&QTI)M)ec#0Rg9=+y&QMkkJa+R(z-5|#e{M3mi zR{C%dn^>w}_V|Mf3Mk6v4=yYUNT$@a#v%8MK9b#j|Nf$1BjP2}j14D1`STmHT`x7H zLy#e8TRr-y%^27}n!QRrNf17Mv@{6;!tTyl*?0rY6K+_+V(g9ME;%i~Fu{z~QKOca z5(E|#i-S&!FG!qH9ZP*>zOs(vO1QW=_jdhTg>U#3`^+&eF=c67Pjk^Q))D%6DT z*3Fu?g~|Ox&VxF%kbhZ&g!~|bZWku)atuzU_$! zf3VIz_kJ&n;0mSLVt7fS3t$_M_naQ#GfBihQN-NH?xO2NA(z?N4Oi+>!K`E~?|$?y zls_cyjkh{5`ML*xO%*6KarPWo*#N8N377o4vw=th4O#Zv#L*wug0_i*+0rnJ%O z|6RTPL!G_1#hZ2INmW?kACr4TGme;i!inXs>HnSP#lNPF=?*%!!`a^i@q_7G({q-T zFHEh}Wm{Gi0N0Wg{d5qe1+yfyJ|fg%o9`rJHEnL{xWP|A{_B2(+Q3UJ&hh(c4YGX< zZA?(WUf@p<_KVFiUy@CZ`gkrhr1T*rRf}GO3QCR_f%{$%%}K0c%_F(!Xi<+);@U2o zUawM#Dl(YJfJ-$|&#ajswU(}Kgzv61ZSHGy34Li;hb-wMuPKU^Iz+u85ND?+UtcbR z7*_m*O|Th8gkCd}rIN+zvm;)vb20P;IqjnP9!N3!aV2qvx#f{&xNM}pl)D7F^i^!N z6*6$6-02|_WHWzA(@M-G64Y`kcX=Opfrhe+2>#IEoZ>Qm3)WBe&MC4n*~`$Yuck)G z_Q7f3y>#8qEw}OY{V<~roW-AxCm2dv*HA~)eK@zV^SNwoFb(Ip(8yNi(X@znELdx> z#qeY5j+7plj{zBPe9mn&{SP-}{)5dT9SxK3mPnqT{9o2{o@$!%pKIKDfb^WqUz2i1 zFC}Rlm$dxP>pA}!4d}n)Jy~cCL-;{>LbFgulVm51GMJ!>Aqya?Csf~1bg)o;O^?5! zNj*@}dpbtjX$KvzKPvbox9}IhEM!p=qbLJMbU#c-u#Xm?1AmMwi=wA|gXvGBJg4BH z-+87@VG5g<_UuxT-8;FFn|Ux*K(O0R0R#G`zLv|KgR`%*V;I7IV;KlQo9eawcvRHH2VaqwPY?F!#r?|S^#q& z(B4W*DU@QO5azD{?m;t5M1=OMm94do;U`E#V|!y5DkvwV7``BVQi_)=e|S(<{}B`z z#x$@s;N9X5ys_sR85NWpNfLRTtRtQdGsFyp4zl==m{I|MTO2GmNmbM-H{0|t`|IY9 z-gw75-@3{z`nFNK=S`yu|JJbmW6@_$Ya2z?kKc2}HQzn-UsQ|#wes=b@zLCxe>bNu z_CMPQ%Q`q2!<4{~3n5IWO;`i%&zQ_UmU7{i@NF@^&@a*GK~uRb9Dn-h2Kj{0bp2=r z0;mIygp69)Bz-A&FVRv20@;N?{|}oiPq`qIVI1t%WAR*Eu*+mti1{pGM~GX5r3`%G z7;>mHpVvutG);J>8QByW9-cO-%EO9%`SNI&$y2i(s&5I&mDsyOCm7lLeo1t?V7eD zP4N?SK!4*EYxuxwKH?SiVMY^@L1&O4ufmE*g72t_)MS?u$y9(q8?S z?$SdY6UeLNr7sP$U~#kq9eqH}D=6k^pq11JZss9X3uf6Q4U4tVTh7rcka?O^FA|`d zAn$d-{AhTOD3c7c+{;E8;Pxz`XID$(e_^B^ zlS%-%6bNJEHmTB?&Vrr@BXFzu7o8QJXrW>`9LmTzK(HLeL^SobDCqr2pRO@aeEk7pONOIp3cOSj1`>qPce>`;?)Y{ zK~#7|gcZt_;f&7uWvn;jp8{3NLvGfhB>ejjGHx@dP;U! zV;0mvDzXae6(muWJ%r(yCqU69elpZ<&A}REbZeG%vd$I@_98l~#l&dBXWX7f<7kLg zJ>8;M&x~(96Fp!nm_9qi8l8eO?nm?rQ5Pc{GF!s$)iP|~hPfL|l=VtfuQ-iJso6YC z9;!u3nRF&ZnjX|&EB*+CaHAL%7~bJe7cUQ{N(UE*0D)x8g?C4yWvxMzGUT`}O|xxG z*Mcxgql?K~V=Q-^X)B;e-H9GGZIl`8N7P>YhIY7LR}lg{3mc#>%%Q8K_a-EL>ZQ`a z!G7F(zEWwUDH+w_vPpg$B_%E%1l>08Z4|sVuGEFCo_-Ikp^YI*Q_P)v#X=w62icP8 zO;&7+%FvKe2FGWO_qvEmx(lEnG#mI@G735aDcxAWluMg3`R&m)_;wGZ6$^5~V{I#` z%96Rz=Z1yX@Fdb9*Cj`?`tchUtj&N&nc3c0R&urYaqg{1?@9vc$Btwaeg+ zrwJ1aJ8Z$(DOJ|H6?KqXX)P%C)F9xgb4=SE=MmrmN>22hVDHeCChLA1Qf?gY^$X5}iUTkP3Fl6FgdeGWNf zKKzWgDh0D>fGAu0U*Y@&-aHv!QWEly4)it7B7VE*Tm(!{t6`9_bOBm^KnJT=p2T~~ zEfauI$U8#NBwW;lMt2=1E(eJ^nEFdFTdyW_AF-z~$UN$RDTv1`YWk70)~{;CM&T~i z{D#Zt8cd1w0W>APo$JDw_qR#dJ~YkV1RpI;vj@WYnL4mzHXJ6PFjg$)c$rjp2rbei zwK^u)SL#+gYhd_t@Pa)w$cB5BPrZfS&MLC*V?>868GI49(C3_0r727;q-N4&Q^yuxzdc$!AE2bS@LCq6)dg^HY9mZa7#Vl$kT1r7QTIgCi!!a1tw9UW-sdk#7 z%g;sf*fWi!ajEHy+1|oLxD3)A84K+0)$I!!#$nurfbE{Y~hHZ>yqzV1EzowIm z6LP!KNaIh;i?c|DD=}m&8MVtS3b7zZM=_Aclb((Va$G#rW?tVgrHV!s8dVF1qdS0; zzF&L9!Yge>AC1bx2uluCraibQHSC&DKUV2hj6=Jn=^}SDrMh6WGI+Z>^3vKp=bhEm zsH}>Kk&A-d<9zJSSWfKEXa%QVFEnt1_O?OPdqRs|L?$}qMBd723|@5s0#u83V23(m zzg2v;-tJ3On@00_#nMJ8)YTxGbrgOD#hvgw{)>7Kc&3KntA_R#Gj#a|-6vO4Ja&57PyR z;8)lPU68J4VJlwKY zW!_HCsk4klGY6O-XvQ+ih>7t8Iy99tH@O}gqcQ+2Na=z<|(FhUQg^&%bnz63TRw}4@7)7(pC>}pJMYw^cMQA{RHBMy?C9{?$n1(PjIcX-T&RvquLGBoc^ zsB#Ff!T7j$rTZTT`C)ggqS-ksS`uA+fgQSqPiaE(^`FfA-Ba9`3PdqSBo8-<~JQz6g_u8_Lhtm-uG+-Ard=2xi@Uv)MyKurScjBr z34tm))GldeRD8=+=cwvS_RfN!Py*wH;qX{NL2{fG_0tvo? zCS3tx_EJCcfXx7chMKfA8BEb^j39QZ*U^)_H;QOL1;8a{(P2T)b}TwhI$Y*;N|i`5 z4%A-D!u6CRfk&84T~=j%O*_etO;as|ugIvt&rjwUh?l3JbOJSOr1myiAB)EqNR|Z7 z<(?mcoJJOYDuE;fnB%aFAk5P3NB@92ZlNeFYldtAj_C`jjB;o7QST%jw@m{zbVgZ( z20*=4NByT$X~-fZInKl_COVN*nqUmhMe(G+5rAnzhT$F(0@GZ{?;LXepuW)&JoFe@ z3!}bfL(_^#%>CHxG{p`(8!>~RVO2A1?wzMzd_{C%bByB;|LfEa%iB7g5qDBWcplDn-V^fYI`UcRtkI42B#h&XlS{RY6!lS)LfSa3{ZNRv2?156Ubi~S(nM@L7zc0uRmJE`_%oTEbvz#7+5 z{h-NO?kQGS#3gxjbOo7i%<04zP}Z4h2cK0qvBVa~N_qSdJ53&Ga#lgD%X!fQ%MYgy zw_1+-p64FZLS`%&!W1ZR_?aDN8Kdk9V|NhdA&SSg1tCNzM>fR0fRP70L zLYuqyl_STi1B<_(X0ecBd?#KdUQpXvh5nIb`~qJ7Jn@8E=@k$n38 zz^4}yt}f!yu!LmwgvL<8Q0yQQaw`~;+v;Kl)Tr?V43bqR<vjHU(cfKr1}m+|<7*qru-`N;NH$|ofG z(YYpSYT7Bfl9U0c<2M8|iWZ`G2B9QMgo}K7WV3e%DeA&JQ-Hreoy`CiK{f^PrV*qY zVlvxK%?~^H8h!A=&?ooMC>rab!9C=^3aaz6eZ+{!I_%)XjArd76Ce$^a@gcjc>gM~ z5-`IobC~=DDAxC$)Gjca$3717;M|xl>^FasiQ%Uagc%9UY6zKu*BcR9NoO`$v=@8K z8oZw+S1dWgaE8W~4ni!_*`cxPcb@u*6idSESjaI-dZY!g#z|%YG!nee#+Ps>;Sb|n zj6bS6KvTGWU}1&r9oP*-s&MQOxi?IbcP~0_Ksj~w-1Mj@4ZeSV4Z%$^7}R2Pdjv>J zr88#GOKdX#~3` zoqfk!MWQ;jt-EM^oDQLbmrIx;l4dUH_pc)b46od^4u=A@{zs3`ro>gJYRy%O5%h)68fRm9n3_1{q^&(59((F=Inwh#7-isADIH-u7um6Y=o zi@;qmZh&DU%9BYAW_>>prgF^Kih^R(i4%U7bbbo_c9kHhqWr3Fau+D2Azrp)!2QZ- zK8)@aK!Iz>zDiqzj-Vr(IOQ{v`!Mce+|4$^L!v2fKy4K?LOT8Ur2H{n&Kd`j;;I~A zlOX_&GWaF8r-rBAt*J2zRlyFWGz;ehaJ9jvlh+P&9j%yx6{9&?-XjTNGp8eF=pn_N zA4rn%81L=}f}$SFw`lN#>sqU+skq1D^bxLNO1;R-!e@UZ>mPRl4@WO#zNmejpb<$Q z9!G~_0X~q0DF$dpLspn!2o@fPnB|_Q0yrNJ$2-}~)c|ln^T>R^o(_wl!^xbU%T%gi zBX`057epsofmr7swE5fb<4*amSYE8;eyBPEpZD^sUSiUGFJ*P^y3#vvG23aZ!LKyZ z#MQvq@gXlkk0w0oc4YhFo7ZtlGbjLp`OklI&`Ejoyk8KzHJOTTP5-x*Dz=i zs`xDp@R$3n5PwNv1()tZ)B9xhqAm)1ZWeq=nND(?!5b|wnHrdu*RqX9ru;P4@f=sL zvTWw~ezue+vtfqLp@XhWRx%PUjzxaTBk?n0*7j%ej}g2ZZp{xP^EB%AD)O#*A#u+R zwlBI+ABk~mOlU*(Qh<-MQV*mgE literal 0 HcmV?d00001 diff --git a/The Effect of Economic News on Gold Prices Analysis/Images/Dist of events per date.png b/The Effect of Economic News on Gold Prices Analysis/Images/Dist of events per date.png new file mode 100644 index 0000000000000000000000000000000000000000..4d3dc5f94f083065ecf89fde973debe9532dd6f7 GIT binary patch literal 17982 zcmeHvXH-?$)+Lsum?;Bb0!jr05l|5kK`^0$fgB_Xh~ywqGHQt>sOSYmGLmyfGN_11 zR-zJBBqt?YB=_7vg&zIA9;3UzpM6KYs{7<{!ai%SHRoJ&d0*=Cx%F$duc4u#SucM6 zj0_FUuMIRb%LG=f#GhQ3uMow51TDpsEM-lvTiR%v>(E@%v@|m^wKUS#`rTT`+(O^f zgpWsn=g|J&^(-yTERON=8vlI&kEyvXFQ;0kGfuMF?EDoA8X7uH^1o%#qEY%ZG-7e$ zXHLr93>a*+m6PwBEBR5q>>9()Rlm`n>0ER4geIH5pWD~Rk@|i4PxY=xC^hcl^4lqM zkW075KCP~;2i7ga&ES*lb|-)B;#V4zbH5rcesx*D3Xi|=+3{Qa(xFFwS6aUK zXGSNI$-3b4(dFv;#c#>WUTt6ec6Iq}{>5)ESCSKcmfXQ_;B}F`mRqp#G~My=d(3w4 z^75?*m3=R=J5oRCW`3J-oTkbrC})_IW*b=zwFn*`uag~_nD8mRR`Yn*=>fG(G&CJ;sg!v=L6#_a|9a*q`K$}Ei8 z4m!=;tPB)VTu!^8Zf0_H{LN-bRU0E*Yrj*QqH|M*q0QR3f`T6%CH>{Rh3PiiB4Rln z@Jwap=5if4AQgDbswP0t!Yeq~bTmaVUg^1X*jaD&6g*N+z#Lk=o#47|Td24vyZ)zC9fP{)C$#Rbes(!t#(T%XCHs^UqdIpB4w(FhW`tcjqg^O=~xKl9oOvj!*d-xrGe%Bhr(?+QI zU3%-mk~Gws8+XBnhsqOCR~aBE8x#~&R$blrA?)0Et4(`v>E7TvFHYI9@kWif>y>^A zEEdIX^b!&hyH%Idd}dg9iH&syj`sW}Eg$m&A3qM^H*Dzna*su!yDBilW>`HtJ6oI* z5D@U~o7@X$g>RjmrLC=MRaI3wc0v9zQqOOzRcmaza^=bzIy&ATKl|$A`hS$L@D{lZ zT@D;ADM2?L3nNkK$1fWp;r*?*H^y$fuh&~q{mIz0#fPE%33YLqLZ{h^ z%p&qaYlf?(4c~{{s;Q}|%d@q}&dv3onC;+eaNDwFOAq;_!oosfVd1)L3tc8b^EX-- zaqhZI({`|^xh{=!B3~g`=j#mgh!8hmWGdZR~xqF*>?4FPHhW1Zm)3K zb)7UG>)Y3_yEQa4GW2WDiq8G)Sf3Qt(=tsRl=Wafj<**PD<9VvJUTjn=z zNMn`wEqkQYvdmryN1C=5AfgUA+lU44zI*qs-yt10ED*1vqT=M_WUsGoP|DBAWi&37 zJtSo)aN4OiJ~Sz9$+ypBcKWH=+1+he@$8`8M5|3bUXMlACI*JcgW7M;Q-YkP^ecl! zHSnN{qg|DiB}c9LyqYpilis~Mf64cd7`MucJWaKZw-0Lt+8x4t)a}HpMd$NyyAjWx zZFPVDoK-@mxqe-d6e5}5cH~-yVdG^__DeE&%EMZ3R;}N0B>v-1{9EsR$VmjQ5BueS zXm>{5Sd~nZV^)22>-%%ezT9TE>)A!_A>V$Yq1m*M+tk#Qybjr@%lwTZ&T|fvKYwx@ zI#i=Nt!C3|Riv$fo&V|6r(zMYb~P;cwL`vRy-~po%@ehfqVmlzjODYe%Nybbd+QSk))2$EOF<`~)o`bFBI!C)(^KdGo&CZfR*rw;68Rp*~#SU2yY9=%&q^ z>z|*dz2tx7lBDQtdhxRx9dBc>57(?-{UKc3^YFEIzeR+HN865e9kb|qP^@IwJ@8Pq zf5NDg!d6yZUi4t%i_0h4W`C=`)Z>+Y%BPxg~N^*H=U``;tlO{%xkFpAj2%O{!$(X# zb_&*HO;x*`yAqfM=LTl9;ptfPB4INs&WcKT>+r#wI@P=3(g zmY=J6$oBz~|FdS+ZOCB^#zNKu2Uxe&MoIEoC&nSBiXUIwPtuQdZw=d?W5=4lkBy~g zQA0w057RDrBp}>Yug#`5>iO)M9y22olkpibu`2`9vlH#Obq|rLcL&xLaqQoJ_|&OW z4?ccW3QJCYFU-TsTfJ(-h9gbs`r0O3eteQ5li|e&bFBvr^zjkyyG@SLF$EGjA)2U{?4?Qj@ zIO#WtchaSlg3=w|)!S=ZlzB%XR!*EURX(q&(k&$t{zcJ}e$Mjflm>WHpUuLe& zaH2tdtUl_;k-)-mg?Oc1xToXuGouWHxRQ_N)+uVUDR+~$mX=)9Wu{TScc@q82K>Y(HN_EaO1OYJ5*ed=?p43AIsg!Lg7 zckYy+4%^koDQ5PGt=P3|7eh0E$eL{{?>62NFd^f(HDK0LK0Y-3hbCW^E zs*93jsZUg!cAci5>o0@E0)%GsiqMNl;OI_#M zwVsCpZSPZc%H1k`02%z5`EabDpkU){Yh_v4)MonSG-kTH7mC1S;rz5{=eKXsCapP* zOdVZak%%@fet!9OhtY==PtS~-KeRFo>Ls`o6TQO1IxbaPjQ0i9jFd3$-@?hk!6AJq z;)`AP!MX3DcShKM|NR7=$j=ZFGOngn9rr_r4vjUanEIA%NjPgiJ(x+qZJTXn z$CiXQ`$lvNkYDY3UeU7D)kIv#Fz=MepQSe2^(SPG6*Fo?1AMaOrOr=w%wQ{fp;%|O zJK0wro4?5&A*gFJ*u*B@)t+|y_AjKq7S2-r)$MxO?z*~`6&0OEvX*ZzaJ-OyC_On@ zs-U1iIm_$||FkJ}zX%PD)XoLOD)HgYdu?rP)1y_dUY$%($yDfXNZ{A6VSUIVs-9FZ z6)PhvOTT%uMeE~o1+lmYx2>+vk*=bFG`n7ud2=z^f6g15Hb{z76ucr!5}rbmdP16R zwQ@WU>SAzq;o)Cbtmwt&Qqa_VUL2cIBU1fvY~YjZot5irfKkYz0vg4kdUef(s;D9? zOmcpy+Ac6Ex$DL5YC0qtsi=Y2}oZ^ql$)0fet@ zb-jJ(&Uj|w?4YE^J^s0$_Ae~DFVBvY^ZE&x1{IgDNpv#Qd(!WyfkOHL#g)MFL#q>) z(PVA@@c?{4N((9dgTHA(49-11)H&B}*eSKq!-5LFx6IHWAduyZ0Yinh>mD4%AM_bNknzVlF>4`>KK6Bye{trcTqDFIx ztepGyNsv1i8qU)$@cv=2S28HQHxKtz?8LBQ#foAR=dtl|`4cBxY#+5=l#!tnQ^$I1 z*-B^l?8iQw>%{qhz8O_c>TZ2|sr{QloQLR~65f)6rDeKurU`eiGuL!tB3Rex4$UO% z{K@99b9A`zo=SoC{V%G$xfCS^Z8p-l2(9Jy_7Qyyl>yW zoo@8$P^7yzHS$2Y(j@ymBPb!>?U9pxy zDevOTrY0by@Tc4=eW(^d7x%Vo-1r$F?(vf9d$teU>kM{ zSv`PQ`9dd0SikU^*7gqm~n`RqS>Qc>XDmT5MFXlQKbC^^F!8)gsdu!MJiPdnu2YkH-!dOkdt1 zU?O+s%pXtpU(sS_+`c^)OVx9iQT;t`xD(|N7WWE7xczvy$73tj#WgK0ZR2mhU7eX7b{24& z>|}JGEtu-#+9NF7VrFiBXaRN|Tvv2JIbBb)E=gnFZ=Ap`y$_*xZH4&x>mOfp7%AO* z7VGk*zuzz`J9`_GkoDmWEF!8#^ET~{jnV4)IbXhh)jDk4RQD4s(v4~KYzE58wv#7M zGH9b18m?nHR<~-^sslg)SO56qkFBPKvoEBPR}NmLY-C~4h>rx=+QY*$L9Hv?1+LbeRGw%_TP}|r|G3}%|TaDSt4y*01ntAhc)2^&xcuQ}=GZSqq zf}N&HZ(=t-1mW4v!^3kH*%EJnZVwwG1 zvbnP2@>TDus|C(J*s6Kv%$cq9TndLl9v}Sq=caMq1K0hM%xkj zM?erADh;P*MynrULv2H@aJ_f$-p1|Q4c?TL?3kVy7Vyaa5RfmuUW^622+(NzTas)X zuu5-{oZJTy;>>&4+1~xPdShjrSR>0HbXTd;#iixTRgY1U{I}&q;4uOvTC=s2U z$1B_+EiLWp@9!_2q9sO_=dC+$f!-ab0%V}KNeb8u=y; z((*BPC*aDCj&1*2jpy?}KVCqJM9BG<$aBjxe=P^ynzd`K20k8?k5`gr_bhGeBnKgH zU0zr8{!^MR{cpehPJ3@hlK37aPfHwDAAhB`O=t0#kbtA+-~NOya--giNi$}avH@C2mPrH7}Lfvu?4whD&=d2PA*w-LvO3Le(obH`l?@kstg|4N!_f5qk+A7okhps~WK1 zBAsXZHHc6nHvRtj=?sTSbM7mtXHcVSK_SL^!aV$@*REMpm!f@6Eyq&a|A=u7$o^rd zQ29UJ?#P^iG(|pU_fqVW0n-Ih*;IxL=L_~JCK{PkmzI72JPm;y6a%>fD2vERD2(jJ zpHjsr=|CcbpVH2)W!Nuu?OHhDxuCVO;^N{Yx#aV#UOcxAO)jk=pe#xCT3TBBn`&!n zEGI{F+^O&1ORZSB(f~}E5?<*q5QlI;DdqFH|L~!_iAkdMaGPVRMOSw>mw-Uy*Cp*v zsVI?`S1DcZiPOxFbH>dt5|lKqUylq341^rO=58%2Dynn+x?hPZQ!M>B{PU%q_Fq~4wjfAC)+#w8qX2ty`-|ebd(YQLN#WrQ=l72|U^6MFH2P`Be6rhK58n!<50k zzS!_^RyH;^HJe~$-vp(U&<9+({0?_c%N^hU`tQy9>i~7+m&LXCY<>3sMDtyEp8rk} z`Tw8r|4oRuUf*!NDj)_$h=e}k*6q=w1`r*?p+YD|Pz>Y|+aR?IS{QI)@j(zOlJ&qI z${QOM_ndw39!1Y&JYp#xHfT3qO~C2=4rtzn20Mn*7EL7GZ%@vp+fSH?*ZhZUI>F1q zAq9~G;ExS#S{%u%7TkIK?GDqA{glO%o82=@?JgCv>bsV5+@$3w(YRG!7)d|e&OZhc z*VEx4ssQnTRUAkNK;jwU2H1Xjon_ulX}TU@NZd$cVrS3x0bkc$;LQ&Qn<~W?VfIye~|Y=*p|qN0doH;`6s&|4D$kzDa#>Gg+` zlT%qmg%>MwtnwcQVzXk7jnI}jpazXb0YpUDOE0d#&+;_;WIV`m^fJ^SPu7!N&&U`B zt;DNW@L$O`{9^TDVsw&MpInD<=&rJsNM1urF|0Qa|-8J-H6pGeRbD?t~A_*CiTbzU( z^0v3Pw+?ffLH#~kTU$eMJW>yDGL3Arsgeb4HPWc3(2MXEj+qLVYVPm5Fa9e)o;9vsiuHnaIO^HjFRiBF;sI|s*kE`|8yJ|aBf^DaFsy3fM2vU^1{x0^8Yn9%IS1v7 z%Cm4GmrW_hl%}CF5G8}WOaRUnb&$f@ss5x0<(+0x@7}$W(o=fI^R4q!?v`A03!BD* zeEZdn3m4B^5qBp8^|Y+9F;i)Ja2dyJf@dnf$sa<2b*cg?x zUe4P3$YK}s^NXui$qiXIv>it)1xSf!E!`Pe8FXCb!-o$MDokegeyrahJ)XSE-e+-b zC0_PjHJ`+Kjvaqz2Q&3Pyp<+*$ ze)y0g=eD$u%7o(X@E09O{1g-%%&V*0Evok0;_1wUIDRCA)J9(N9Gg}-p<5lq4Zv)n zfjrodq>=Rg{rj4vr6W1+N$iZj6eN75W|*r1iAm>1a};=7iw&alQt>!}_6UCP6g3h+BIP zfi?q*nB$LPMj~chsav&pSuY`Made?-h-fN~_HP5eq$8T|{_)56vr>x(wH%D!&|uJ* zXgp^MU==U5NMViS`XAzl1}E7x!D!O}&@K-(Z6sW$JU zN+_fOXp1H_4-X9`LdlllB+d+cIELfxxO&k0^z!w!tt=QA7?9yyTIVb#CHi>M9Dr19 zDByeX(7My?o-uWQ2UXf8T0>eo=KbZz7Ek5UEOGx%Mo36VYWz~%WhHq1>|8_$G&FPf z{tIWrolPqY%b#-Bc9#2;=P)du=kp8c(5nfkL!_C;ij63Z=D5xkw7SVhYRH>IDYri{ z7Y%R*af;^FL%tVvl>dHKLGNqt)2c<{NWTNU0Q>_6)W`&(SIVGxX|s3A-@l!KOdO+_ zq<+lov&%7?p?E=yu4tJE2_4m?oGs;q%Xo%^3_+PDJw_7w--d?NpIZHO7UlavDb^WJ z_M9t2wuZb}2T+r)S+p_`vPh)oUUv3A)GT?T7DADO{-p<=!=R0(arDohH{s5ZM``J6 zNbtWLa8&ak`+r5QizEFOAKHbId`t#9KE~#12?YgQ0<3IuR|_C>w80DJgi%_6F{|e=4lN8umQjm1k78z_w1>Mha!Kn%O8z!v=w~f^Mx00 zA><79vdH|51u5N2tr*f318V6(=de*X*pV9LR$5y6gq3heir3Spk!YN9K?xFOKYUmY z#ShKmG**2;V^SMtW@ak1fhoNG{o`75Z8S!Ofw9UeD>MEf#k~se<4(u#2D?>gUt^bn zHrM)Xht2?+$b-7Fio=;=Zf(s&T`BVyy`M=53LOkR=4{hE1HvqGSx0VOweodQ=tQs#l2{;o^gOAdt{YgQ4AjO#TixEO5T8^2x~+(4kF zkx@LfmFLjW#A|@OzJYi`Fs+K*P23fbmq{m25kR0~5OGgb5A?;gQw#>*+}{j5D&R3W zH$BY#NO7#;J#Lox8~{rF4VLyO>kfr@e!cf6(B+c2cu@`#3f>C8=IdY4G>mhaol;;b zKd^2+v#=6MOg&6BTXya=`oKa@AF+mh9|uIimKTd6!864Yv2*7PQ9dA49P+q=a7518 z!pv+k*txWO*tEvo_{D(-8(o$ypBpRf=;#=S?WG^;Hxbw?tIv#5sZSxx<>lv-9E`ef zkswJQA0Hy(;q-A3fhge!@qNO=s*=J#{vhUqii(T*)FwkW4-Z}WrJY>%;L)R6gCRX#AglC2Q<9QkO}Kq-k_?)M~8f!@rWX#LUQT7=L`{r*nr3 zh}Xq7Hzec)CnqN)T7?*fB~aj{$hM&YFMqcV9u0t{|gqxA%nwg zLJ3C)iEtSa5fL4Qzf&p72ABEw&#zLW|4!#hO!49}C|EKwGH8(KsFx~y15MrU{d#eu zx{Oo+wc(Dp^IdK2Bb@vUF5 z>+L?@qAd&kyAo(xB~$BUC40e8dEAv3&*IYTTAz7aJ@2M8X^Ur|VL=EJ{XV(mp5Vj! zGBNajuL9~kIt6J6Vm5L31yXxD#Fk!7mMk76A~N!+7}MfOUm6$p>HcNROV%t_MjAD} zS>BB(pOZVebj%Mf9D1N;6H))5jtJ_5 zj1m@SRTemQ^qDp+o|B_df?KH>*$JxOg?_WeKg2qXCxpNb5ncR3bL%munJlNDUug5^ zrurikwk{qb6@);swYOI>5;}SmEdx8UE?w&L3oWZ;1y;Zw z`-vfM*7_t34TOVD4E@sX_p-ryq0|y155XG}-uuK!`UoT4Bygx46kUnjf3P2rD6s-m z1sx|@v>)0>EjkgAU?ZFY0*dI-IQ$#3B`ICFe7OPVhAHp5$y(5O8JSJIyh|&~R0J-J zP>hv&ekz5EbOPp^{6FFE3}WsHhU*Gh@4AVQ-B`5i2Buh4ARmJpORHu}Xq)!ib#Mhi zyH<`xmy-Z}1UK;s0i^z$27ub*-S**yEVQ&t+eO4>K=7efNaP<~JYh&4;ccw&iGgxN zBl$;=z7hGDsSwfAf_ZXV zSyj~wn{C#e9UWmWU!GXvVQey>BVhKm#O#4iwdr=@o5^^Id&NmR6`4;?N-9KA!!e^` z%?g*oR22QYu6KJ+sR!j>NZ}H&u^DX6^)Vw=@TKwdH?RDHgM$fsBlI0o1Hsg2#E?qt z<;5y0T6lzja&Hl_UPjQdG(>pbmaSM0IzK~C`{5O)>#TWDK z-OIru2|(bm4uJqfn|GG!$g|M2NdM2;tHjILs|n}9rL2(SpIUP-uKi2nus5bFmg4`r zC^S97+hC31gdqahQNw96Lab18t6j%K0ho>WAysj*v!6wMWY9*lU4RG#kp9pDrVt!v z(OuR0I&SIIf$tJuHGv`1qpuqt9&SjL3^*zcs#qI;B`w{mU%~d~O%9YCG+PdP^tR?^ zqPdWOB;HFTX`rTr?Ui?6uunW!}bm>@1 zVV@*7OxmFE+UBgrc1=x*;z+N=gOEywz(Mbj@VXYz>f0{ z*!b^$Oc>7i>eVa29YvI?Y;GhYNKf*>U#y%EjdZI5q#({TbeTCL< zJ#YdRff~>m{+r*gLNs(2xV=dFLN0#dSDHpYw=PxZ!YDOavxrsv#*G`qnyBvZLyTBw zNxPrqTgU^PczLkGb~!Tes79m79tXh#%P$451^UA2Do#rQoR#*GU&+4b`Mqmf-&##y zV)rEWY0z&~n~Si!jsa2mh}kZ_rI%LT&3{+8&Taq6Tuu)DZ*{Bxx1R7al?UgW;Q?EM z{7mI3N<^P`%hs)W!-vRyZ`y_Y5VG?>D_CYK#IB7as;V09<_V8)6_PD@wTsGA!jrlo zvcI-**$ql)f1I?U%uBnOclOC4;zkhPK~i~Fx5tgT-_e2gji z=sU80LyC=Hrs_YvxAqUOngR<9q_sMCyEK<*uq#~vS%j-N0mxtM%o#mY`5X|U0W|_4 zuk!!>_L7$?aL+yRcBe66biRMp_{Y~`;_@RM0^*!RE|mteq7Jw7LNv7ZSwN6%=21z? zUP{@kK2t}0RyCj@5)MN_G<-gkaAfjFX$SO9>UYp55ubdtQllu%jV5tVD1_g!6b)vcl&2rn47bTqp;|x3|IvS*<7Yr zS`Js|c-ge^@PBMBEh?0ln$1matbP^rYe_3z5px`BZzuOjVFYNRPAqx}vOJB~NLJbmvE8F}Zv@E7C3k!|9@; zx=Ry&kL>O~$cKrKhs?*P6rL{j%UzlwZJ&b;=;4k>*@KGlpLQc#7rCzIGi798=mYGN zt&f%0IpjN__}957~yhnwOZbRJ?e&=UpLnVFqU%J#sJ06IVWoAx39DzLR3!5N3%X>6ULv!K~D zN>j1y0PV}2G#28^5m5f;1DST-j? z*g!yN(*juWj>0BJo$Darg}NurAwoarE-(@) z=Fy`^RGt)7?c(ija1i_%&_Cv#BlL zo*&8#XpJN#9dMY?Ut+aJwbt(LlX?nu%eqn$(l-0WXIIpB+36 z%W$fVIEOYSCc-u_3+uH7!PgF3LM-Ym%mmkAhkC*kSCsI*#iF`bbbit!zuYB|{G#L3 z*unX#YD@^gK(J>0`g*RUyin-=MW}v2RFDapKoLh}=jrD5F(A6K(o%8KafQ;He?e^9 zeT=w(z{f%FB|Q)_bFp&W){x}n1B2~_8hE6Jx)|9>+Qz~Iw6wIiKz)qtx!LInMd%RN z8iQ&KCeN{j4Zgm)Zvex|5tEi^h{HXDne7c|5_f+79D@Ft;pdmPwjZ}kC)d+&i1&qk zJ`8szL1Eah6ta!)x*izrF&LK#T>#EA1XZ$5OrP1Ul)D^LAp@?n#2kf5DYM(&h0$Oa zeGm`{S|JDpSJNZ99j3E>S-yOA!_aSZ!rxuUnaFK{D{eom_ju)oozZZKh*Qu`Ad(!! zzNTy$ue+-^v-h;m&t+b(4l>>tq!2B25*{rn5GfKJUvcx;YLin_eE=_wfIb;o#cM!x z`_a?xYs!cl%IW8EocU2g<)PPk1K|~1Rvx}Ibd;D$#4caC?!bgIevY>j07z|IvQPRc z@@_iXqcAzDu4UwryL|Z(u?CT34q?>X?DNW~!W`n+#CqCcJ7j2=Y(SLhV=|}@z?@Yd zeP=s#A-scvOu8kc6(FP&!4Af56$%g}2h3y^^g;$K zn4hz6MT(+?6JibW0qxN`af^-)u)Q6g6QQw}jJd$&h~IyPMh}!FJ#1RijLdch;UIh- z-M|4Qwla!`heyHmkPz8JU<=q}a*%7Y=h2XnM@IMd@zEvgl{nXa3j(Sko_h)%4b70eJ$3DG3VfPUD!*i2((sgcILAG`a5T;7na#j?>sbH6Wbu zFUyJ-ikc>XpB!_Z%fpb3WzYLvApO1gDG9x=!M_ikKrLAyn?TftPQ+4W@AKzE))Ew) z9nNP1DT8K);fTOG%(W1=v~~Q3Of+#QW7DwOCnge#F+q%U;1kq+>oZ@%>l23p4Av|| zvOOZX!r~X3N1?%!@C;UZ{K|o8CM%-ZGwXa|&~GouM^5DwM-bm7&RzF8pmMJhof~AH zpIU)YhtrUmNi!!7(WCd}^<9k7fa{*#M#NQ78$p=$q1-W4Ya*Lw!X-B-&unrF5TFOP zU3qi!RMJtxTo??Yr{I&Mgkw|3VLhx9Qyn@ILTo}{D!}XSMM}!PK3}Pj_Jzs-`=ir| z&id;W&vuFTwPdFqFMG`mw+1)SWWiJyjB5V#5i%6KW4GC0qnYuWc6J7cU6OD?>6BvZ zXboC(GT;vLg5XWAc=FE5t^&NJIOua&KAk}{>tqlqWNHpWj7k7diNx3B^tK7w56O!5 zKC6XRp$!fj{bBQO=MlqAZJi(U;{;k%@D2Z11w26xhCcOg_*cJ%hrj*ws9@s0GDf@E=PbXRwiC8F8O|dL*(iJ1l za-tTd6d-L8O9UuZ>S>)UZ)6y~jiIWu&XH`rz<`~_D{LM^3X4ItA$Dn`h5YhY+%jX2 zzwSn_g`pWS-FSyiaOzUM%#N=_YJHaMeZKX;KHsvj>eoId%0Q;_8O!5C+ZAb+G>! z0BPpH5CrGB%)sz1$kk0Tsm-*1>%vAa`2fflKL6Q|B!y0g<#~jDbEavg4d-<-iwFsc zi2s=5v-bh^ziP8EYTWof(^LaXf9ctQSD~|*z{U7Qs;oSfA1@7p18G4?h>K@;JqsNk z^azF?)LNr_?%{T^pFq523*!|pt+H}*`VbH`u=x+FNyKEMiBLHW?J)_&-51t)nD*-X zA3^&Je8eJZ@?-Lwr=*bxguD~BV#LvA#ssN=kZ&!muT~|hhB{<+7PArDqt=-0An=3? zY9Lt>)r8Ph(%OIX=f+r>2shH&KqqdC&>ULSV=tG}y~9*8=0)ElJMW*u=tu+<5Hfp! zU$^^ue=l)33^{}T9tPVc9U3UuFoWlJS#4opFo2aWRyxcT7!vwc3|dqcg=qGI`{Sy6 zpz5Ios5T)45>7^2i=&_%QNo>PI#~KXr9~D0M6i^@IYEXevY)i>-kUH__5blB6-A9IspUb9?{O8I%BeQnZYE-sCFPY| zH?z&|!jmUY$mA|-X?wfI<;#~bFX4sI!YEvleS(JbYzDq@i*%HD_^@Jm$-EO9Y5X4Z zKRZ0g6a}eTsIz36Rb=M-Y4QfJL;IRDlbD@nZopMNpL(=9>qZBue8hc)!OVupOa7KX z@yJJ|*cP~E7rg~4OWC`3k8x$Be~2T|crHl*BaTVBjaWLmg};ix^sqT*+9huLBkOxdRWP+3riY3Og zG1NhPUkr`o&@r#5da|OU^KPacSimz}tG&IR*?!<4=A=&&^9uTfq$0t4UfkD@%*XL{ zfg#b9$Zo)Y1~rT6kjxyBn&fRgH>i zzI=QVhaQEMj?QBfOWNU^H*YRX)C~>;`=N$DkB{FEV}}G*wF^GJ*4P`HV)bF8k5Xj2!)d?2i3RiA1WjSIL=NK{ z-T?ve==&%@2ahmsgA1DMI9Pbd21W^~r0WIfY=p{^R0u{va5VAdL0>)L&cIzW@F@+$ zUP@m_A8b8%3N3Fryc3eGQ3do+=DJjlBs_sJ6qLaI2znn73Z7-o|L|}o2zLq_fDD|P zB*AX2e)G!;Vp9N~By|cc^z<7YXNe<{hbQq2e_gEn1<2fWs2}neXd+uJ*kR=Unl)=I z=VvE~-wt@>G5XCYaPbAC$#s80EcN;bccELW!B*r8G7pAX0`m705MSr$4!$Iv*MF=g zhTYw}cN6Oeh*QN*Df)y%T=3)qpw}mBo+f39aK@WKD&oQzRwBBSD;-NB_%u-yz`|tD zpZ~L-A5TYGHw?jebypscjsWq!A+s>rzi1|7egNre(9kg}B8z6`7^0Bl=+Ue<{Fboi zgZRthOjeC*HofqONaOE&7(=H&PQNyijAD=(M`+Rn? u6s^CsiU0VQj*vtD7nOqi;s2WuI>#bhuKa3CP1`g%m$=yFGl{3J-u@p6AZP;s literal 0 HcmV?d00001 diff --git a/The Effect of Economic News on Gold Prices Analysis/Images/Dist of price by country.png b/The Effect of Economic News on Gold Prices Analysis/Images/Dist of price by country.png new file mode 100644 index 0000000000000000000000000000000000000000..25a30314b0e56719c78ef7a7ed5a3a8f24b6cb98 GIT binary patch literal 26021 zcmchA2UwM7w)HXAXe?MzsRj^K6f6`$1&s)z0yc_BQ4r}MT|i1SDvE%Dic$o{g1`ak zMT$|1h%^-tP>59Fph)lVuYEMRnarL4&fI_I&-2V^IOlM_?|a{O@3q%jd*{MlRi)W8 zxn?pLjM>UN74|b2Q%*A&-(}61hM#De7Kq^w8T%bt_6Mww+dCb#HDah7wLf8DZEs;} zu*}iO*3Q)0YJ-@x*!tDWOziDX*vX2ETmJC|F>706@s+yG9{45SpV)cGj=`9Fl>Rp< zQvQJ{gJCpZSz+73lOdnpJD)t*mnHwD^p{^Q|DrPKkVJx4c=#RlXpOjwJM!G(`l1|| z%uNRO7Jo7@eVA;eRaL`p!mP|V$aL7YZ!43#A$HNiU%3`3?3i)G>vBjvzg~;*)@56t z3dzJ(^}OtP8Pc=GSk5?mL%@d4Q>8LDg_QkqIgIeUq9TV$^tTxP)64LO=hb;r=-==D zvTO$aShjr1HvGX@`Qwc5@W;;Yx6Q*JTX)UC<6$uN|1@t3{ey$*5-)|BDa=gx%6p^mnNrhuF+oj;FgP-J*#rf z`kQ-x;Fek~;?Ub(A*#B$E4L!$ar5=V0s)1&Bb_<*A0^jJjGL}<>1$s!o$ut4*dm7K zn*~!QU6w6!zbgJX+4QxrOYcXHkw)YnHLh zcdDeP3=e*?_TWx^XS+MZeYmYFFlThRul)F+dP-butnXp#EXn>l*Updc((M*5T$roK zZMkryBT?<0{cDx@lU)sc2Zy58%;E`rf6?39@QLT7uEemh)h~*Q>~!@K_vz{JH8k(tY;LHYJl3Y>ak0Im2KxTL+uPJ<@AZ zu3fuk^Y-ZZya+!zuKJ-8rv?%EA!YkdHIgmG!Hd=8hK_~UmcN@iyM3-fbXnQ)gxXYkec#KP&dJ>XIo>TtsGkw=B88);b55 z#GBx!kfr#p*$#XZaog+8++sTnnsS%NpD+C0(dwK-rb8IFoG!7nAu(7d8vU;Df zFU;6s=FFM4!=rucoIbx>vi8WJRBVI<6VA@UV^?}uAN!Zw>-v&-Wmn!YGmv=;5^av>eap7jbEP4 z^}|CEq6K;UDdjM8C_>54cei+!gi-}F>)!4_MF$6ms1Z)jbB$$d8IechvidKEO^mj7 z;r~Re@QIGzYoUTBPk;G7zSipTjsjoa2+P`(@*Izev@cI*2{r`x40oh8`f_mCyiyi1 zn%kF7`yD?`vq-Mc=z6tVJn!@4PQJXnylNwsY{71Ib#Y<{N zKne58n3ErGpHE1xa`+sYkdQFwG0{1ZS9W{5=8T`OSD)%BZoIUiL@WA}?#Oqj z;D_@CSdBo-1G>7rhWVE+{5*NOBE4u{726fTKei%!u)$lK6(s9m*73MAyFA^lmA<7e z%eA0TBuuB%(zzqPz@XML)kn&*Cf9S)oibP}cZJ{RAHtPFu&me23^STRAvB)u#HDM<`VVIS#ycD!}&S-?3u{ebdIzX^jmy zIZ+k&V@sR5!>$d~d&nbf(et%=ts4dcmr#VM1X*itN_-O(6dz~{|B{^h)= zWl!Z{>%5<*^DU{hNL0DRCAn(mtXX(AOX&Xnj+md}r^?|L0JEArnd_?@Ae^`ILCAb;Vav_KA0upjow_(ziQg^hsb9ax7)#%#GixA! zsc{I$r2ETn;66EC`i#h)Rsb9(`+9x`nRTrt*;Sj?TKQM(k_f1!|kuwUmbO zx88EKvcT47hvE{1iMPiBR2t~mdU=WIX2jTs`fcvsc~D(F&!&J^v$M)rB{lWFj9p9a zZ@-=~Y|>|ZI{l*qK^#vDp)zy|iw)N@{b%em#|iWMuo zumSSrMmiSgX4qet7z&%X;LE!yADKyC^yQ&z6kvSihCdE=`FZe&gq-;49S(%en|(@o zgI$e=ctE~#Zo|2;k3Vyz*1NlgAW9`)&l>BmjnIAUX!HEX^Ka6}k=2$77$mn|(mr0@ zkDcaA8zWaF?9_ZseK&{AJuf$Oy%3F4KoDUi-)bJ~i}Ub7lFRpV?~R~^#PZ6`kstkX z16!Rk7yW#2u+h&D(TAR_(LGk$P)l$l7Wm?8)lF+?4`I*xJe#v=_2DbFw9bM4Tsn6>qV5aaTCJS@BU9EG&0jf3a#$_n9#>GpStdkhubZ3!!mj?Gwg z!K>-Dnmp5vS3G;r0Pii9uFrg$iL@k$SMs^7b=uhfGIH|OU1enjA#UqToBeuvw?f^k zbe)!ST+wmstEe{J;@ZDQb>oL$Dq`)_lS5BD{a(5B)|N!S&YX#HAp!sT(H80C8eZq7 zE6TzF%Ew>cxDv|Aq0Fjenya{eO0M$v+8LYP613=6^!;^)`9d65-Z|D}4i@qOX{<@i$NPSaD_lCfxaM0RiW}3Qcnr{mhd#-E9xTj$4Ph^;c_Kc6P@N zJUaRezg7=nw<8HVK$ut7ey4!IO-b|0RV>|pxnMar7y5{B;_>2LjaZ8Kg31IDXZd)Q>_zNj__r6vW!R5J+d`fQd?Pom92T0<+fls% z@9y-NaCNLXJ$07<=l74RhGWLCulC?Nkr5MLXO9oF?%K7Mh`L!Hr zgyo_@-;uPTbn}Ko)v<#K4oTMaayK_QSuvgcJiI zci*U;Y__O1#7>pj)*9yFj{Qc5oY}Vh+z*Am>o0f_=DFiG(!b8Gy zg{q=BiFPG2B7_`~nwz+)vO9Ji#>(n`NYAiu^Uvz*s7|cRl&r36u6o>4vZ)|7XY5l) z62+0Ooj&7ZBT9i{x_6v9>)6?3xc?LP+%3I(7cO3GT>EBVtY;u+Vhe!-W9)#LJ=b}C z?U4hN&d=dBpfg-5H?rEb7OO^Se4Xj5yIzAi17pa;OLkvheJH~6q8HGS5|88CqtykJ zMfgX5n@)!|H$=t`(9gAgL@x-i#}x-#XD^M*86W2IahbgAJ&^mO`QCV1&2wKMb;&xucc|Lf_vSzZCDgG_5Bbj- ztXRpJXQk>+HcHA4v08$y^;kAQ>)CE2mCo)V=eh~YAX&seWyJ%Y9B-{kYP%mC`^a~; z)Y~Ix?TTYMoTchd^*k?%&T`#f)$^txA!zX$?StmS6znL@e!oCCm+tc?Uh{-3(b{v( zeVz3lKJDzhORu9kD7dtALj&T)rBA8#*&4ya*&fK+S%5ARtJECFkt_0X5)2}Iq@osG zc4&LGoE9JZ-^a^~!i(?51}`=k4&CJByM2y~kX80jix$puR!X#WeYR+bd9;3xI|oPg zfDM9YWB8dl7jwq@;;N-66kB9==vvOz zTJ!KLnTaZR-)21UF2v%3t^$63tc?qgTW@*%K%J`+AYIliW8G5j#Ptrk+L_sslD`DC zialKUu;9XV?i$X+7Wj%wL6Hx42a2sb_Wbga^~ZMFchJt`2wUPTGfF%d2P=_rj-7=sP;!t_03;QPzK#2#Kdu-;>+Kj

K)PMVWE#<}X`$>|U-D{pFXUS_AJj2EU%3DjK5Tri*hL^`qQmhrZ6a?qAMm zC7JA_hX7bPN|}ftyR7}ky`2t|FI%Ay)GA2`NX5csM_UBqnbnVdc51{yxa5H>ybinR z#zq^1{00_yk+DX4oe1A494en}zW*>XKx3nyyx!5f zc{n`@J={OhPu@G#>mEH=k+HcH=W#JpJ2}c>g^F9dR_!Oi{H|#F)ZIQjN8p_VinSGUqyAU)ilam41 z49~7@3U#Wx;1$^?$0uuVVvpTN$2YArd*lxO(G&5M`xt&kK)_75D^9Fv*v80h1HMjs zOsBrIB1o&Y^E_36DS%FC$o7rM6uxui2E*$_3Z{9^KpFjJy-h>zAf6y^mg|6Cv$HPh zu+*nXDCwjG1YB?IQAVoF-Q}@0)(4eovc^UmtYj`CoFT5ENENZTxM8R@%ny4?cGIU{ zr}OI^{UtZ(O$q=$Z7m&S#pL_?4i)NG3Xhp>naFsHB{M7uk+EqFbvpiFjc$enB}^04 zcYw`&=9wib((ffy5mrwkWNSov+-yE`!J)ctY@lAA>Z2R$jdnTKJP32oP~3KK`=$mj z!G^?Axx;P!;X(GJvp-+3rqCr|oXj=p$VjHFiab?*fkWCQ9xdNySpNtM97>bB4JOn>qr^WnItO^;?Zr zVCQ-4B{^W5_$3>T@3C)x^YB->GmN`uiV7xQ)}|b^Cs=CDbunG8uv6X2R6V0^oCnNs z3HU6$^7~_f(q?ZWPqsgN(BL_Fj@PX%uIz|C%!>1)QU`z|)oZY&z>p#hK+h$|Pc=KR zh#g6Cz617Akcebr5$k_H?3 zCzgoZI%$yE`)YT2v}RlyFm}UD<69Sii{6X~Jt^YGy}t~S6fHqy9;~e&=bX-Kzn7k6 z7mA}ipnwG^W97|5MULyHIOTeAu(A2MIlNp1*897==z&z}d$=*%^)=-YL>f?{_GF01zb*Y<{9_-L*svBTl#6&3LaK-o+}IdS zgaB=@@A9dHP6NhieDrLNH?1QDCJ(SE1PJ1>x8qW-qiAFoB?LC9Ud{L6UQCaZaJMLP zWUj~H_B}xoE5)*UU%6PCZ`-!*9Wn}q(6?>_?;9x-cVM^e+q-w3bylASJBA^lEmQR4 z?e^faD-TxSv^cRXlODxiRcy!v#FWIm!s0S3rNrw&6tBzFb!z)S20% z%4`Oe;UP46+7CNHm6+?sy5VW>oHmCi?bUF5#;H+Wr*~H_@yM*NHi_`@N7!n@-rYIg z6E+d^XmpXL&K1gn%0O-js8@v#JW$nbYmQ?@Sq|+s5K;DDt&_G^2H)b(x5Y&W52p|q z;g*hLwNZ7EpZEffLhP&bpHv)lE8U%G1#H1(EJrF<)lRhvwaDtL6wS(Ya}(#!c?n7- z0O&-f8mG~Jw)DHTg{7rxKwBZF1|HX|Sm7G91Lx`oeA2CU%);^);*ee;yi|R%(I-HE zVz{c1NU4wAT{zQit7@5rBe=S|ckT$J<3#v_0}#R0DFZ6{6UXC>(_@zW7+}R8utIL- zs#UuPjnWkrdT|K)`^k@QRQ4Bg9%>E@py*Q#iZ1|+$T8rIU2`^nd2$S~Av#7{c|5L^ z5Bd67uw{xes-^&d1A%nlb(YTY-=6%etf!~f4PYDVI40=^s+h&et^pSpT8J|pxR8@mnAL zuu`Q2X{Pb^c|Kcz6Gr7l4luwHORckqj#Esr$y=nE3&_9;=%CX)l=13VWy~R>BXTE3 zJSN2TPIcv-q{kn6jGNK^%xf8g5p)UkuZXH_+g)Ng-=UKKDV*!psqVs!pfU~V)2;Fo zhh|K9qPdAh`ajjqB7WPG)7as`Q=0@6`ujiN#jivK?3m2BtL`rZuy=*EUTZF{2(*Wn z7sx5?Ps-bs0~;C)I=|m3gOtB@=0T8{rlzK#ux(>-U7&+(b*JHM&!)TC`Mn^%cK`8b zQa4W=*;#Z=NcrXA(c-b$vz{H@sxY6UC!5|}ra;{Le&GdAf4<%s%s+N>kD~s9D>Huf zoFF3dA7AMINZ|kDk6sC5edl>!RM|f=GSbV-tD&I*tb zI+L<+?bojT9ZRV;2vC!g*%Wtt#E7Mx(m^Pgs2lmp9~8f2sZZPrJm4Fv_# z4{GHEpqeNYr|v)<=M^c*q*@Pb@(vrDF0P6}V)5~O%$U)KQ?1rHw7=12MPW^mBi0=+ zy~X?fv6J6o{Zs2Ud8qejXl!?@Otcs=&$f!zw$?s{Sh-JIn~Q_P$jAtcn}6d)hSp)p zoY$L@3y)1?zwSmEALh|loP9l8_)fp;Q#sx@mHzHMZ=`!nI0a9;gCQu$8mQy0(y>z^ zl$Gzt&#%PieC*WtP;0u_8spfE_9%-d^Se}T*g>~3ez0bi!*vyXxhdLG)M9=O15jI^btt~M!T790g^uIUP;^jg6qiQwEu&if9*4v4`ypX%wR^o< zaf(C7+jX(o!|foJ7F4#SYrpUc$EWfEl@F;! zK=}*wPOy?ZD8Y(L#6dq`y}{|0I2TpL-)9}t(`Bgy?C|EyyB}dW*9hER8*|9?vft(^m?16y(%4m?Yr)P;hcb>73gJAb! zofF##J0?4>MeN}aRD8o_lq8F5_L(J?w(N8E$mb>N402~ioQsN%PJGP@a>9P9lD))? z?bA8&>r_#m@s#zVhplT4YG@qq6d$pj!U!KqP@C=$9TQ_wxoxkTq_@XZu&XLv9f_ri z4^%@93V59^fnE_OcCV}c}vzN(Clso)PvdD^e(|55fen4P(P zjcE>6ave&aMWzV0FIqqX- zDy*tF{f^`+J^FS@?J7OjPm6#Io#;nhO#y0^GtG#ZBHV|~thS}^&CDKBF|{35N8gU^ zQ^*A?gv+{5Wqp74(OgFH;o{q!TV1LjoT)JzcZ(Ssd9b`_Nai%@S0CRzJV1Cf`Mw`O zKJD(oQjhV(SIs1d z_1&G%wtr*$pUM1Am_FClJZ0?k&y(n*;&&u~g8zP-h@nIt< z(dZ3A52N#a0Bi4kIzOBHx~?Wp2I**u8fJa&6J0P!j84uW{& zrLc(a+;|IE*F|1)_fn39UBzFLc^%*W=sMH`BDCOu+LlGcd%V20WfPY84&VUrFb4^j z9VjP7b$-f5OylS(zV|9H+0Sc{>Rp|lDK8}hAw;yVI)6<}-;hogDJ!U*n2x%O7A<0n zHGn!G&-m6Ey|~&js$P8f(CofLr3s(nhBBCDS*GRwuWUS%HVCZPLg!a;%C`5~udHt! z-yjePyw-(#BwoS*3|u^j^*jppRL=asD=Q%&&<~zs5O>W()efl~Ho#~F*vs5b?;SLK zqf0}PN!i>xk`0MWX$==e?;sfw#3GbHS^>peT1`}|D`^`M{Ap@#&I3B*x_9rMP4hL) z{A-$eH!X84bm<|!di82!Z`pPVYjhlz$elWQY<+#lPRc*AncXic&IuJ&oup3*2V2ai zPh@6h0;;@F)pyq=xzRFxw7bZ>Sid6kTE*V5zSXW-X4zJzbAQGnn>gFb37EK^Oh|9Bh!y~TrI9>e66 zvcCdEPasqi3H%k=UO{2uqD8(^WG_=D21HV~!@ zfw^NQpFf9(1P2KUhn0zLrK(qqwdBj59#j|U>Yg5^q>!5`^=Toq`&6mq)pnr^f#W^S z__FYy0T%ZQiwAT~{@$cqyLsrA`Q8dxBs|YG{U>2oegA?f%a#4J^ijn;+vVAEzr`tEx_!dWb`r<b|Fu0dU54rr~c3a&!cx|h9nUKI+~Np9z{h3T&pvFuP&me=6PLV-jvJh#m8EEbOIS= zk$U4#26z~6@@^l+ePrarTMX#%~u2wj_KX&(NprEA=lXxEb0P@2OYVlwMuR@nO@g zi32@ulO*OMr*Q3XkIr22MQ~F1j&9z$Wv7PvDVzLX41NFVef{nQq`j06afql61#)b$ zZwb3}tM2GIL$`GTk!PvqL`Wsp#r-C(qD*3FcEPZ~-?BdcvHcY=<8;f*n+w2UIU-Vs zfY*xvb1_HuV>rO42zbLL|J~%ew5c`tE%l;PPT+PbX_h7W#-XKthnh&}E|U^8i> zgIz?-Z-hs~JegP8O6Ss&bpl|d10&4n7zV|S>MTA1i;M!W^U4GF=`1-8KlyobBMOcZ zIrr{Dk%)wZ^@=`Ri(s8H-wdeO720`9Wbtz8S<3#$IyDa-Yl{1YR!rN5`q4Mf zd$BP;BspoVPb#{|>;3K%<70MO-(S{HuW&rV2)`FSG*H*+d+xx0Me4mWTO=$%7GgOq zAVx=9Xo9pDcxR_ZZX$TsK<2SQFI#1{4b-t!hJNv*tLU0FmXB)K_a7YMJ0q&|MCzu` zX@X=RSOVouLBRryXL+J=X&UOt#;XTZAKIl~5md_m^5I#cUr|xffd$iWHjFxfv9}N` z(wcpl6F;b)n3nRQs40z$5guPL>e}g4knu2`U%h95MC!Td=I`_2XQBm{y zzRKZGx4))=pQF#A7;uOOsh&?Zge8(@2cg(W#X}ssvG(Xs_~2~zFQ*qtmw@C+b#=U9 zK|WaD>t|lDpI%_dt<|yucc|9rE)p+*>#32#+SbT5SatFM$wOlsFC_GSH18syO=M zNACZ=)5nen`;bDh<*G;MdUV~N#b?hrtsMy`9`Y&$HioCm7jECa-vjx-uX^~)ec)nH zKbV@TJ0J;!PpTNz8{jQnUpK346mK+HII!pD6~fv=*^QHe#Q%h2C2pWrTOlf11b{1X z8kiA>7MStkMPM>u#-Jd)jEwZ=3q^0%zHQQJw;8Fe#OkGWY&|okT^CS52MX zIgild;yQCi)5Y!2XdnIA z7ydt{kqgN)Pm}M9gjKE#PWn7ox%Sj;vp83Kku4FD6CVzVbt611W*;-?b(16Ji>ADX zpv^WlKw0NQrEE;*adH%s;%NY=I9pec-aPvVvy|fv9J^EtXW{^`>Aw1Gw?^19pc}a4 zf}L87gKo9G@_W4hiL7>Ozz+BfHj(^GHWeag#z#8&tuwn6iA2j6%67r?Q9z33NpPBtFvVQl7ojL=pH=o7cseqPWuw&I=`U2( zj9;~~W#D_CH6E6n?NGBo^A@Zt;8}3s{+yt7Gj219xYaZb|y+uM_6mC8VyK}&w= zg-57>$ECT^xdO`XyJdM4LCQ{4u9_hW*%Ajt!hQ|=OYUH$#o*$dMhBkZnV+K3I-?z| zDUraUd&1;B+>wusL%qMltKlD*>hpT>)Z==ij#Bo5v*yGfFO}auN^X_@aWb=0$sh+V z@gmWJ;HKW6s9;~gk;)Y_WWj|95+$Ddy-3Jjb3J55+9t7}TBeB-%Jw{$sJLw}%rgoK zy`SH2BKhhgd{_|+r{cw}&kjdNpDPZMjK0mnzXAX=D+=!j3J^=hHtG_|1!*C@(kEZi zeRPnL8#$`)`LQ1BxYbl7zYJ2<4`|h2P*f=cvTB;XG=52v1c?Wdx*s)jhSkZ^3(wg3 zk63i%F72L9lw&S&=48|$4=BuE3;Ep#k5XDC#~N~kP6)h_6i=xEfTVg3jw|rlz)k7{ zT3lQVq~F^kXJ)sL>A-DK4#rLE(UEP?yRz$wB$xl0^@8b|&0wJdyyZ5E8bc8xfmvX* z+GAMkcjQXD9kjcdQJEao8rj(s_sN{T1O&Eu@@Lw*2pxg~B&|Whs(dKM2nr1Hm@X!J z>VZjU{i=dR<@?>Tl2$3!kNl)?GEUM+a-=Z($MoL@zBiA~zFDB{Gb01qN+andi}gWR%G9e zQ5h<(QP3x|$+ zXRG;V!PCb}LY9)RXti!eQi&8q=`K*GJ4jqe*Kw;|lk*uCBvCq^iz?NtdcW!kdZjtS z8tSZ|SXYq3@ldT56>@PBs+{l6XB6*71>4(MFE1banh=ZS+_!KA=REg$v)*8D_w1q50SsVM@VYNc2>?4|gii%sz&*c4q{ z7vXnOB&a_kw5TFgSB0(1)MdJ;#o?CVd9R2rk&MsK25hWyd5_&u=1;*0MxO#QE^%;> z7S41wm(4JArU;FPvyobGd|J|fJ3Xr*cY)d^AOxHZvCJ<|;Yga?KysZ1Q$sGs@y{|v zhjMCAFu7Ssi69~yruB;ISd<>|*cgh?EZCc-;wnxa?QRvJM5LUT}OdQiI z^A$dy2sO8y3GQ_i_7*?V5Uza!Bi{fX-%aXrG@Y~Phr~Zyy-V8&6BkQz3$BnVrk(!B zl4-ANnn!CeD^1=@)-GDSc$297){9J*e3EBNY4(pQ7jkw>oC_JNjRp};KFI<~Gx}(= z;1bWVSh%;i=W&ufX>$-FQZ-H{qJXG!IrTZcRgqkp?5LY$aTCnD+dWp4xeI>C8XIMG zYp>RC&4?lGRyzt=2#<>g206{p)Zq-+O{kS19&Y$t+{{wgBOUjk@E}(Pj=nZ?dp4Pn zD4H)>B{w^<}t|8krK-Nc)Mrh)>Av#`eRW)?`s#iT?vx7S)36}?H0Ro|lI z7UrSyM#mT`?wMHjl~6uRfr?9MqhIRC6VE|xvBu^=eP00hj5<~|dHg8;5e#~MMbHr4 zW$eq8tkPK^KUApJP?a<8kn)LaCzL>-dJB?!g*t>_Rb36`BS|W_%mNR&09GF&5o{pi zDk037ZHZ+qX=$clk7Ou7%D|%Q56yL>U3`b-CTg-d;S&7gGWR58u&%`Y3`gHavfq*% zv7MQ)?OI?U+a3*@XgMsyI)U34bm8KUs|o07XtZoR;d%ApkkfB>o;h8t91_i$F*PQd z5adT!eXnl_vRYbb@u=KU%L<6ZWp-1bLfg=uIj6H6>%^FSciWk83XteWdVM*XXs+;| zV=9^(fdsy2`vnNGmjgOmBO;jdnT14WY<;GU-M#(%oMgV%=H?x!Zw=947Z3Bc#LlDi zOC@6P%*iBtE|!f!6jOlT){AHL?$1Q>HtK^ZVY%gvd+1? z=_71NP};-f3XAu6{6^pylJwvLfDeD<*d+BLSGeCl|9eD?EG|pACd&C1fsgXs}VE0kwdkXk>1i^-I3SpK7!8 zhHoem^vp@@l}7w>KhxLu(NjddMzH9cmNgu4`$L|NaXL$wcRiLx~645hDP2SUL;ole4Yy?PP6rhZC*2aj1jF*KAA%Q?#$>Qlk+(sc%-CCD{7N3ZSzcx;-&DHZX4# z;M@u-`+Irek^R9Y0IOME{fR)TmNaf~hXS>J@VO6uK!=++nX`y*!6uD|A6h~Yk{9mv zG7$RpY5+UZ-z}bN(+^D)%=pRK?>TJ?uW73BH%#rPd^T+Q}W zhn!M&SN#viRrpO5@ZRhTo>X@1cbb>j)9SPj=SLKdZj06loYeHZVfpUHUU?Nbow(i8 zoECDvz1Ga_9e6OW&BJ9iYI=!T<1XKoSuEsCx+vv7IEiDQ*5yvn8kML27q#y{Zm0g! zVNJXqlK>dlP)Bj=%_n*G=U+Vr= z5tt#{mAe4)S@A*TzlgUv`Ok)VAAS z$TbH%#`$XuiIAXrW67LW#*w8Xze;HK+dV%kykH8m1o65N-9r~3gKccNVQ2t)Gw zzp>PGthb8-o#Tq$+;N$hDd9GBXfA3mCS5t`26C2BXYJhk=}{n42wme~gctH~^?wtk z%-_2s3n=DFPb#5y3o6hQ6o?+RL3GHwv%^~>y=1pox)7q<<*aMhuS*R(;x-u)>MF+- z%81Z|K{Ha)5*ie!n*WI<4HZ=Ky#%i{o5xN4xE6-I6|NpYaM%?g&&(KHifp~>F;O<4 zNrUbLdGL2ke;xAXUFpLi*Ew7V0=_?uf{mb`Xs9%(;gfKy3dm1PykG*rV=Wg*8B_Z0c;Z&yP@Gi9DZ*qi+wdi^^>L_-< zI7oM9+)UUe&xlz49N)y?)_qY9QDkS=~5IY(%xWfKz$AlDgla1eG z{;avkAg`OHdD557Fx&Pgs{*6_SL=3(Qe-59|dBv zsSHs~(}jQ3jS(r2*j${?j%LdlD!FYQL6^aKh9CNqSz&9yH&6g>*5tcCIaUhrluyvN~Fxh8rdA|jJ@vsxm%S@+iURyisD;%-r5 z)-SmAKttS2#@1N}-^j{;4Gxu8+^2-!{ymTUQ)}|C%m?ME@VI)9g0+H)%!yPG^;CUDS2c)#lwH>5<}0 zu94)*KrBppxzOow>ePl`kC*B-gcNd8oS7rLg6K0Zua6bcngEJq>N8&>4L;>9N;IQ{+cjSa`!_!Kc zSg+)LLw){l8(ULhu?fhLlcHUkCQzxE*AQn|sy`|z&>@nfAemz=Kls}j>ihB)Jw0s9 zH^hp+zlhp_X-Q#$(ED);dRdV+``xKqzd(N6hT2D{0m#`on*U`I{2tU{*>3}&f9B2m zgUglYlZw=wm<1jr4Fm{ivY54CQdX(TG+(_Yw!t9RD-F+y;6bWvphtDyBc6l3B0lD<}O6|uq~x1pA73Vokewz(+m^X zdSj~obT!)gfbUIus!CIsZTn2g9UeB?B+})rKPo`Y{S_(vFwy+LFSmIl4TiZL=eLaw z_j%J)3u;5C}-kQ zEYY^Jkn_Ir9(w@s`ib!Y+Fw;cw?G#K>N*}0Qcif9NnBByO=H7zK|h_NH|b42wvi=K z?K7TPGCw*aK1aU4;;eQ&rO@z0z)Qr7Pd-{ff(%R zC$OS#Vw3nE&T(Vv3siy8;i?>8>Vcu(4hzYj36m;WzVuk>tCSFH}bQ@j=ti}uvijc^6cCGZwuq>nyFa*Yhh>9Ihk>JPXA=n5@am% zm47&37)Q1w^6#{3`A@m+zNPOA@Iz2#9X;w|8oT?*nu?B1V{cEjZ3=%lAIfvm*6ki{ z#<9D@Cw)|6a0Pvoo(x!tt05DKY0;S8Pgv=R7iO+mffmE`K4&a{>Z)aJ9gEzM|hTmd!?u>B&QB{F~`z+D|~l zZ*i%YCrdu#r&5{a{hz`~e}BKve@39bRyQ3AoDf|Ykq#Oz`~Xt{|DP^GX6|X4@&!r+ z1oRzHTTtzIDT&|!;@QL6KNz&U?z2 zW<<5o`~j2-QZD@+=_M>}WVh9NnHwq6p9-y_a=J_h)$2#H=%E74M+PUUgak2aB9M(6 z@ZT+VL4T}WbN1dJ@$RiXRYG%Sb8kL*A`@x_d!!cB$9W>5_WMz~aIiA#$n1h>k&p@? zIxUhk?{H_c`GUXKX2|v6LD^~|Y%G*U!H~HrD6EE*cea@Z=Ros}w9CT4k$qZPZ#V8> zKbZ|G1`2yskd;Ng>fX-MLL#dtD8tf*!a~;9b8`h;>ht1U;EYHpZx5A-&)5Q~ID;dHTx9kjy(oD*Mf{Q6lrw|Deem5G#7!)eX03)bi# zU^S}yOwrCSyhEGkPZpEPoxnlVB1^P|PT)_1<^SL!iqriLIDGBql-TgC)$||jq5U68 zv!iN-x=e7tBvNblpy#{+q{bSuU0?{x8Jfxgk#AOV4MAvM%p{@vASWK3S{jwXl%lC0 zqg5Vbn$*yY3bc`gGDB;w33CTGo!5Sto`Ybw4kL}UU-#L(PRWpy`%0$0$(YS6o20?* z_AaTS)ov8lmI6c|9vpoyB)7L9Od6s1J};R-oNOSgw`!>D4mx%;*A8;x-AY+>BAp=t zlCqIhjY$N-a|4K7K3UGW?IS0LO1~u3lHJU*(e9l+Gu8v+TNV< z%Ae5>ToNlFjAUFZ=|tS3$rf-ASm)BX2`VC?GRSq&?50{C^lo+0#I#?&U%)n0W30j| znu^dd3QYbMA^whW=`HqjJ=`@XS;%R+qffS5OtxQOIxGn6ks2_x#H>~0m$vL{Yov}P zvCabi=M=nAuY2g-^njXUM3eiZ{Y#igAz<^z-{vLje7-{&b^GFBNH zRXNnILxxXc!APd0p_w$*kNo=ymZ#1Ir>OVY_zT&f=PDoFpcn-)s03wCluSvqQ>lrw z+Hp9o%>_&tyE_1Nwj9}<;1;}q!B-D{9kE73w#}1C({qWNtkBf=p^jFZ1uo2j`snh$ zP9jQ;AFk9~O#f?yD=5ZpOL4cg%}-G~6l_7{F%ybua+TLkvi75nZbHT3gb7m64sTfY zpa>DdQ5wROMnrypJT*B|H2le#T07eNKwbrHll5P?e_d5kQ9!nr1T3@&sqL?D2Tf7Y zu`fzq7Zex07#{p(f$GjVGEJ9d1Ixeu0KZe!7yPMg;7u5b_V3+$nam2+ru3X}0jR

+BErQX5|D!3+E7Sc!S4C@Q*N^9U{HYtTxxiRQ;3OqGVOFs*AEN{+x!{L<27 z2=wwIJR`srJ3)7@&C;qoUM;KTalNx~*d*4&d+N5BH#CzAEF^mhBsqb|!AHIZ1scW0 zo+MQvCoeBgnB>L=W7QOuV)0C`=W=?L=ia4bzJVZKgOMoYT1izwaXsyFBALlrMgv7o z;^5E#9&aqUS6M;vdw9jz^HCqykBJdSg5eulGzE-3&JxzJr5yFW`>44Dgh29jj7f}^ zvpP49s#)o=<0ms-+u!WoW$M}$ORj_bPs0!IU?EBDOv6MR18V%95%!_Q>d>;am?A+y zy#a@YJ%&^cJNd>IS4V}9jV*Vv&gkgmr13^HKa`{V#F(aLFk&7Mpv9%)qsuia3;N1+ zCOBJLn+}eyJTQgNLgS>1wQF405(C z=JEu;g(<F~Iu(^B&&1j+N zS*OSR}$vMdGW~cFUNVV}#KQe;Cpw^@TIFdE|0xdZ8=hzl=@LMYmHM1_+_ZTnZu!J~irg$C1?jgb8q5WSfUs z!>D$(NB$`K%9DSTzJ;kGH!$&zh_)+XVf;fwL+nAWG)iDECO-zPTq=z00 zUjV%qIWkhx4J|z{^(15PMO}SW`f(>5ype$w_@y_f$&cC7nN&qTvG!{>-{3eDv261o z4aFjWK~HrfD<-i4AX7yfK;BRaG-_3Y5sFx` z2ceEHQk-EGqZ3{&MF)mr1L0wJ?+4duXp$aCr;{*gC8m;LcIslC%UQBN%UL?e-v!OG)b)+j#LpilT>J&$z603RI1O#u@AC< zNw;v8c;@9%mj1*pnu^y%GYd<|)cOijSDSzU)M&dlp{zQ*A7sTSruMwd6Mj$(fZg0-X3M}Mz)YAW9)h53RJ4vhn>C+7`j2B`zB_N z+M*B_!7M!GSj-;mkR=>a(bt9khimi>8ph*~-WmBe>;+r2C01#lm$S-Hl^^T9i=wX( z=_mlN7+X_^ht%wH4-A&s1AQrg{Dd_1GJqIDx~cWB*!E>)nH~(2!|*Lf0Gl`=nhgcG zam%IsA$tXB=B-8WH}F^_=9W78iJ-zNQPBVzcS@s^UZL&&F7|67&~ylf^4-A;Gg4F>a3B}N}15IFP=@%W*dZ>vqUeuet>7|dLSu%PIh^TK{#h#|UH zEFS$jjs3Kd<(C8S#8$N64Qk|RzYC$a4Y|e^YKaK7cJK$^Z~;7}Io8T(8(R-b_FC+- z*0eTl-H8%}3mMc90XVBdv@SqZVLIq4SB9O)kyq}SN^Se_AeLN}=Hk%BviC^XSckEw zPPZ<QqA5DMK^Z#!!Ka(8#%6Dlj2J&@IzM?NYN#AsY4A1b7c7$TTp zNums?N+h6CG0jfPG*c^-Mb>r@GD?^$N26*m%foA@|6M%?OU!JerXKcKv&A`sJ4Q$9 zC&(>(OzDR$@Lk3uTPjg$jF6<=cKc{!zK=J})W(l6NOB7m4jq{&wh9Q{6S0H(tAMPi z=*F!H$~uXQhrG+szFI0ju^E2TcyirF+`W73o+X$z1qEtS0Aij``IL|@)e$sL5}y2w zl0JRxHydQdTv8ukLDr-KnVO9yV-wkf-KhlXNMesurWui4RNqpE*wgjW?@nwF!Eh1w zV@CPOL2!|JY&T6rM)+Q&Y0Q}NHJ=!*Q>?@F7wJH*v#!gOjGfCcxk+vENh_!^0c+wh zF`j%Mng6f8VZw8?$Rs0y8ie7RdZqx;FVXxP@~bVXlt)QUtTL^ zfGsqkmD3Ci0*wcxF{~~X(-}#pFq@pQW*5pN07CMmo2zs}s8krO|M5`z7vvcwQ9a}h_8(xe4{iivGsj1BGBUAk7eyN-U9!92=&(H zrkp;eHCyBbkY`UedBzi5(~=>qh)6U@BsNE^JoY{n_&5l#d!cQRlD6_7-@w76Q1{n^|yY! zKXn~pe;OH&$V4-w*s+WT1$$Y?^7Vs25~Nv<6b1xgv?e$*TT`Qj8U>Mq3W$0pQW%v> z0cJ~aqKq=>{UnQdNNl@2wF|j-2ZSlKmV`ECNR|vul57H$C|R9B1aeZ{GXX`q%ngqf=sc)va6ip0m&1`_%Khiqh1S43rcU6x1?z zZmUpG>|3Is*o*n~0Q^MmrJW-DPsB-5(@E9N%*oXdZAzhF=wxqg=VWbR^t+2G+R?(! zR)9yChyUX5_nn;V9YuM0ZT|WIj~&{amqTyL2TpRx{*IO-1qF>E@_SE~M5YA=MVF$? z?Hg(j66Qx;Jx?@{8<*G9_1yQ$+}ZofO`00cr(-9wQ!YHaAbDNwx1(?Fz4lc9%>4L5 zil)V5%Ez+D)3_Mtx^!l_ue&R)txHdi-+BDXwfRy0%tV2Bbw%uGY~t{F$K*k+2*Xo; zaCHibhxKUAS>!h1Fy8pvksk+7{tphCgjF*Yqnb@r)YKx|*63+zStFX$vQ;yOtds5K z4;?y$@6HUpdGn?Tf9&P^pI<%B3uno;=+3YlDxR~6soEU$BJZq|g_fGa&YSYb?%r6S zpm3!+utZ_+e-%CXY?DOD>`Iqw9UaxHt*y2E{OXbT_P1NC?Cf+-Bx|$29Id!ZhBt3$ z)XR1xiA^mmB+hKHMab+saQKZCqxi;T1o;yUU8;0wUr)9wX}+k#@?#LaJF%JFadNQK zCSIN`V(h_0@U?Zv+0SQV<=Lp2t_>vh?x%R0p-Wl0m*Sz1ZD)$4`)a4OsZe}xjfbmx zwu+>Mg@tyNORm2A9P7ehk#w@puGYRVAlO8G1^#7ptLkUMi?bKq*(dpV+G?RZ(i{; zyuivT$;8AYGA1V@6BZvIpO8RldoHHgB)qE1;}IkC#>{(PDvVlo7jBx+mm5FkxuRe* zQm#zG_qHzYmf^gy&z}9-i%};S^s;ks$Rs5tp&cE!G>|c%F4-_qEZ!xr`;arAKK;du z)T@Eow~lRz=EluB{H5CtJWp`D5ib7ps<5Kc2SB(kw6{uCA)->L#$j+E8#Ge{^tiW`o$ybYuIIbd!@s2xHLE5BsV8qgx|DfHn(g{#mp>&RSCXRa=-H&qlC9EECBfL z%agvg*rTl};o_Dv_7K&ONN#b8&=CI}+NyPQ_nB?SScM?85 zEiJ7scS|BHE)H|_yi}I;U?G2e8zmK0cPnpQLMn5Hd~C{eTRiqo*g5z)Ok}wD&Z;W* z8eD6r$UGEQqp=9D#!^jfW$oLc5-UOb@$38d?{CK840bk2s@mFdMn*oSy*5`ni!HiWo6d*cZ+dZdsMsO`_G_xw*4kVnvrlo0$N1Yl&I?28$YkPb zz0_ad+~4Yfth$krk;_iAchfU6TH4waxHR(AV8I~w5PXX7rXp;{cQZ?MY=w;UymW{f8ePbyn2>dVn&JL%sZI1FvU=iGS5&r2`en0Er)-8x6%4#L(gRL# zq^ys5EJe55I619yPqntRsQ4dYEOuGY7Ta0v#%LC#xGat3BG))b!_=cBv18J_HJ6!; zK~J^dKfivWtE*cKvm>@X;@ARTCGYOA${c5t|Gd&6!E0w{SF^iG2u~XyzlSvzCvUG% z9y-*SrJP#qFd^jy&jprrKSWOTl-q}bnZ&dM>3I7fe5j|((mF4VjjF8G(@3bnV0v{!^RqMqO195{UHl}fs-MSFq>ey}JLmiX#>D&8!khJZLeV?TY*Wl36IecfAr zhr?K4GfY)>z=yM8vB!ydl!|{J-zReQs?J!I=qsP?zb zD@|VM*Jx;Hn1kJ-)}N=>TV`j_(AY@8=GUrVQMtu#D`ve}%JrP&)wyn3X6F3eoh>d1 zgRp^K#|hizjaIqNxE+>ppGkCGosPG|IL@>q`G`lqI_vpyc8tTs$DvxUs_mVfsOabn zRIWCMpkOai>x$QA@kt)ttd}oO!9JL(@S%A4gbxx^!oYy$t?=dXCp2R!yNp*|PK5`F zdu?i_(=dwmyfDept>_9zL4dv$USQIE3|kH3<7c5ymx~b!4-daMr=_JORe_!gg3Hju zarA0h8cV8Lw#rAZ^-*(~cz)A>v&~mr=3lDUo`xOK@ojbWvWkkzMGJT)g0S;q&o31i zHy)Px7|Ee}(L&I&=MpS3Bi%};=I~O-8O8eM=H}V4nkrVC56_PJu}oxVCKV3N+@cXP z`Q?{iCa?4byRXg~-l?4HtMl=Z+ocyUI|W6!29t5#b zC*8n?!0fYaD09_&yZp=IqV2WS&$mSIE;Waav%zdZxcG>_f}E+Wtn4Tqow*FJR$*Fa zsm*Zw;u1zCf{i{r2i(fz>7}gLyeAKP9^Aei84MFF_3lsUIYa-ISFe=T&s-U35 z=iza2c0_S$1R;B&W2m*~{jLcq&5#^UcG!(9{u&TXYo}RWGv=p$l zyVV~)e&mD^D8yav>`axmv#NB2Jdw-9hbptxqxX9~R^y@5m5`XIo~g*lDCXXSnI}1y zqo)FljE!Lzorjgi-RN-c{COmLwi1r9%Fez!$lL=6%u)VE-55*;?XhDid3sgaUAlUD zNP=T!VY%NHCs;PpM}P^C%*)F|sm}E0Xr*>%D(Pf=!VP?^+uDw8GlP6junS$7pSP}{ z5$EEPi{Uju!5YH%WJeGx2m=MF0km9ZZeB|@>loY7$_j5(KJ4D4!otFy3P*EnhsvEh z&sw6m%r`FT1?TYURrc7HJ*J=_9_*fmG%`sbaB+CNao`GJmf&G$XOH66>Eje*VY$7# zyDJLIP~9DZGjXIpc!^Qe>5j_UD{Bbtr*;ZO?t{I9Z zWNsR$7Z^!$>s6}3vm_FUg=sMtl;3mWdMouS&<*Ikm9O*jInmrYV=ALZ7)8?{M@@;0 zZUMZCCL5I5CQ1dJdQE*=X!4X(!^e+fM5me4!!9Mdnwpv+tB{^F)46ra?*im2b(tS9 zbXM}V?KsV=k*6C{44H-tpcfslzS^BTck)QcCW70JG48B~`OzLDv+v!zw+Exnwex)< zH13*P;mGKypjF?+it_R-h-}fGWh)z8sGI?AUPWP>q07Oig%!8fmo(hnD_Oa?(} z8o(MG6=sTuJAB9_sa3fwtZvLCTh;qf2LuIGTa1OX%5lPChg@5D`!eg?_Qp!U^XJOV z;jCl_F$61fY#sE~3BGPn;!d*Et8|iCnQl{^_!!JR*BHXs8n%w|c~CwSz3K9;-N8>q0A5foQl?+UtVx;>E#i5IYd&58!Y z#Z6lxbyo}$A34;(qi*T$7U+mQpyJ}QFjOK3nF!Unj#cd=x0x5+@;^dcUhd4%Dw@RO zG00j~h^15FsFWiCgA-aou>CY^F^rg+$fTs+B1Z{m<7U*p>Q*VZESd$^EY%o)g#BP!VhjyAG$3D(CYp8Vgt-o2%VQQ&UsvfS*5Og1d6P zc5S6?w?+Zn3Rw@lu-Z-b-jvByN-nJ)t9C0AvKdP2%hj223-V|7)`XET2wJLz(4X@& zoP`)1UfAE*)YSCGy$)^86zrB5JpZawWE-+K^CD z`T8|#IhuTl;$GT-W5OW-oV=*{!fFsshrRpyCcZP(|G<$m7ogS$EHNpnR|8evCTvc@ z2jA|EI(CR5vjMf1{4AU|2ExHmnO#0$M~<^+Zy0zk`ywE_$h<>)p$NG) zOf+e2*bWP28>dRzGt)iQKBx*CP-%sxtx#p@i4ZlQriU`T z&|NKo1xg)!Mx)#2TqX%B)NIJjLzT|h_x1H8z{~eXE1iLBc+bt-@-l`!>A_9NZ~gF0 zdI3XYwdf%3Rx!eE>aKQML7sdzTv!yK9Gg;74m^gb&3zh!g{Hl43~z~T%@;vo-23#< z@e{xO_A17}TcpDnqL&ns5B#W4XJlnvaGoDf78e&sPT;-0ER7Tl45Ch1kfXBq>^m^q zDb1`7MM+dx*lU=2BzPr?I&W$${6aBVv{!3_iQ=9B)D)LD*A}dv`um@@wYBvN4Gryt znKg!0iVCfiRZzs26!S@8Y)_d$mBep*v}LDkHS&Lm|AH!-v&JiL!^=hgrp zPeBm5fB-c}#>Rj=qOVnmaYCMUma1_l9fpc9^?ql{N7&NV7a=zT64owh3Fkd~_T2*j zM$|q&KDWZB3LM}&?UxQ4!_cLk9H2(NR^Q*>e;-#{Q{cL!kG-bBT<5&}RT8^8f{%@7 z5_3PLudnY`n}3>#*8J39=nbgf)`K7$o<;_vmi0mzFp69V&*mUt;X%mj#hTK|=uZtJ)*{$xxYVe-Fbm_CbqoV-it+-SP>WMWbT32;I zF-I8~Ebs6`u1c8L(b@TdRI_v|(0PsJ%gPQAUq8-vrUpYU&~9%4hyW#-yQbLUH@rC% z>jfVny#&2^a|sy%tU!L3#SshVppo_}!&4teDjb7hNie`X_{GG;zyJ+bmvFc%_TvwM z)pJ;#RYp)gKg34k@~W!SP`?Sq30j$5G^pJcYClKu_UOyQ^&hdzK=_eQz&?f2h%gZ< z!841Yps?@%n&kR}3_Nq@$$vcfmVe6c-OeJ#!>dEEG&9x~hOzLFAvC&)GmzY|8u?Jh zl$Z#`tCw19K~deC=WOx^srX$s~^}1x$m`TuE;FZd0^CV%$MuH|s({Ba^DUd{Fd7Eu$FsqizS0FN`>= zsH)OJ{ZInAZ^#69TFCltYczLmmv)I|It1(i6LN(^!En+ZIkSma1B0sDqpZMx zBEPQkRm4$NQo0Wl0U8Fmkjs}zwE68Z z^7jcESn{8UoA?@{nEUEy;7y&^=CxX{>xV-WOP35hIS0A32a;13)B*&gB!}EEkCOgl zzz@mAP;|9i3c7|%7In7FGcC2l**0ox{Un*+P(^ULS`Jg1A49H5ajV3#x$H#vj%)g(Mog78|^GhsjW*+ac=Sy%oZ*xv;F&^6>^Z+RZ5B`o~* z$1;EW?&o?R*iY3rc;t^0z?uHqu~7dYUve=t8meyl$CrGYpFb$bwP*YBnSUJ??ESxQ z@?S>aDNXb*M-Y(oM``EwY=NXZDgaUX7aJ@*O@tK9`(@#BBR| zQBJY6vTaNCFpti2o2lK7q7pt0ZLODUHKN9R)W@P)IHo4G7@1bG6&1*xoJ!5+%o=m= zYD|wDQW?qH84{S~Zm=D+>BtxtdLZm}y>{I-vM9fxoc?)lI38UP)3rjR%p)r9j zOM%^6$!EHO;$_GWfOmldXi9%^1~0yzdFk0RWtf=QjENade((jCCE# zmgt0lnCx^^XsFtk@o(|b!G@^Ujc#^!-)-B!1eq@#GgN#cQ1HX3whW9v)1%3Ash7 z{+v5%kpb5vbQQ(DE2cw}wtYlNMAhhp`7AmU6EjYWVRyNtSLOy$a`)b(NO)%y98V!2Jmw6u|?eSSY9mXviwDX+}B zqo!~azq8N(_~p&|efYJJlhpJDI&2ZE@5q?vzG$kxrNG)AKU3W7yQK4^`DaU0mTNsd z1zu4}(Q)RndZ+2EmUGs7s*Qa}WSp*VWY()}<1Nm!i{UIB;?s}68uQFP%Hy>fpWVQ( zuHI)HAyrL#k)*r@soVz2SE+Ui(0)v_LMmeViQF1R{D4o=`j@GvMZ2qXzGaB750;%O{KS$FF^lUy4 z!;^-rD=OUX_dShYUr*u=EU{iYC1{B=@EZHHxMat!OR(ec7~fs+_fo4w-x4DYogsPe z931V=0mZBKv%}2SZXJqGW<;DF7~oj&*brl#m%vOUf9k2IkW5LLNK`Z7?Q^Or5Xy=F-v0!46MN@q$V}Qlx z{DgMZTzJTBR{R3Z8rQ2gTEY1JW5v2=8LwOU=AyZU+BXk&Z^(66&LjcZ_yY4p`q*lN zurlQlw8ovIDVO&*TsoYqBdVux^;)WIiOz+z+xx|amh>7LbwAhIxcPMC>+mZ$$BAQx zf|*faMy8~D9bss}Dl0;q8xZ$jr%2!5hN=~q3GDwR=5DMk$qASGq}XSR)6|T3%l!u5 z;afT=d5tGR9T?BxXik-DHy7M@l99zW9#XyKu|nj)jJ+ws2+pRxO)({1FH=T4IQHj} z99d-)72AnxRE0xF7B%ypiRMmCFGd-()l(m?|2$3G-TP*t2y-_z{c)glR=w)rj@Lbp zv7H)=!4tjKJz9bcPAYdh3oTbZT&Sq5uxhNVh`!cZ%be;FCy{+1HyL%e08RNTN3QI8 zaabT$$NMsMKc7e}rFGTtr3bFR0WF|`AU-?&HD+4il{aToLyOHjm=xlL5JBcgwJ(D) zsH4fHl$$NFiM3fKOG#CJGCgmNa^4n@d@@R_IgrDBHBYna zSOkB``n?3q?eAm7*2^hOn--R0ZM$FfshN+x9)DGBu2LSK*pp%UtUW=l&v&-^{Pj2a zTy#ntXN9y)Ii1QR6j~}PC&tXJA;BzC5kGZO^Nu19k8F+ooZqz=lOq*w zku+;F^9$!Aii-FrjB>h)z8X)?6Ub##qwiZ=ay4aGbE?*;d^Rh(Tgsi3y=lbGMr6iJ z&Yw%(Vh)%4a$RKWWT69S$ZoI-CG#{;2pYAa5qszv~lP_*Q z85NuxWgvdDFKt=B8=tc2>~f2n{5lNZ%ae1%Zc#&E0)k+k1U+wB^$$H7K)lyHue{`t7$DRAMf{EAb8YE12yeo z{h4W8aa_GF9gvn5uWd|Jc3^T%=0o-^F6-^X^s%wBgLQJvKDJR#>k9ACPV0gkDKVP{ zTlyXwK4k0HO~E?6I=kdMYAI_>LESV4y{apIH?)iA696`8B=<)zXq>n^prFUhnOCNt zon~$@mRIa_;M;~_lFH6H6IZEfwOC+lEr05Q@Ev}3eOX$Xs(hsTVz*}xk^L@HK~8?^2ty4IE`q%Klq z&!n0jDGhlQ|72ej)9L)2NVRlH17(zy-zUkvwoS)h^*C0LIfJ$%Vt?a3FCZWtIojMP zA$@sQicPqvdeP$5z<%7+1Kynv%84H4&*T@A_$$gUaGh0rmtT!7o{+ZI^cV>!iRZOg zdS|7|II3Gj{`JBnh@u*KqeFL_a0>pRY$HVP};l-d>mSt?QB*Z zkFM+xZT1O<9PT0F(4oZlrJQ}%wpvH^!})hBy;#q#g?sJ z5m997P-$h#(>&aU2Glwg7hNCZtaZ9QboQrQz*wb}tbkd%0eyuOq8V1mTxDl=9)xU;Z8$09??sr`{t>E3<%27S?$rPF&){N{bY z;Ws3A0F~LBt;&vg7=TLw-ai4D%uJ9<2%qQ)ybQv^!ax{mr}yS)sm8{}A`~C^QmjgR zpFW***DV^n2EDXz>LL{oGu@XsPt0w*1kn91${m z+Ro7y@vUzaya?qNh;;e-Y~*~N$F-nlmi1?rvRB>5GbF{V`eT|K)St)qO~y9fkx@b2 zOwbK@+LCKR&$={Xjg6Z)$;xhyUmZNr>N0;jJcTzCqe!wUyY#^Q3RcCj6grBKl!OE?G-dW30=E@_&$ z`sF#_2Dh{i9XFRy3TaR#+(*? zQD)Y23Y?6RiE4JoelHj3N#M}0ka^aq=4s1=#U_*fhvXg zD1cb9LdaE6vwFoL`$WBX@rsrUl?8?z#1aHy4B=S8xS$8hh$^s12uGN!S#T4Ot14(q zR9Ouhtx%rmo62eGdqi{c;P6LftIl8}Bh1ymEWAVWp3F(C(GO!`ByV4h^301r_pv%H zLUo4ojh2|N_>i`a=xWjY#K2Py%r40zU~n_jsBB*4`&%aTGVyb>#R{>;tBJ#VWAFY| zPkoC<8ZJTn3(vT+n230-Lj(=k@V)Lw)TBPKHtb&R#w2L$oRl3Z(9(J?l3K!4axNB-Yx7ryZbK{XD|!m#vx2$*Et7=_8BkS!6e3M!%nx8Qiy?P43sRu;6fCjU}tX z8d8ZUs-vp*q-t$$7BM%y=L%k{_2St)QlNzTmvgLBbeg(#JKL{4w*#|0gROSNtUPI= z^4*g0mpyKVJK44BYhNMJ`aacA?)+vsRA>~})g7*$yIYUis`LC(u6SlBrG1}xN59M2 zAEzyy%_|8k+!~g6Q;s6{;%F`P2}^b#Nq2qY*5{I@2Y2+=YxU#EBrZzo{1l^fj72wb zem8Gy+_2S~P=e3JO)II{Yd(Ek&uQ7e$?QBgqU`KGox0b8>mJqNF{-yf$DUwd;H0CY zL+n^k*z`*?d!+$2+XRI&@>kG9NkAf7KnAcJDK9{*NU(Bs)|BhKy~I{N2_Q-fk6vXO zIK}RRm=Oo|jWO>n8)|y~+o0#5?%jKZgeedvXzvBC#274a2I%tD6Dzy6@@2vm6_Ydd zYW$neFtCKax!bzctejb#eoI1~L0JAvhpR?Qw&T#~6160+j#aaxOFJ)`iZh3J{y@u_ zV`=4yTg4T6%;}?Vo-tBNb@e%;iOW$2TY2a;lEzTBapk3DZqtTF+3*CagW8KeRV}RL zStG6LUA{EZQ>AhuTeK>#rQMqc`;}q~_+&@QwF?4g25Pv=1qEi3BCD#3^qKDJkLmLa z)d-_*NzIp5^44fR^WXN$S9o-U@{-l$=KvzfSzX?`(q$o7z3%le?eUnJZ+e#Q(HM<2 z)tMs=Qxgj*t$Y?k73`>v>S{f{f;kcV!|m=Y8|L(MHbN%H`N;4Snc-8G*)yLza?ef0 z@Fv_<*)C!KO%2;Gh2SZpG3kKNVATER0r-usnP`h1^OQCGWY~PBT98k6RPVB1h)&+k z8@FdDWouAKeV$`bOP>cMh;LMGZu`Ev$Us8LZpd@-?8&EAJ9=|TLb9^uIk*|0v=8Nh zoGR5RqBPqo`n7%C)2_MkTn6OdqVjq!;f9{X2YSBB@9GLKx&P5%M=!6mvi9C6PJ<^& zt;=~wZv)N}P?sYpVZQEauPN#5^+m3=*i8mAT$st<)xAnsH;xQHg$2$Jk!`YJYujgOA?t9p$wq!!Sawm=Tq0?N1t+EPj5G@(&u>4afGds�!fJg+PF=^d zs`uxe6E8bE-{{}Fk#4SP@zL%Fq0D}o&WU=rLX1X;_l>c}uAAv2#$l%N=Rc@VAW{F~ zPJ^i$X;1uv1-&G4l(&?&odux@DUO8v!9Bx)#mbML{1=w=+*0ZPLU&%W8FTrIjs2UX zygedO zJS|`*A0jFR{vrVZ)pzgSq2}NZQP)M?yamL3M5-h2C_()diN#_OsT?R=d`Z84QL9_z zPquvVCb$w*K`QG7-T6}dya$x)3}WuZV3R%$Vx;^$RF?=VAJjjQ7 zCni(B0$cRSYy~$>b@*^(QBe^H6?ReHyW4IE#L}K_6UOx*DlRzT?t~+jjt?JhBa)>% zO!btBzwhSH6|!3dMosWY*g*1rA08bQl@4kC0#q;k{9uU^IWP-)cQ{M^rFj*lKPmij zRVG?t(38P!bqn02oi*!YSTK@Z;Nw#U;W3;AK?NX37L5o1$oB|lme2?8QVpKJ^Y?Ft zH5=3MmLM*g{$^)&_z#_fYymEdPLNUrJ-^$7E~p4@m(P$1E(Q)HUU7KO*|iI1)g~(GAF7yyr>1sbSvsAQ;0vXp9(3*X`L|4l1<1C#lWTk$`>Y^3u=elK!? z@$r8OWfA{zU5RVHX*c^Ta{mWW?B8a)aeVZhufM<5`=^KCDI-@Z_hQR@JiN#+AKxJj zLQxO6xLIVt3dpIP^0d-*DX(AOLxG2=8bxm)bVbqrvwmMRsI^n`2JdSmh4>^TYTDUOZ#2~M%{vQKAk1PqrL zcpRunAKmS;{tcQIrC$-J>$22Ei&S=;)fbhdRY;{dOhjcPAPerLgy(Q@WSWSaE8VS|)9{ zTI*sArag07>6ExGq@@ixdnrd*3YAvZP5R3W)fzrG;z^7s3d9D)VA4wU4q!|MEjK#P zY*W`?Dke5Q-!yJJlg`qBy1T2yJqBH^0ajn}Kfi@L73j-y8wA01@+ z45l4t@DU<-7hLf@Aly4n%E`$^AU5x2aG2F$-5OVNMz8xa&7}|c7CF1D-c3&qPzjsy zZ*6Ym?ceT&potCAe`nv0%$nr5LyRIQo8vMWq3(V%=FlBZAYgVP%)LeCk z`AdxM9^rjsTQ9!4E@+HO8Z>ify{U=)Rt#_s5Jx>M`wHrk z7zH)X8q!`~*r}C$R<$O=!Jw~2v+gFnPnuUH^sGVCrNasyb)kiY{41$iP4z6F;p3X9rw z7p;?N-;C^4Z%z7{j@g#7n|`qTXx@$LlIy z-Slp+EW@|?%saUX%=xlExx7(zpOtMYD2rG7cxG~RBmS=1n9t>NKDqjr^}^bil}9sZ zIMN=_iw${{0|qLwAca;;lNVy_PAJzriYxPxeb>;Er7$z2UaiKuQ|lDXsos9nf<8Q`aZYE|UDutwBs zxSiY{nsJuS&+z_4;hg2jF1_S-FOFv2OKDky=RUb@bE`ia=m2GqiDV=LqSUJvQ$a({ zTd3GHs34qHfAZ zI$3~T1&5)i7x=4&s$BEOyw>%Ab(ISbIU|yS=+Izg>jH!M>drdO3Ji4&m+oD!EzN!_ zQq`1un?8Mh*qOWSQe>fB%!sT;dAi;M!TYb%B>Gyu6EwUd0U2&Q504J^Cdu+nxO`q75v#7%$(7eu`Ql%-BmID1%ClZ12f8rIm!`3% zpAvPtramQCfh)F7mflxlV^`>6pm8#U>->4W%#a234NlTU3lO?EHPVwpn1^DmVzX{t zRj-vzQ`h#jB&~c(4hzep=9*~&T}D!FWT@`wo8-S#B0a(_S0!c;0~FXpCwu*WNJQy> zNJRWm=bed7A-b(;>1-CmODpi8$~~$42a2i7ok6ctPUq?`ORMnM%mTxKsM`bSJX3!D zE+-+&P<495_?~wn);zYjhsDM~&S#>%QEX}d2M{TND+9MxFSHKjLn}}Vbaf#eO0W>o z+(jTIAZE;cMO@e6yxM)`@Uam4DR%f@5EOOd^t2M7%1=w5fC`2g*uAw>3 zTrkJoEVbP`-*o0oR?kW&$^!WGDg4ZNcGn_Zs*UF62FYwXp3xUG;nke>$qDB#Oh)WH zF_o_-^)wEAm){_h^lce>R#mdUn$?JgWVI%q<68`XkT*3!cQ0yjg6d?j z%=V*zz=GPvb!(m6Ip&(Q)#4Kyn+N9x`^95~aWngQ&I(l}SKH0r;>BHO{hND6 zgdYTVS%s1$CQBi5+0vIa3{J%&GbM+vthJ@5p<_(-ZNv_(khdS?)bx2=`lLjeY~|Ks z=AJV$sY7G#m2$79NH06uN7uynZYTC)RUeLRP9}5-9M(b6xMmebE%ttPo#Eu$4G_xP zzR@jy26Mx%t%dKKzt@6p-Sw5s;NoiUuMJ8I?$!9P1@%(2S3{$I&yYdJ?3N5Krh`y4 z*|I6PVbt%pU;C2H(<$e&8xinPOVSV)#c+Do!FVlXF9*1jve_#tjv65MCTbZQL}nn+IcbYEPsVZ%jDOT zoTpdz*Aer&LYNB-7YyxwXgNoUWd#l%Q4XjPc2|64b_{+!(_UqX*=+M1y zYfHCbe>bXL%-7r1j%>#@YVkSrr!0Akw+DzOMyFP@L>&=m#WhNjg;$5>Pn(-Za7H_5 z5Tt7HqLVKRPjz2C!;8BKhVAx(D|(*utgs5FwLdmWT#DK56d}fsiqW1>xq0I(>k0k5 z$}zWsV4>W&%xK1~q0*z}+0WwI)T=+0(7qSoFUX= zoMX1L>rW9~rfAU>Vhcow3%|4IHnghs&(7d2aHUfiRDN!5+|&51yQ#4OdS&N4r+arp ziWZlimf!b%I@OCC#8LJ0Dzck)41HUxar3DguFG4q)62k+h6XV*<+QF}-aG8~6*;`| z38Du?bM@!PSc#t3boIfqodNCNbK~zu=z6l%vC(Ubqgb$4PY)0SW@*6r2;O?s@EgN= z+bX>ytOBk3-d2hcA>R1(k&*Jgeg`M_8%Zy{!SY+-CTW>mF2hXwh3XcQw0;UV4j$rtCp6O2 z7)0q34F?qy<@%!r4y$wfEF4szDUz9zjdT8{DVw)7;B`rhx7I`DR%243wZBr@?0W7Y z2GO+>`&`CYjrl*?$YbFYMQYOZp)jN-!oR&&T?yH0!ciL>?0Xj2`Ag-%Ba)LpB5F-zbG9e4Y zFU{#?`ZwbVXIw8GSaN*0N3nl4tdXgM4=TF^%hM@y4D)Fyq8%8nIiacrRtt{>c}2LYzG_xz-en8%mv z9V!h|I$}2$4PS?+QQFaE^;lRERnC_ijjB0}_>rFk<_HjukRw31RS9UF8 z&@40NAj5`i%kG}>$w4P9w_xvGPorqXB!#lb<#h+t13qEjU(9$_wD@}zzBG(XE;LKT z>`%8CUK}dNAGFb50U}F0g}K&S4pBRX(^6S1rrGO@zYWt|+&Eq4eRIn-uN&j5>b$$E z%)Mb4uE;c+DwWF=!;+rCV$tb({DkxUOdf-4sS(oav%}4H7uH(#tLG16evf-b05h}X z7)}pMC*N1Qz~#I+d82J-TYcjMXG%bcwl-10Ek8zxr_Lq*-VREv*tzYDjlos~Pl8Cw z{%&awZb7XQ1~C?yO3yE8eHXWNGgH?tOn1>IUMbeYDKN0mX%w|+*d;72+!g{yxBI$t zza15u6?rX6)Q9-cd;2Rba+POTp`*aWYgC>Q)o9(hkWt>uDnmYMgD_zx2rZ&&<6 z7v)hQTlvj!v4hHWjVtYD=xTUTelowYab&qei4k2#frpO0qjw4R0=nUFD?xUtj!i~X z#4E{##Kh)!|HZXkh9)@`bPtEk+-IezkJPH)S4N}I_ym`Ak6WFsecHr?#FfC2$CTLZ zXOH;(f8ns55x24Jm$slo`{Z3F;*_|IOkEsR>UbUziS}K)sT}Seg`}PNcYAnZ>C}9;$hQnkd?~9VI!ti z`Y(Uy>NL+id5crMHY4fGx1^IDNm-IOpR89e!rd*Kq$#Pn*kvGF^lb<<7EhIJ$Udt( z$7|;kbwO3KBlKm)=QoA>yQDO&dNM-0R3ij^T7Cs`Ap7=)HeP(v5xdpJYjEXt+IOz# zesw~rve7ne?)T;MtRJMfif>CgGZQOJhpGdyT8%Wjuc_-4HDrwvs<-!^(60^ItX;MV z@$Gm~$51+#x>{_){Ze#0e>X3e{eX|5v%zK*6?nD}PE1ns_1h?+u?Qj%PId`SK^fT+I9yiamf8VnWO;Y{i@16*{5ls+xAoQ`{ z1>3k2^z+klsIW-y78hSex?Yj49q;d74gxJK-x$gqQ&(3vioef)_(}8QrY|1^Xy}}1 zUnt4SCuK_JU1OT7OR?G9BSw7R`8e+Y5#~6$@2kz6Px4V$U!f9RL62K~IP(vBuN~7O zYIQo2m&vrDy>*UDrAAo*Rv`)4au|tUB4zcxFXo`rA^tvhq1!)qz(W7P)j};** zC0)~ku-XgwYzmLJEE2_iN?aEB^#`-oZp=?R;u6@^)m7|FK$Td#Ex1qv{w}c|RDn(e zKq=6TLJOvSq#6Cn6-{WG?}QeRD6l73dFueB`r{;d5&gymcDfTt$1wa0<&h($vNT7I z^ud=LN7tcy7kN1W^kgd_{rg|){YfK^9UNj}ddSN|N}_~GNd@vY36Lpgp>wf+vN^)0kUa8}H5_q9+Kt{lf$oQ?HIv-8Z?8ik zMu3r{=Aa`_18G3rIzmky1(HHSVm^0>4s^sKoH-~OZsM3N-0y!_>dOfuc;kZ6|3dA1 z2}A#%KMgYq)mP$slLl0m&!6vB9Ul3!#lfRu-^rYaG#CW|I<-Fob69ML6aUd91x+N- zgT^8QE&TleATDksd#!2d)p}|n-eg3-fp!Fo)!9xwuC7i&2}k~ zfEF5{8~l*w5v>o4AD$maS1!hq3=IvnE1j~Dw-cyiQ3@a-bW`zGztYfmYq0&ZjRm?D zx)TKkJ>EXtgA}28OS$?rqSD$XCTT*pBll;t^&Dq@I{SB1|3S3U{2LGZr$kmix5hN+ zSN+q||F^l{_qoTIjo+WN@IPqdAN1@$^tLCU5d1ISk-w;E{*R7?wJ-mXwH{Y?5UP*; z1zDAE-$5(u&x1dh`g_cXPyFxhi$8DX|ML1tuKx>bE-wF{NOKzK3KRINwc^i)h=k@# zhf`m1{g7MAx6&@|VBUr-jA2}VNTxH46_x|u3O6+NY?v%OW^}ye&mG=q!08Q@0>84jze~2CH>cS9+#wmV2^Z6&z4gXXR znAucs^pEG=_*0?yN2`n1m4B0E{}gx*BLc=>8ty-s`1=3&_K#9y`u2jkDw z;$mKw>n#&xzQ&6iaDaMUC?z*Bqc>%0ZkLU;x7C*Hj{H zUsQBFBgMMlW%WD4h_nFj#1}cq{d`Kh-5*1l^J~4fFkoLt-rNI?nHS;hLWmsf7TpYX z$uir~%a%PCqImR%7XJ(Z<%G113{D=Nc1t-0g|;wWZf*sgGFx?!aJdog$8xYR9ckj7 z*(I;nk+b2oK={$BGCjP{`Jdyhx+MQUVl%pj?|(#l@JOL;`oR|k?^H6FgBbXx)vc8p z`$s?0q9};A-H~ zj~zb_mKt6e74W92L(>70u8=nx!E1=r-Jm^GrX|c)?#~-BtQ27LaD|siz-thC;B7?C z(4z;?@s?cl#e$1QuHZcu5uvr#`SZ#CyBce!?E*DXY5r&GKlkVR3vc%m7KL0to@9aNUKpuR z1-n^M^D?Yc=xF~PX@Lp{*%WyZ81lxQI0>IxXgRlxm>7|9ccs$U+PXD4F_kj9^>uZZ z-QNjsjZWG~#%rr6i80wmxooS2SBh0N5I56zr_?gt&+b3zqN*aBu{%PSsg%js`&`v+ ziEblRj&ReGe(t;y4LjqN=#-9`+k}yZARW%(g7oC1`^>L=vBrX=M!D$K=rD0hwPBs~ z_n(MPt}5#qsgaQhrul5+b|?PNq_G2_MBy`^1BZ+#Q5-qe+$99@n|t1U5#}y)Ymm>? zAx0eoPwBCfulq*F?k;zUklO?g-x82`pzTlI*3&!SnFEE-P&R8hE!KNOU(P2kZ{VdI zB^7Ueo|ir<8|{`qw%xdCy16l|MC=Lo6>TDKhdVpi*eLW^A+53sVc zW$C8J;fH2u_tSBQF}J}lftp=zZ;b2?}mvGDGvsEHa5 z)r>4S5;|Ruy8xC8unG6U8-~DBf+0`7to91?nhh^u z=}>k|eFTAf*fHO_%$@x9%P+yZ-yT+ql}Uo9D!Q4)>sy^A=Xe7W+D%WF zV*Rc0AeHXJH5>9-x_Z02;#hvxPnG$#`6-H-(+@i4&AQfhWa7%^1H>@F!;|w<+2#L_ zwfBI>djJ3bHK>e~NE8wgLdnQ3B`ajhjIuMz9v4wk$`09O?=57LkWKa`dtBCKUB>_U zuA_6#=bZ27`@7x#U$=8R-3r%wzuvF$d^{far{$#S{;cSCf=1q&g2A#7=bv3b_i z-?Lt~D`Il;$?S&mgy(L-3ET6b$8<|yKr|%~a!)9MTh{$xC!ma>n?=pUHF6W`n0{rXO}} z`5CN!a~w)ht-}vpZMx>^(`X+d+17f9pA%E1LfW%UTe3CySg92TW))apIQDBC= z7arx#reuBRtovTQ&jgN5jYX9=Vmtlt;lnu=Vg}&VAgC&ssDY7@0&(*C$J{Ie0vcd0 z#dg(5gKHH*VU5=Z&jM~j1r&%qj1c;^kIkj{=^P)E`FJTllEB1#;qHuQmHJ%Cb^c(JHH)gkY_2I+N3GoQ9*ZXYc%WhRzY_?u+Dj76#06+Kb|x9E zyvsztvJvJH36WsJpY5rWNh_a6w4-2Ym9e$vOVRoS?k|*DZlMMhKrWsi3R<6hP}P={ z-0`nM&o|q(FG6YBe4@lc81IrWH}%ZN6?eHlqiMMemp*vD4D39$qZJ(1qdBX*8*Z{o zMqrTiv{5{7ru){%YN?d5vF4=PNk`MR#~mfwHgg!QR)@{39k;jwnN{x7R#$eU4Vg&F zN_9*OSvI}By{lGe@p&eHDz;XiicGEeE%humzQ11}SEoa^a6-GpE}ps5@Iw%l11M@n zd5({tRZ6OS54|{af86rPlYk7D4|*%BYmFYA=h$q;_b&gja_*4^R4h=U%MBI8mnWn&9Zw!aT%#3w{4CspQC*;>FPk?cwS-4pRw97*6aPM=mGv7jDlR>?f>w_~GU{ z5y2arO3+HUfG_EXLr%7A*_!^mEBcZI6Kqmsl{V#h_T=K4V_bVb@!T&WCUGr1`(G5R zPVM>!XFRnEwRSPa6Az{Rf`2MXYtfP_$w+i)Rc@)R!)gXmkKm9p4dD@Gz3}jG#n1Aw zN+1e7YTS98*ei5ZL&*8&n(;w1xjPP@y=i(9JUeF8+K`{iQq!d3&1C7~5F=htj+NVPCgw7VT?Wt3hv3jgs|j$dFkF%{UC%r zJYvfnoowx*lB%UG=aITX(~I@cns2|o=lHRt6g$d#@k>p2@$QYAu-oK!oJmUHw3$;) zyPxxw!x{zFHKd{mNIOfwIf}s5h^I%eGKf<6)tf2>9DBPlVFOzF#V?@fe!Bbi4^S4q69k*pT1se~%WBnDP;bIHnuS|mlJZNQWJm@VHT%F>M6tRz)wHrkq=SuQMJyHzU2 zroOLUwDGLk-ihVenH7f__q3V4nd1=x5wQ>>TFqZ?tFoc&SnGVdN09%xsVU!O;m|Mn zN+|Tn&FSsMgV*0`o;^JkVPJCqQ)+{{y4AAH{7|WU&6;W3Ax)1Sy*&#;Hnwz!g}`;| z-G(PbGlPmdMV(!)!ug4kX?Ra{Z#+>+ZvT*%++h^2d+}S!R!JkKA%$jk!%x`SusNuV zoe*)fZhn9*f&*;#KntZu0&sv;k^|z;+|$(4tZGw$e(HKoER+b<7ZmW4cp8NP2nm># zlEwB{C+X<9a-??V^yVj|dL0*u>rHsN=3IOUHj8H30y(7|XkB=yghDOqvC`rV-|MbP zFjLRy1V+Lf^Ck9C1YcOH;E~bQ`h24A*E#OhyNs!9Z)c7--=^Y=)U`)pYA9W34646q zVn^zmYwpV>v_E|p9NVU&zlklF+Ix9ACzh8#OflrYcmt}&_kh7YX%{5nLq0U-wjvg!F9|odJ4kMA`>*c(T z*+2?zBVx0Nd>?Q}BR@_~Zh60y=e9w{@(Qt{(_3rdnrbcoA?r=4prqK7V`U2Ry2TvV zIDU+&h{tG8r~B&x|L?qu9rm<;K!9b_?wdk-?Y;gk#$^m~L)Lpur^kbv7n!aU6cnTI zr$-9|loeK8`A-V-PCRdl;D?-o1e{aaVDpCgt{@8l!zADessW@;X%LEQ$n5geW_PmP z0rB#(s%G9mz(Qb4v1>2>i(xi`++AFz>HBmJQ_y_(YkE;_86^M*T($?Vm{L-4#%@22 zZ9NuaVJn|?f;fc+$Lx{(+J)-$bPbu!ix)du3a1F`ZDuq+r+?8;G~P53&bE6m&8*Uv z`n*Q|=|IiG^E!v6fdG)8-s$l>T@WoZmu_jvN;p$6bWxXk;oc3)S>euu>fgHpz4+-R zVA9sjpO<^EQfoqSmjRdajbg){Sw`veE)X9gL*hfYWJql1JXN2g>Ac%dG3v8ab^Z5R zYZ^8-GiJ5yZ14FZt)QDSwVWzWs-q_T0rxK54nbl2swu$(pLWq>kBiFWn2DJ=oD%;`7t#aFSEH zKh&ot2u@dd+cgyd%%b@Sa9WX+1yZIgD7ap~GY1&aRzRZ0T-H4Ij41ZuL` zRRiFsIE4EKj$K4x2Mpzt^i9OOJW)*ks3@Q@#6?Z;^ShS1Yju2%LZYb1qg`?JNn5C~ zJj34Kshg>{^htXPad~Dd7a{W<4XZuISwJJ?{>z|@!t+dyw8ax%Zn=6`vg$8!ESJht z8L5vc7#jz1Z~I{%KK2zpo%UKO0lQTpvTa zWoQD5M{~B%!&C8zTU}@-{n;qbfo!RfLyoo8^|u%k8td2BXc>QtNQ@~K76tgYWbNN* zg#CS7PKs)*3#=JEbYzZJmg+EFdO^>Wtt7j%F`mLqsU=!1snq^eul-$QXlf`CO%VO& z29RCFBeZYGk>N8(3VYo;zMhAU&tUYvXV)XitdyP|#Qr`Gwjf-FgE#$GJ3P#j@7*{l zxcz0tKlb!Ibr;rrts_IY`CdmaQJ&tsJTi(HqwK4)n}s{s1ANSB$&M4YPM`9?45&O* zS{aN_)}Z6);yb^`Y2KxIjiKZtNgNAP@nayBYF7m>t71x8e zBolQpc=k$%3LajuYi2~&JQZzJ99Z-dfr8{83k4^mwYeTjA*X^thgnwlmoH~r0D35_ zmAY^T!th;SrAN}HAa{Y!Lp6S{#qzO1lOU6=twD*vhvMQAja*0b)R%9&({fi$XgeSc zxV&ziSNuPvYy{s+NjJ-5zB$kIe=Kk+*0kbfkmg_iG7}P<&%(ehC`RS$;;eR(B_}Lk z%lg>6V2^+`8tK-)fad!H&D7_HFKB1^i2IiziEhBC#gQD=XoT}IPf{GlVveCIS_ z_sgH*q$j3)mT~La0rU~!Lb62;!~wjV;?z1o84rk&F_Q9dPUbXwUm1l?f2S~+TQqdm zQ|nWw|Kwb__K(wws^emW?|A9OpYX36Sr!RN7WrZ=U;6D)<}Sp*MQ44_t-&Pmgjp{A zQ{cCn~{x@k4ew8yutG4@MTJDjtpcCN2HBs<3XaW~_w zN|wJKtG#ZJ^@Y|{?V5Jo>!oEDjoT+X zE_9^V;}m|LD0y&ou6~2qOL(sFk;We3wPALmz6_=*=JQdhnk~0|iY;FA*T>(L2GnR=O+lo*^^EGIec3Imsg|3tx;0`1 zRaCk(+J6?gY>$9(;3y3Z&F01isTCLU!^53mh;RI-B_Ff{{(scg_e;7qIS2Wt=jZC?V4~ z?LjQR>hgdo`)?U9gQoB#gm?qlpnJD(zd)Fn$o>aJLYox2Ke%gi(dWriK@?B|(gnf> z2Noyfb2jF((oes+p+-v{Vp;x9pHa^SkFnw$9%9DH9j#B52Z78 zR&HDCr9wcD3e@im?d?P%D<13p?As8@%5oHZ{VNtVS9t}WZP}S0QDz`Uixf{k0|6gN z;$385Ky(-XSP0OjfP*o}abn03Er@{kVQVfALAvolJ8(t)*wY z?gFq*1aV5|BcPiX^+yudCW-Es3WbE%1kw2>e^qdMXRJXX+F`Le1Q=Rms`?kfliao~ z*Iw)of$M(?D*Yo!d4({(vG1SL&m&}p{YOp*7s+h>$2|eF=01kb4K&3+X>a>?-QN;F z|C~yZN&9zTX&*sX0XeDPNzUJz-QTiJHWbA`hJwJJ>{|EFRRL#@ch9hQ84phnM4`VdG9T%rsiT)H;qOnP3#s24zU@iAY7IUX_NdBa#Ugh# z8_G+zvQbWkWXswA_mP_aMaUT6G8>pDB4dxpktM2XX&{d591(U=2|hrRqMH_EV|>gk z{{N17_XiLz!esIi7q3k9x9{>P>2yjP=3q8RF)(h=&}O>25ba6o(}L0*RBV;+>9W1M z$|UVfw_Ya4zZUV~Rd1T<0AYW0%Fv{G*CUsx;7ck}^O5I1J}cXFG;Q|`QQMPRTer7> zd{E&C)@k?q2tXyC14XJ9xMG>vT-Mr?A7PJUIteT|2<*8Q)tZV8#zaT|%xFT78N~ep zcPzBDA%R%sU7$zii&3HZrl(;Qao>9}M2<=#sxNJQE+{tBb8@J@V=f6nqY1KdHFFek zvvrQ%M^;K*>V?fvEeG?+NSdpf?$14qm!}c}PuTL7g}R5SuGa_m<~qIXwWdiD zGH(b9>$!F9D@M-2VX$jGDvaD@dL5l?v*f*>jbEw>3ds*>hp?*f5Tk^%@;S_&qR`lfS<1Ut z?hy51R5H4p75zp}ZaM3kU);4uVNW0Lc(&fDW=hm2%+8aOAgN*&KIyFEVgkV->3aP{ z6bLw2eH)kNGkaid4?Ar#ZHrExe!kOT{zCw%@xOi2IW#F+#gg(6-AZ}I!7uXMavc4w zYlG-CC>6qO_JAf|(9UI{a1xp{AssbfVwV63L0T0 zzmLFRp-U0M5PPgQj=%KU3ct zh1m%9?$#}?2j$Py)7LvbH@?4m3)1GxD=X~}eFWn-Htgy*)uHzZ(qjq`@bI6gsOW%v z5gHF>wt=>3V~P1c`OqqvxwX2TCaJn_$lNthLqA{QL3eAmpi;~E;?ZW~jZWjeH4iE_K#whj}D z^&Qn)HAIg<$sMyY{MWImq zyu9^&?6t=H1rG}^80QCt6{$FL5%Xkj31tNCpmr^W)=6E)Cx#|xT_TcuT~@$)XhiO= zQXuAj@J))LogSBqov$u?l+xYR>1{*G^oM8S5B4o^=X2SWIc;WxGb|b$clGrwljITL zI2_*-^P-G{!l4PIFO1vcy}*(ZUmu)9rws5RB%CqP5E6svLK}-C4)b|koQ`XcQ+5D_ zEGg!F4k4IxLgNMCAuE9^KCc*I@J8@j-T@$DCs@%iP$Hg%U7#}74j^~dBbB%aauMMJ zfUX<|HDuM9Wm}}q4&h3Z3O8J}>_@MGp_>ld(Wd2HXi|dY)=O5J_yL3-b;pM~jc3S7 z0criz+YJ41lA#yZO(e+!+uv2BmypZet^@3l@<7~z+f^HU`z2`(G`vr53-7E3AeAy8 zMjIpMT-X3!lt5bMK8C$s#vW%iqK_|srMe7Km&w^bXApq{P)rIFl z$a^fE%{dK)V=gn5b*SXd;gfybIQiAfD6O6?Y%!9<3aJ^=LP&pS^J zxvuzf=%^zJX3`dbH3LY=K*|9QMM$x;9(eEY5J)F9=iLZF&Q11w+s zoAXHc(up{oF!M!|XDU`ZgeF$R)0(=bQ3z@Iz$^U#c@6)NM1Cr6?U+>srh zOx2ODA<(u9a0V}+KUf0%aCch}jQE+HW+4SI_FTqNa2onv^r1%>fs`DNUTN8l;7au( zt*X>9O#r3>YV`P604f86P$6K3o`Q;oAGBD5#MzJO=_Fs@;<8x4cL#17c znw`7v^f;Hku8+N(c>t0W$F7oFvIda;6vXVYgQ^TS$eXF_^X?*c=G{$&f%aU>bad4& z$yoX&78V5|p4B`b?PqM^btOZi52G#XXc7zFgF+|Rr);t%#?AyNveMm~4r_VMgRNDq|Yx-4Fzjj&W;4!$cc&lh(b7a@Ru$%{fi2tJDg-Ybhe`={q_l&@u{|_gp$( zzBLM7woYijVU|P%8LLb%=Q43{$isBU2cUT;Cnu{PwI?wP1M1M_ChtdGZLKd{%MR!C z-SYDi(1@-DicrfM{b=P`Dr#yoiUO&g$;q!FM_iB)p|WtScpGS6igB35zFygzeOb<~ z&XF8#%b&5nvh&UjpifBCtiN@GOz9gBRrH9N;-|I}%B=;Bi(j={zXl2$_Iljnno7IR zi?^GZ0rH+<#p=nRt^qvhPxVh=1%>SCg|9sh&A6D8t~unhwzm%tWF=54 zYqWHUqTtRmsXEB|UVjh0l9JqElED!;!y>d6-O0YGmLp6NJDB0ZqN0+c=|f=ha-np3 z7I*v;9vU`3;6QAH#bJ*-BPGT9N9Q9BCKeXQv@ zciHM{A`UuElkilXVumkVZ(Y$-alkoWDHW800uOWNusS|K_CYvs6tKD{bak0#-Tb|h*9FN#YEN(^O#6{K%emjC?Rxc@xWL6qj<{Qg^M_uqQ z-bpVi9b-=tU+On-c5pDz9(v8AHMA7`V?1nS$o0_Q;euuutN<;W8m*4KOVs4_zo zI?ewcfh*dXHQwvgOIFK>NDDpuBc+eB7{;wCtl4d`5&@hR!{z7JOKQG+>2LdBhqyfe z57bdImQQ)CELp@I|66Ts3n)rRM=Xh+_N@$!Lftx8VObF?JR2JuJ~44w+Kx7YL`4>Q z@T3RQBV9G&oOCuPp>iQ#6j++Ss@RWiRN`gxDva7Ms6ukn)GUNJXvF{dW4IY#FU0DS>{b5?0Jqr%}2AmC?K>iS=b9v}b!_@Efq z+vDR7`Rbokz>M*{U1(RNg=F3GA+Q$I1!quS@A-ibEhL>? zwh{V;>xFOLgn1%tKrFW^H5S48#9+B+1}ESLt3IKWQnD~R8Bxd49}sO32322-QD)YA zFMiVRy$<7x<)<;$dSk~W{QV-+yG)o8OmYOY0_kMf`zg$Wf%OJ)~87 z)3dkiW`zsUpnSk7tBG!zj>q9x%>3MFye~;0S)R-DZ(X&erCzC*sfNmK=7kFR(d{)^ zTPmfiS=w(czHr?R>RR7yJzLr=OVbnQXts=^Mn1cBHJ2!45U+nKs2du)v*xm4E3h|! zu(aOwX_-312mzStcLY2H2NGyJbqm>gA$e$MXS2I={2f)r9>hm-t)}Iv1nll1juoW2 zh&tvKSSMhz#Xwob1RTvsm%&KqEhBq7yV}*RF%(i8tgRJCI=z(bZlwU66ls=(v~}Eq zhclbL4pls)#SXLsNkU8)&;&{mdOoqP`}t6ENg~av5L_KtZH>WFi?HXw-|W)911WlW zaI&={--H>;2<*|J*Plc;&qrVK&TA$THEDk@Z;+$Mhr*sGr_59G~E*7fF_!j@Mc zkw(Z-2^fK?kzLyzMJ2g9J$LJ85jr4^$%J7aT6ns0nl4n>^j({L033C0`KKT6cVvM| zATh>SJ*n=Pr%z$x#``w{4zV~~rhS@cRdzl!nt=19U2L_g%N$9zS%+D@qi@`P^!~In z*7c&xSf{KZTq3nRi)4u6C0`W2+g2Cj_&u>>%s=+~J9^eFGq>pD^WVqc7+5V&QKR@b ziK?{l+C2J&yqWWc19`(oX-o|`3@XH=bc;Qpf&=;NdBZIg7rX&B9OOOT2>CD-^3+V`uJgVvrk<7o3moLIp*l5anX8*m7$)UO&#rFV`q|d;QQ(6wGAp^CQ3Tu&ku{rCQ0%>Paj;COc z+~CPLCA~KBLOc7ZADm{v7KisyiDgd7xA;}2DyI(t4N=b?OP)p8aB;ei*uii%*`#Z| zgw@e#vbU$VWJF9fN-#QZ$XiiOEjzixrQ3K5MBtFGu$Pg*&05wugh8W|OyRQC^vd9qh^4+7R?|zT+EVR1A zc-*voPFBko0%7CHTy<#ugWQ&V^$&xg(J2g^c7Akm4DGF#Q?LWY$H$k4-6Uo@A>StI zNtyFbE(&XdH2j121cAQ}==YQWP=WDJGaRTbD`c|(yGUiAMI+cmKms8rarrg!O6VGb z*_zEjAo8E>mZE_{{~her(0pa6?JANOgw3X^X>V>T6dyW3K1~s;KzhYQMn)ptSrN0f zy}f-BoRuh{jg0hqUyK+rH0_-N(@hK9nPg|qB#Kenf6>PT#eyd(8QPv8R)6q}z-^Z0 zLRMGS&S~5y25HYNqhG1HM}=xLysMTe;+x};ZzFXv{d6bK!Svl37g3f8RP08#p?gqb zVkA4tEJWFn!8k*Py62(<<(@z0yxCO2IPC84*1B-fsk6{7cm{1RW{v7bE2Tbqu~ou% zU&uxJc^L^xnV~&zh*>HyBZ=`yaYA(tBjQPB1_Dqd<+7hhRW^CC)ql(R6?PujOu0Eb zH|toDJ0dCJsqp$~9_Gt1d+Nf&;-#(hr{-s2pVXNg#lTFv7A;cAJoB2otoDgI;W>|A zitfCP`~OuOlIOCnhnvFsZYjVJI{iana$m~M>loi;AAdT4L5+_}0Pwn~l%>-sCU&EK z3soT|`L-zWLN!Zr{fhR)d+sum9gWQ`k3_}lmz$l`{Tfx=sCU3`#8uea5@L^9!ES$Z zKc&2*8E3Y(zWEKxnHQO7>MFWQn-Rm|=&&+U$zXc@WOsvj z%b#5c%|LB?r4!v%`|)jzXpf~go~GrU(ogcDR%0x>a|N}ly`;LsZ;MlGW3KB;RiqOa z?!!|SFwjaI56vLspaG9!p0N^gWQK}VHo{MbeIYo;eyR&pqu$iT2?+_aK;vtNOyBs} zSPWosOrVOutE|&31)EH301#>nL4gY^ocuF`wV;3h?uo1reuu?DX!V$9jAr9kXRu2{IkKkMHh&geTDO4)xWrN+tvFW zYu2M8|LB=RQ}v*?_)lf_w^~;bGy3@DZyeh{RF2wFUi6=xaDEF4h#>u2`ur_p{!PXB z&t#B|4)nqKGxoKwyuR5pM>kbH{JeGjnTr8^$Q-s*>H>lPD^@qPTXXNC4PWP_W) zD(Nz%ab4;)o|jkR&l9~D8vD^W?PwnRF%o}qU(+V6nDH5glMVEArBRcG)Rt)8^~h@m z6NBNK5svBMr#h2}=+L)+eW`gz*h29T`C_fnS^4#ku_r|=D*3E+enh|`4qxK+SC?ge zeT$Ozx=uvzmHofQj-Rn-{PpWzzR%Z-QwaXIM-I=FLH+)nwx@H&r{FAq@}%FLqqI!< z<9g5-^aQN@EnQt=78X~a5~QKK1>{LGIP$^2d6bn2LxZQKWOIe2%#}Z0l6f9Xytpvl z;T0Z+?wIC>@$fEOzD$^JKBOE1UF1NETfG4lf+x_2%WCHPF#zmT0@{#E`HsyX!2jWE zDvjHq=^Wv?>nGrZCki>2B}n5|w6vUnl(tfcGc+bN>_{eqnf#Eju<+dw4qQ+Jz99YL zvpBN%Uj-#CIkfmt*3zQ(rWW*sjAu1pk|OdaM2`|10)XlKjv5DUP*3TMoP|U!V4;rk^Yh1HY;0_I}>%INs^OSSHX4ZfGE$oJj26E(VaWX%Bx)UcE zXffN#8i#?Xms?3m$v0GAUtgJ`gY|>`3(YBVL*DGoU54iXSZRw+UP(_#@BpI^EjPDv zmJC}k9XI!BD2y=AB294N?LdD?!mf{fd$Ed`l7)`{kCC~mJUdvz58X?j!}xEh3@OjK) z4x7PhSR$3o_~E!?IST||Pk1!r0!7)y$UpCZKR;Z%=NHhu-hRKo#dy-K%>Bf#vAVUh zl~CO8J&>nW?WtthEs&JEeZxNZ**8hMQx7ynHX{_19$ORmjSdU*j%yM!(|ILR==AI^ zv*88?mP)%0S)slaol(5gJHbddKDV^Yh8KA9$PneY<_ndt_p-JWQ==~Y8XT{f&)@lD zfQr-o5Ro4gO}z4#J7@n>_qzjc0P~l7HEVxJ#*SZq{Kr7!bgP=^@c8rH)cpBI!~JaY z{@P$5>GMEsY#e*a0@jtVjV>#cs$i1&Ed{-iPd!g{7^|Hb$P zJ^Vcq-TeL^-c+-_3eEm!^eXq<{;P;R`5&{)pPyCj__(H<=kxs+36oyaANP}A&{(GZ zuc@r)n42ak?{qf5!dMdRxuAYU0;q0@vyscLw*r{`T#{CRIkJnujSg z`!5xK@n0ukr>3Hx&MPc_>>A0$?mlw;CVknYZ`x%dD&?Pn>uLQ{8z1fphXk z(|AYE@!JqWWxNWK<$fU{$AI(AY1DQY4o_V4~wm!#Nq>;QhUPAXk53QwJ`lZBVv8E}mw(0Kkk`(q{=SAFb!GolI z`Imjl-Cam5gvYp7SBXYu$X*0#idB4Vy;a2(?LRlPNnm5H^}6A$RY8GcOwF_Adxer1 z-S#~)n&+&-?00(S!!j)`M1zSvs>+maRj;MKwMy0IqA~Dh9M+NHPF5rm@i`Dx)zq4I zIr$d*;)av+s894tVSs`33(TeJ&FykZ`i0G7y!S;XS56NEHct*oUz%_dx`JOS5EaZ@ z|1xjnYO-*Hv9d>L4D0R;$C><3UxUIEy123?A7X=zRGk}i zIT4($aR|rGQTb~*vE!w~mPIhh*9^LA9$><5->K|=3_WG7=99#L3N_e#SeaBP_BMFW4 zHm(E5t->+(HV8mkwK6}$XoE)w1Y0b=jQXXFGmG$u3neK|6ZJ>P8O*MW3;VtjHn#l|hs!d&x1*?< zZ?{|(eygi4WCGh48tb9zodAQA+kLVvIa%Koxu!18@ss+9N~v5Zb|k+Xvce_6 zQlxYD2WNkMtzyXTMv_a*cEr|ue(MXTo8BK(H(`0}y^U|%_NHl1f0kbT>AC*G zQ}w~@>{roHB546d3&0Y1klhwFG`s{rySG54YzXBdK&)gJ=Fw$)-mqMYFa!Wo`vAz+ zN?T7pKzaR)kkfTUcve+Ys~jAphQ^zo^CCxY-?>xS(Lu%$Lg?-74L?$#>u6@i24WmS z069ZJL3{oB83a52Si97Tx1q5y3)Hub&CQDLZq=o#>WA>H8&C<}Zl*H^oy{I)-;#4)Vx>pSi(ct0XWoBoK!0U!;uVgDena7EPV!A5PH^XFy zHR(t{HI*86+2So2^nWcJb9~ciYlr4I%suz=8J^~Y`6+kh5{8>%vNViiJUBS9ZIV~G zbL7;TsD=oJdec58m@6uG#26f<_02T6NNKxq#+fUuYOwl*_@4Sxx z-K?LCYiOEKosm5ked?H|AZigfKpeC_Zgt}GQLTBboTp^<4x34-z~3buwZqE znzV6n^5xSE!dKoRHU3f{np zdwXRo_RSJ49jw)x#iyGm$H$u%o?j8`HsY2KAkNaR36%&sZcW-xRfJ144fKNm0Q ztWC`FD+|%kZ&7R2c~PAsTb^FEGM}F*Jg2+2F?>>^vdA#;^eTt*!1CGNPmjGjKT3}* z%)IrBB79bQmzaNTK_$ewGI3<;I|HGTK>x_Z+>5KXgkSm+Y@?zL>8mkeOxFXPsQ0js zaGX-?Dmr>j?qTh4o~|sPaJ-U!Ipt35Nws!+mALyk`bP-~zks?XbvGY|M{Hc&2qLZ( z0!8HXtlB4oIN38Mlwf0@wid>cl^duYrjzXftyd2Q`cXj~4Y7d)UCyagl^PB{c2 zt^j|@2^7BTF1rHYrX++|z33p6K`zkJ9sn)78aVc?c_u2k#vS+w-X+$4arglEFWkZP zHv)u#0tXB;GKg_5UAlB5K_;RF>N4R1_9W2v?+mBm33?KVq`@4RhC!}81d*^?^714= z_Iw6H`7OmSQIV3qel}FR_icw4RJ5~XhRP3n2OfGdHhMMC9-m;@*8xML=*;YMo7ug{ zd`EXBR)g0|z03bZ_pl&F`I*+Y68}LYo3s9`b4hTe*U2T}{xY1jBIL_KuclViS2_+8B>vT3)A8)BW-VQh{a^6&1 zpkWp_P)9-{aC`e8y>`JXHCNeP?;y#zM6xNLYju-SwVStLa=^zYc%ZAB+RcbFH9f;T zub?7Ep5X7_q3RI5{E=+EIQUCf7dfMB^6qm;qEbE7)*d2hhxW%uL0#B@hUT<>;={AE zZ^C%YM*-nk11c@qdgqbDhtFTQa1iHSoFthOc0T`=mlsG6tQMFVC72EAI5|l_fBtM? zZ7m9O%>f)Jw^aj_5BctOKE8uEaG|}RY^MV~$=`FEQsSH!7N!|Oty6)w=K!ho2BT~w zAx`bLZzB5o3`lgkdtq`?WoDh_;zd|-ai{tVuYr_{b7Q*3JzrF&lM3gVUs7P31DyiP zk4N!I4J+rd)Gvxpykuyel#ne+-9C#I>#>^Pr!2>9xVdsf^zXDT8o_*_s@C^#Y{qi+`QLdY`RI-;8i0WH$+GX(Txlgwqv}|yGU76CV@$UJK;G12Qgz{8W zKL%x77^L~$I$bxHu&;0U=BB~s5my+}=0IS1O{2s)M-jW>JWi>quEy+)V_|LcBEpL+ zD0Pb>29Nkf>0O#KvmGMaw)Q9M3xauFu99NAHq|G%Bxm{2BCp8rL`a=gl97}YfeLBc zE)+AL&CNa5D08MtPZvFP3it5gOXHRn7Uh8IIDiA!NmNmhR6szW1*$>F!~p;70h?Yh z*t)}sdXk~0zOm6gup>bDJRuPg8P$rxy19|jYw%UQaCiR*qv9wLktm#bhllTdmf${k z=uj*4_uIf?>7Yme4W+*TqvHqx0YTt2tVe!fDNfBF?lK%Y&(g7!TRr_HtvioFWa)EX z3tCD%je67G$6{j9hSQK=b*$!s9^+`f&a9_+^(^sjzG_Sj0ih9bhB4-e@XGPs?n1({ z%iA<~PA7>pOL%4-MUtndrgRr4b26Pq9y#?E9fQ?qks$HS4A)u3hO-m7{lc%+vskw3 zHj8I{IrySzdc3zx?SvQ|6jJY(QDBc()6JwDt=&D#8y6GvyzZfx&e!~*kEo1YPjP39 zG)jR81@{k_h;?XzreO>M9Xy0m+y>-U{URc~;0Qeepsqxy8n+3(_41PH-)k4XaasKnVU-7Q4IG#k zVNdx0!1u3SzrG0_D9#5;Mq#rq2n%a3?ZNNTGBDsREiHBD7!aSntojVx><3|@W*(}6 zddtH$`tjE~aKIWKq|YWrzgtTr=_Z6pk}QLO!1HCr#G|;X?gr&7Ax0J|8@6OI!!wlX zH!h^TIIn7ZZuA?tG=?#4o%w0;BAMwf5c{lZH8oralBySrP6272yhv717gH%J2 zO*{8(^M1FU0EY7R0coQ!pWq|To}sRD;YVPVdR7?1Bt)@;>r{NbH@bMy;}oWK#&K|c zzRv@8QXi#){Ta!Oda^I3rlmm>6~e&2YaARnq(s89;^Oyaw!cyp)*0B%si`mD+unya~C+R)sm|Ytm7*aliU;uYAFHSln)g@n~VuWY_9 zAW9@DU)c;}7;7HOG**^1im+bUDp;RJEC&57#h&;p~<9a+=BMrzoVP6f79Oc1384%&B>gx%BV5gdIMwPBr;t4o<-NoUGSDv1gz?i#YHFb}kk&zBoRw$@m#^n46 zX4m$HQE>Rkkt!&Nf^PK^1`Diy5A^ihwMra5LRs&o7rWf7gVv(*UN~@_r0C$LJ@LtVWjSrT=)qFAlu4ft zeJwQKa$sglFw;OE-adG-fP(%sG(Jxdmcvm>GZgdW)U*G5>nVR}G zOjRo;5g2@W-ce`T?P!6clIS>dN2aYhCv4)PZ{{4wc@{N+I!3^vZngX149*ApqR97{ z@f&kJ+4#G8l%sGiezI9f;k2=IxLRn>)5rC767J=+`6pvDWvbZryN5eW-Hf@kTsX-~ zsH-=fCIePBKc=lb*lyU|o-9NSYsTOj3t9@y?&zGqbPVJ%sYJdj(}Z&p7{!!Em_ zwDe`mlz(wbj!n&j`vA_}Ff40o+U2W>wz4=kR$sEJo-R3l>JE`dNg8V#S`P<@a22Ct z_<CgFYCc88+Is_O>Polt~YGGmVvjBGa@`*EN zUcn3&BO4_YH=}Ah*L@O}qW3~5K8Llr*MKA_C@A;<2M^Dl9}(fqkW)A&9q>o{pm49yi9~A^llh|g9}nn zhXt?&)uM(ZXX?0hstTG>jkw@1O`s$1O#+ z=HYxwt0{3wNld_Te3h7Z>5-mZMPnmTjzRMsXb>Q!S>qY4)qUf~q~MpPj#EohH&1I6 z8-MIur1=8&76~;%j`ehhe}(htZjr*!%05 zC#M+dNrb*C^%3 zu%boT$qIfZ3kQ=IoJJltnn!}{2gLJ+gAT#Q_e4=AX+(2GiSbA56{yR=`Dk%CX{Atm zp4-l1kL|dr<5MBD(B0}yfzl}_tsbArm1TY96h0AM6(%i}2rgrIgXq? zQy>s>Xli79_Ile0onnOG@r5dfu~v*?_?F?pHr?HOu@alsjH{0?k5FAb_p_EKUO8fO z$alSg-bPU4p@KJFsx`8hBs-AZUEn+0zZ7x&eMzIU7R zR`DM7*4h+4j(Ay^tGjSoWk~~}>V4G@dhK_n2E2UmF3U!17^JccoGKb5C0Y6;cV(7`BBxel{r5mWQgJsiO?`*Fo zzRhivy@O9oD6)!quVX;OMYtYoAY}0huG8_Ce}nT`~Br#s_OeCeWSySsS1Cs(f@13{Q6_9 zKSe?2xFTD0G@RJ3aB;a87V>VbqkZP)=1AIsrcMZY-jyp?o~5L)ydtROq%)Oe~JMwinoJ6_q2T+Kot?@?5x*+_ zexadi$tb9u=m0hdY7{L}RAKvKLb3(SQ63G@0YR_7;0bfPHx>VBlGm|c#=*;yp&1X; zVXkT4X&4Toj~@My8Xp(@W6;E&j6TPh`b&+BljH{=gv;P+pvst&EKtreiKpW3$E z+z$4aIFiHPFHV%X>newUnt#O>`{ z!gGQSq`;6nh%?uhPyDp-926X@C+gv(t*UzF5eLO5vjKb*YA2YD&ZBW(7zW8E-_R{8 ziUyv?-SyCsQE-vJdh@0V)V!r#ESg0>wCu?ko)Zf71bW`#h*GUXQuG2N;}P)qpUTe8 z_6-g7{Qg~$^z`YVt?u8dOki6mmkF}l;WQsS2itCdX;dK0;=YxY6=bJ!gc!QCA!2g% z-Bo1wi~VdhP0~LwAZ4wwuNuFStZQo{X>Dz-HnW9xji0;9pk!)XxE{5C4ccBUhi9fo zkL-W8p!MwEA#F!_5220!RrnIQvYP%^_2~E0<(~WVGg*{)^6#>lNYk;u--!PzZ&mzH zck2t^VB2HN$M^NFziDbu2Uq?dUKmU{|Ngev41Q>8{zbpsA0r^Iy&fh!_-oFJJrKoK z%a;F8jOZHt-{c_Lo-t6F>N1+--u=zYlbPI+Wg{i5gBk2M8(#M#%BkOJR}Sa0p$q7) z;PZbGQ#Yi$5{lp4)QdHBeriwdnv1i4W5=F!L+lUmuz$>fPxnWJ-d?PB8@m7e zp>y1_zg{0@1$?~!s-qsJL;vlKPyY5!JlUTzjSh=7ru@59`X74Zzh3jB6*?<3mHQLx zU$xSIT=e}PGCGX@f6yzDDf;ZcUh=oae|x?A1N(1Qk*7kFnx=obu77@@;34^|F8vn| ziCuHi|N2SOPQI}I_dCSR$Mb(*QZ~Z>rXT<1$$u;_vx&G@?0-h^LGE8GP7yZp@lS@| z0Jz->wAS~bp_NdNhS;YVSTT~8@o8H=Tbqc}lRO?Q-i-6cekBfrmaH|f>BGU{&Lg`67j(rzZIWRy4tBjo5VjJ{mL7=6epkUu|O%#7|Vgohn zbWV7cg<7!IEk{K&6#qKO%1$0gur_-y<{J1jEtf=9eb`47d2cW^VhCz7UD`GJ zi>*jVl1OdXoToOYWm`JhyB>HY(u*9O8!E;Tb740&?_%a^U8p*$+EWz#p8cu~(Wvb% zJQinn;a0SC#xaXEyS72~VA(I#*NzoLJvj>!UV$C%N74M&%qNR27VuDIXtg)pruBY- zet3*L=2r7O#}~AAtK;|hb%>p@+q4?x%b=u*z`)&aRlN zKi;4@m7$#s+?j0uXIf}%s9sg?;+YN_eXf*SL#?M>tSR2At3Q-#YENWKZlWX@OIBK( zQp4YkC_U4qVkR#+wk9EK_jZmrq=YD2CbC*MO6KN-pF(IVeu+DDR!0O?Sa*@SFL-{c zKiqtNf{JRVvRF<|&R3j1!>S+uq`f(qeqbkIvAL{=$Z67H+|>}}fE_hgjmi6xj(Sa>gR#ea)_PR)%jE2U-Yx%eto*>ML4yjR{cK5pCnx+~k3kB;be zO4op%`k*{G?7`&Ro2ZyAIz|>vzlkmPha2{TIChFAubjtRMEBS`V`SR3e8ri+bWM9< zYP@Ou&g9_FJBsNJ2hV;;F?gnAiFdy2#hOq=!J(oqXDNVf6`0j&qSh;bAxUe{r&{#D2oY#=MG>btr#*t=h#oXC7AdL95Gv?}o zL43+xm#drCgPO7DXd4HsyUjakGi9!AU$H!FrX`s1F5TD*@BLbpP<5N_m$%u8#{&)tu9K$NtzEYyya6b6WemVy)9Qn$HuC9U=N*8`C0Uq zD5Xbw+6a&3xh7f7|F5<00LQX_|GtroA~G9xSryTs2ifCMnORw(60%D6XpmWwRR|eb zSxG7@BBh~Ji0n<=WM=jMT+i=){{QEBkLP#%-uHOlj-I2Q+^*YwUElBdJYqX6mt&A`F^+{*vO#m}LKQLkGZ-{I_LQw>@&~A+TIKGUG_%g^-)|l&~d(O1N zQv#U5y{s%6a1tLt1SwLe!e0ZH??)uo07H8rOQa;hn2X?y1y)rZMjLxC%=0pNSTOi^ z3MBTL_wN~(mX@+%t`DUnBS}MB8@ye)o`HdN%F4=UQ}++21Q`A{3DP8r(M?oTRK_MI ze84xrtO|*Us6+TE0^p0Vgx}kxU3%EMzDmV2Q3l%>rCD`o_vj0-0@NS*;7nkoYCnoA z>xYg+m|RQscy>?is#uZhtWx48K}92No`(K|!p(Inl3W)P{6f~})6~4op?~mQPN!6B z+sMdRtm+pHYQA-A5hkH(6Y|%b-wk1{DGp!m?pdqskY4tfp5UssJ!F4iEDTqE-tv0G zgf~a&Lb0-Td%1h`q{~7M)dmM!f&+k|GyF47^ped^F}P%qUx!he|BM)|T{|7)`()36 zp7;-+_9@h^y~E;ZD_-w^U@Pw}hpVZD}<=(#D;BJq61I?`TbQ=8&4)xY&&z)Fb zdXJ-bVR_=mcwF~~$EPnmVsxbUFtUwUIYpX1?cG-FQQbI;_JVrWL96V(UPdWfp@=O@ z5`kttWERz^mT@V47r~#hYYVSQi-yxz@=65O7N$u9LxX(tC(XbiNOrYdP)rIBsm*bozStPJCZC%}{8G5%`Gz>QXNf<&n;EDYXdB%MgS2U>HfmkHI%=Ts~+y!mdR?OpFnIy_b-& zO~L0f9a?tMB`m>v@Q_)YDC>4vnzh@wbw4fSv3ww8ZX`i7sfZQ&0fWhQ?A+Oljxm9V z1u}8UdG9C0!kkezZ{50r^;+GsJazxIM)?h#V%gspGP($C^9OC+TzIa!0W13e-(aJ> zrq>QVk#DPG{V#*kWDl8)K5-pg7jg7K(aQLOgvTkr2T4CE3X*>vDPc?7+*z*wxr_Tt zvYm4i$!vMyNuw+^wU@@zl}J7Aoa6M7xqS6QuiyAxvI#gB7<7H#(LI(E8Al4UQh9k= z#RO{_s*|nn9v2OY4A?7nSLU8%Q|1Mso^hTBkKT(H9TrP5(h696Yso2-Dj^toHnQ}{ zecomNYwd5e#Us1PW$OO^6t~39RPvt-l|9$U)cZ_7+i+)KX6Jw}zmyaQbr3aTg5h@- z(yZIX*!i5i^l<&(U)%4NvrF)*+^W$LpZaK0>n%@FwhEVDWkgZnd{s9o&=B8jq_su z(szosI1B~$r@xvIuSiMW-|y$q3VuasWTZs(j)pyqYr(VsD7A2@$#_q%s7EvB~< zd&lN(1*aXJUu`^4^!U;76;jXGcUqZk4!cd}_Ng&&)B4>x?BBVxZ89UPe-a~W3#sgG z0QGrV7E?X*w5&PR;S6O?)y8M+XKs#-@GiJ7?XzpP8hGKgyD|DhPo1l{jJ176J{-X(NYX6|X-_SG$_VXFOkE;Ce`e0w+wW$*}I$Lt-K_cZwJ~ z3}x-e7Af}bdc~K#Cwfgv4^P^5DXtV`8kdde&;IJO9T}@K>1GkNm{_0B_RHh^+_mUL zDgNNnnx6qTgjIk3KC`%b->CG=>KTGzm0ifs`)St_g_^oLO?1PJ+6d=r&A@=69Bgy!Bnr0CTpd`EASD!-IfI>sDSD#U(9|qBt;kx=Gn) zgGNSdj9?bkrSA{iI1|}dZ`+(R+|P04dU}@LRtFmGQ}^S=L=_5~vefjYLY*O`7EWMG7Acb7hm@=S#F|x`88c)s<2hd z+#pR)^57o(vgIv}6LGOoj5vp5y^g-iPf2_`>3?Q=l;U~&`zEeSv|2yaEDLIKxz-aV4={d_Q>p5Ftbz+9Kn=d;Lbv)JN~ZEQ9sAD%>KDn7^d= zX%={3B_4R8aG?-T{t1=x<$W+(mu2i5=BF9|?Y$9S>t>-mPiwCBX%W;qgo;v)cx zEjKJcQmYv((Vo2C=y&`2HV*CQUzO+lv}55J-($!Se=B)_`TQXM+oCtKrtwy11~V=vM2SjL*%*I)D#D)lt9`lej*#QRh}A(SGif@G!mXkU_mDf$ zEZA#$A+Cw-Ts1kzO}Zq!l+{zsNFBR}i_83p=OW+F*=RZ|eEt1hEtS(`g;+099~%Cj zF+bKx+G?-SEr{lRqIzCAdwk%O?eouRi;Rcu)}s&*H#g^6^z`l_M{9GB?~H%rIy+!@ zd@e`tTvdvcQ%&y0ZF>c*w}TeOp7_4)71Pj}`%nD$QNQL8OI384u>N#w{`KOF^n(PE zU$^Z$D-KVtdTl51{+NmSxgcNU#QtN)WfjW2`+Tn!XXdVnei~;!uj>>ph{tpfJxoq% z7hYs05qJ(8xqf2>o$)XLM+%aZ)3-~7g@x8tl0H5@XxN(D0njpPji;|L40%P67Gc7m zYit|>UZfSEBmyf!Sr80rM0HD5L&TP=fK>T}g=sPEukEqpHjKRrsq{ILyyZe)T_^#u znwgtVclnSNMPu;~EYf~U`w4&ujn{O5L?g|a8-Q|BiHnOT$@!r9x(@3|38ofB{;S?~ z4Gk}9Ybh@by{*YNEn}76`cJ?o*Wyn$RX#Kw2?ixl*%ytC^bmV|@Uwpy*I;o*_;sQR ze^jc|OxI$6Sv?ldRV)U^b9ZQ1E|@N^3leS4Pwu2Sthh%f>njcEQV+Xd@x{?$7nefD ztVRlrZ~wwW+fqxctLJK$`g>Za5lVvYhVy8>bS4gEx1XN=Pd~@5ImEM9y1I0D6g|8U z98}6O@0hTOWrOKri*Iw+8{5Dag=d7XD2KO~`@eBHx8%Az>0925*8(IuA46X81->g= z*-IBXJ6c_qrWid9oJq&BN?@BBi%kNrkLGW3_>J`?9Y(sp4TDfRb6i;%GI!EKJabn?##Y`@+Sn#ZxG7^%oY zL3$d=eX^l2TvtGv_5M(cM)^gCM5Csl(#l;cl-pvA4vfmL_*a`hb3Ye8I>TPm@P@_T zK(^SwgHhHyCLHue66w>B{|1L$M>dXivXGc6tv1A|7QP77ePQM75I*a(g+!wA^W)q) zLPcV%+xZ-k%>5w927{vPD^DmHu8yZ_=}gP_L=728N(M&7=k=9ZowmKbeu~8&irAg5`qX$VahjP{QM4Qzues;ouzhqY%9P@hNlCp;mfMzZ%F$VN$fZXCB`OJ|12uQ|gY)F>U$v4(`}y+M^NW-D z{7nxqM{=L4$<*94%Q-FJmi#Poy6dik=grkqwF&k>I%`(T7yaJ&4xH+|jD_kQv8Zcz z`?SkhY5E^CMZ@uYQH#0bu(pwsUwb~v@FkKkMG{|q0N4I z3r>~>_T;fYAWyM*M++QyGDRM9FMo zoT_hXIu@vUI?Hg?@YVZg!QCx;YF8unOFvyc`D(F#@2d0Wasu?!NKRUo^R?&oU2JWu za;JE_D$8?_v4C^`8Sd@o;rw3c*+~^7tM`#jr}qvYe!JVTcN^0c_s(FY_{dA2>9I`Z z{vG1D5Za}ABzPdFdgAf-Fhzew3jV4)>5ozlldFTPiA^S^~euQn(Sous1TpsAk^jxX%j2#(abI4}KV z)A)7uR(;p8bUKajpUP2!gROVLVGs1Eb9wdM@#aN-y5J55g|2ZPPJ?b%8y ze@da2V}{fFL=)&`tU7J5EiR)E)0hcpXwY2tUp@Uaj@+rJ1x6eMGN-F^>Aw9hHPxeI zLF9_W+qa+B)n(u<|LEt>w)7Tx&E-t}3D<>mxv?GoQ``J2260?>b!CNUA%%6}Aqo(I

^B&4bT@%#S(aQ=jR{|2cM($v4+)c*!0uJ_3OXK*I)=7qm&UVjf{N>aSk z<&8Rr$P93-)7&`<_?(Zy#;4l6t;?C?@j^$?#HzcM&!-MT#YKW+(B6IfltCIkdhFPn za_J1KbL6rO9m^B7^Zw;UmEB_JoV`2#8xHyl@SySLFQPrH1xnuN*C@hkUTb%4{-;aS z{`Rk>4j|?qV2uC$YH4L*<>fL6$As?iTH8>e7Jt-9^gba@#APUD$j55{@+$L3Dd4w} z5eL8yc%D+niJ8+sHM1C7Mc;G#(9lrAF5#T|PZRm*bt0!Znk>5oaCiOCq4NW@VEi4w zmYLCti8Mao*J}ekL*yGavnU#iFPPH zYfoR_6{;WM`V6Db)d2yh&3e$% zYH~CM4~WpW!qV~j_VS`4Cg4L27^77j@XH@Zsfs{@h&V`dYIxfsOmcmjbchA#ZY_91 z81AYMUJ#03yMMRubZwB6J0Yg%%9^_U-fiIT(Lhhf0s* z;)*#jIyfUELpToVoXYcFqCXaHj0COIrEbpB=J{A`(=go9@bV=+$r>7XC0f2SP04#8 zgB1fEItW%+iv!Wxb@(xZn3TSES6h;FPT;u*GAYS=&uT=#O$C&Adi0ug;m(9lu_l?z zC3nQYrwjv#pexfZcEm`c+L{{0C*|cE_yS!nTwp=vWROwqK~BcGf3v8x6k?#G$1z9t zT*u>M#j8kE(yU%wQ?j(Q#4`!UUqiv)c$m#i#|Nj$pu2bP-iBXG^V0GHd4r9OO)>Nx z#mI?uVIqJ=x)8{Pbq`ERVww+k4DIwvnn%N;4|;4i5SRNc0kPh++w-(g`uNX&d%Zx zP1ZyBp=x1~%>NF&5LFmhp+#Ti;^9F&3EiLO6PTYo#F`~3zU~2bIyl&Eec<;hUx$h z$$x27sNVKNSC<8`C_WGRn>|KzfgbsimA$%g|iUd#0u zyAthFGcn@XV;3#7Ynv%G&s)#S$x5r&vl7H`3<1J;@UdfuAX<5Rcur8;v8k!4S>u9zFvH{*6VqBpO%0*K)WZiurq1w- ztA)SotHJa2&oYn1(*x>p#duP_Sj~FGQPuP39~xsiBj`^$Zn=S;Ki@CMi0G@}J_kic zMnb)mo8XYn)%@vGkP1ID(1BeNT%_Lb-*=~_r`LlPS&wFJ5OO8JOB_nHQStFYf?7$! zuuI~{q-bG8oIQBB^)T>AYg11->=%gmya?j3s-E60)V_&m2eQhqOkL$a23I}w&#o(H zq0*Er$7V;oH9S4)px~;j59g@IpMjZ~na1#QWa|5UxD&=XQA0!T60Na>h>(KE7CJC+ z3S^(&cu^1R#l0X5Be1h0%5Da2hZVdeYdDHvhXG+zfxraqfz-Z)<2pK1wZB#0Xtp>K zUgFxXMxlTrJpML;tJT7$VI#M!G0==qbjazjy)xf>5g!b90T>%ANXRTOEMwXns)7il zPOJO5MiL!*%zrnx>oSPy>QutDQ)1w z6f%&Yf`S6$CocD(;9v)6$&PlyX2S3^gM#;*qhmcHO+CJ=4wtQivV-{XiTn7(rS}Rn z8IeR_!?uF{#mJu}uoT zc*hEdM(5++4Dt&Ks$oY-c+Z~wh=U79`ocHrxlwt3cXHRB480tDEW@YZ;x30PUR^Je zFXJ|H^QLBIA6V=5g`0BXVq#{^PW8h~lW4VF9{F05g*+ulZwc~-5NtV7i|TX3<``-W zfHbtD%sDT8@q~zkgf58*ZSCFI4xsq1s~?Bbh(ZB?eo31w#wjtQ#j9H}`6(+B2b=zw zi~B^ofg8EYoOU|HFLL{#v^IYX5vEZ1=oHMzwHcKy(LdL0_%S=niru`rVSF3bHgVqy zEUOEQ%YYJNy8;slv$kwf>$-pR4nHXFflS)Jk(+Mpc5!oKC8ldN_Q&1-hVCx0?wIX3 z(nj`S13d8TgyIm&?huX^eRGSs6H9F{w-q3Tpe-GD+X*Y0I8jD}pW*@2b{uErWBGE<%X$IngWNocfGslgOi5x60zc98&BHW3Iz%;-P>>p81bdX z-zu_a{AWjWDHND<0zOqt+A4+!4I4l%P%nuV0iqS;w;Y7&nr1gLrH}WIZL4=6^}#gN zK=V_D*UYfLuUV;mEZEmfN)?Ms1)A{7sz+Q1WD<8OyVb?Pf2>cAJln#ggq)H@nxE_p z#}+0u$~a0FAqt2}PQF2G*2G^hOU0Cmz_Kza=#ALk5L#pmvW_u0FtP>DFu1r_Vs>us zBZxP6DqL8-Boc(3Bcr2ii3>Q6aR6TfKGirOq?Pm>J1Vwa1|10y3*q6_ta4F<8WH1j zp(PLY6g6oD(5JN92ou35g;WZRNd*x@$nqHckgB`)J~GVjMazbDdNW?ZvO1}*bIC%cVQwNYoW4|5^ww)f_jMeH+$kj zfemQXPTZZ8jsQ51vHgP1|DaP>MJR4$p6nUBHxrYSjG$e{k|Q5`EuA=_m(UEb?r(y+ zOfRwIyRChr3t7ldJQt@xJ(Asv77Uo0zq|6d+ZA@8bu%?Pd;DntMt7hFAQW-!DsbG_p)0A|imCYBm&-38+c(H2uozs+FA`9aiyojMH|V%zZVX z=6vw(4>6Li$?y0O=uEkSbwgMjKpR6>wKTR18uUI;I0z#j99~A>Po4St^(%C0n_;(; zJF6~C0>L?6l}#h){;@>s>ArfTH&@fs1>D?{lUi{0XufqIFqwJWeqT6GL$f3kV$_u@$dx&jWfx6e+-5kvQGJ|Je;l59UDV296M{dA@J> zG&VLSS{bLYBh2JJYLsvU2OAvxv~+ZrLqq8Z0O${LZ~Fd+B_+K*J*nqk23(ZgvO`8@ z8>t9W1;D)C<>)i-`)k%KbN}$o=9uM+-6;=e7f+nH)xdQh0iJ)yj)Brhljh}qR7g1W zzIT>$NJvO<%6jf4E>6hzKesv>EC(#nguva}3Ws7_sRIX$=s1qv-b;a(W*Zf9XXuSy zkT;Z-yLaN>;!Ye@k?jThQ-T_x7V8}xoNH|Gp7&0MA`qO`dpOOTGQYI82K0KMKDu*T z%9$IvbPw1lh!?&v*baN`xa)lR$HePV9^ShMW-rcSCG0>K1Q?_04#t5 z^!9$c%{boI%gM=M$B$;-D0I|ZHt~$=d*2JtWRHX;@mb)U{9|c%tfr->Uu1Z=GK%f# z8X6wny?dEp&)bx_C#Un#pv>>ipz!C^67&_6Cd5O7kJR_}(hZ=VsDoVfhoS`piaGxi3iAqX^@)I($Xs6 zDZR;gIh#uuM1k7^6{FbgeYQl~*#(mmz;Ghu`vlzqX?8Hg{nnUmLm;b2s0cvSxq1~H zgkOdd2M?;j7gPd(I+*ta<&v})Tz1?%8vXl674ao-Z!Y20?9hyRPuL(1S|g7-+g&Ax zhF*}v3=Y{e+`??rGBKhhj#UWGA1~ys=z04)wdLZ-KVCyr{eWg5x!r;^sTK~>7NU}a zr-#-_FrZIRcG>ovc17ac%C8i z-V1dCer94TkF?|`rm;wYE=F)V0R0d)WEhPwjijp=C>59;r;3-ag9HW{!$wn6(??F7 zTNlXP>Sku!kw)K-J5QzBnt^e&X0VRIVFiY2;PKqAi*LdUGIvVgt`VF#G$zu}twBVT z#$CP{7k3TYsu#DHFy;b*Bm(Lr%v#!r*PsNEMD@7${J<-{R_C8T261q!z@`nALorl* zoSdA`p(y>pd_+Q!xXa((^%fI2QC&+Y-?A&iH? z;9FasN4!D^RnPd(n=-8ob z*+9}{*+R$18X5KpPAvGy)(Fd*9hQT-uG$^d0oB+Mn^DCYCK%`OKk=Hm&k2)yYb6m- z8VOor{lFzs9gfMEAB48#%uK-SNEGd+O&nNY;5(c7{&+294ekj)3eBjh{gKVjaD}tz zxDZW^ckhm&_}+lEMtJ0jG-IWP;^?Hq9lD291~X4p3N0!%=Tt5=MB11>IvYjgyr4Js z!9du@NvRaoa|nhg(IO_{G4SE98Mi-^rvon{@c20WB6=!Q)6=?U9LfI2zlJxiJ~^kI zDC1E;kuh67~1W{mFJCKvJ zMy7*3lh%wWetjyaR)iops{6IJATI&sNd53K22ub3J37scm=;dGfjwqPZnyK;;_mEz zUDu}M;6Ns8Bn4^U;1P`r(8K6t5t9Swm8v1}SaWg)ial z6R4uYsu`ZE*XwS%MLWH@q=nF5*|p(t>h0@GyKOdm5#GzzsQjB4Yz6uGy`x?JkQl_~ zfy&H>+yZP9aP(?yQ~cILnX=#hb2hrFDk>QVq^-D^nJd{^9+;%h8sE!`hmmZo$8?uH z;x?zezbtB~Ygncn5bU5vP{<+k<%0uQ>{t%{7(@Kp#0&CfxtC3px?lSUr!?L(6 zupRZD9z)mI$;s)o8NXiqE~5frx#V#>bdfcibh26-{`@BEKWX+FZ~jku;0QGM^*;`g l(24v-7V#Hk;(t^L3jvS5t)ylS0&2yt-&M6#3Y1P>`7f3>Pv8Im literal 0 HcmV?d00001 diff --git a/The Effect of Economic News on Gold Prices Analysis/Images/Trend of Price&Vol_K.png b/The Effect of Economic News on Gold Prices Analysis/Images/Trend of Price&Vol_K.png new file mode 100644 index 0000000000000000000000000000000000000000..b00fd26a3ca7883d0c5a9a433fe60817aca8d1c2 GIT binary patch literal 71749 zcmcG0WmJ`I*X;(BP6d<}QKS?>KpG?k0cnsHL=ccJX$1snl~PLS?vxUcE|Kn%?v_65 z_Icj-8)uAj&cE{m1$Nx`zOJ>_HRoJ&@lH`engEv)7llF*$UKx#MxidGpit-v*qHE} z=j+9H;XgimNlkkdtLOGkPi>7+@=xupEv)P}?cO>nFqKCwfgh@K)}Xz3zpFHmSGl#Ij!Rp;2%aVKZexsm3r z4Ga0gR?CME>3#JsR4$URkvoPc3BN*9()_HHgv4?Kvm*F{ulo@q-28X z77rsL!=xVav@#C!Z_s^YyYL|_?3u~Ov4oWo^IHN%_iE+6t9JwslF~CXulo>-VblNp zM*^E-m+;#E{H#UCEQ|BcL-0%gu#bu1|9!3xHsAl(2TP&_Uvbh1IQ9uheOwwUVEB0J zG2x*D7XH=mUT7F%9^(UIN~G(R8^YB_e{a4|Hb5CZhE{fk-9jRh>?S!0$%BLS@lPB^ zn0$PEF3slT55_g-jx$oV?O03a78dMA zUzYVGNfTYae%(JX&}i}JS2o>msvD-<+b-3D$E!uLjw3IA{P;mkL(};pEw0I~Tgb0_ zp_hB~o5M=^M$Iu38(SZ@A1qW4b@V^W$yI_y>+Gcv$FHQP*L8o=t>F=S^$(K-_a-{e zlLxA*syW@K8=mKnt`TD^{o1_e_Q#r<5Nl_l+hn;fqo4Mk=b2lO6vJ#&FrLk~pOiu_ zT)LHx1Rgrd%Js!Bddn9R1Fs6X*l%tnC*Kg7p^4~>xqr{}=e6za?egt5R=&MH6=pWJ z-*HY8Pk*<(A9GpB5j^`d>(ZQEKWEDUR~pEE(%?_RfGjqq_v>zv^H?g&^4CNnCt;6; z4}bfMjLI92e{&e~JU^9-7yL9dq^Zk^taqm`X$piyv2(*)g4sTm#}^IYUVk(<@BIGw zc)LfM&Suy+O6{0Bs@=Eqd4mOyAE((+fmTisjX)%y-F&{&hMuyra^@;KJG)8ihnumk z>lHT`8JEL3xfFP(FTj`2RP*uvn$bw{i&*P=9J%PbUz-*pqN0onH1A%mH~0EBxMI9I zR6t5fn(w%#r66*;J5>{7`R!dhdu{Bkc;`1NkA)&&iMgItxCzs}7DWX%DzBZzSk-*u zHXqm=v+L$CY6_Z~?M;=R^}V8J&=f>5<~aJYYO@~iYXCm=pST`X*+-8YSc{R+m%mwc z=5zx-s?T@6g;Cz?MjjEkLTg`M?)Cc>cR=t%@R@WIA-a$}}mD{Wi7cKZ7IXwRM>(oAhY!ygw-?CWg)v6C8Nwn}1bR6-#qwW}7#W@Ix&v zN+l&Fd}`h>k@J%xg@inu%Z$X>7c}z?>Yg48pYE!}Dwu5U%Ia)epO6Av3 z7onji^Ww#e2%~Y!`}fD~FXQ0gK(blaUAz+Z{=HIKHl5ohn&-(Dmea&5lZZE@UOlG2 z;U)AuJUl}&EVpi9eQf=4dNAoZRKa640SPa7ezH^7jEjd?vDHK+^Z0QyEJ2C62Ce&U z4+{g4)B4yuc+S?3%Yvu7y>%Ng!BqFvWB3>tya)9?RqRGowo#3O???ETZe9Lr+b5L2jfn4 zBu|Khc8SjqJkOhNM(NbUqpj`jvlR>RN&2-OC)@4pB?>Et(|&ZCWtKEhRv2#I4u*K! z{`H8R1Gb;Xa?Dw?bS1Agp6BI=^+xqUq1}Q)yvNat=N-{?t{c@?1n1*j*Qe{S=zc@^ zBPp=3kl^{eC5+x#FrLAq=4fw48sZY_*TQ^^Rc@ix*~ua7HiuaslPJ}@efS-x%PU=(F%Jc+Y{R#=KX399-uKu1sOnk=(ue)R_*?J6hw7D1oqmG%Bt$U zd0uto)@<|6pV`oR@Fx4K!{Tys_+Q90j&_&46PY@qIlO&*E=1neZVG2sVPavKX`-^S zu&#Mh^!#aoX8GQLwoT=@CL4Lp(K0Kno7Bccb;ZGiE5}v*j!*aeV7LA9YR^7U{gv2NMmZT((<{S1?A> z+ix*J<40#*G`+-9iUbwiQ=-EUs#oT1<~S zP0nSc#V10tq2N)}-f?wULPB@`(}t_}EvYXv%3Wh-em6Fz^A?{%3@Q#R`>le4g4MB# zkBxy>23H(#p&~vNCqoX}bSUKMUf&EGak<&qACDKAgnl!qL+2J2)(Z{_QoYB?sj8;d zFY}Qx!^>qM&WYAB1o@tZ-yYlJq+dfHe%nBBpW4yl8nL39ni}L&24%3+-d8``%))cX zUJZH1-lw5-nZ?Ds`OO1)`g!QfRj+mkUERI0hzRwx)ztP<}zUOSZgOhKpqOf{A-xmqQeZFXo55YBbYkQ&M8 znRNz=wa4p~Q?u<+>>6keU9o(1&9DcFrRIYQ<7HO*5#~@%6dZV|`#sLGK1M~Qp)bR( zyJ}8!#R+KeJ%-O->9CSYNW)*;Hu$BuSaq#0B|J?{w0b!+D^q79G4PJ^ zEEEAc4Ud|<%Jpw7&B1gcXZbq)d`rn6Rs9;2Ryg3WPR30KI8gu}>!^)2FWu|tc%xQ> zFIOW^Zy8Rm%O}oIs4_dBtCU#`E6%9km5d-WXBR&1=-Cg^pU@B=iNFPPA(Q|W` zwAsLcEHG0c{AUV-RFcmk8QWClwWxN%9b#;2$i;lC$(pI#e0-lQ$G;Vr^=E43kx)=j zjP1Kr|6W+=g^F%yWOR7AkU%7Gww#qms7E!mTGZXNaZqGFcn77Pt@*lncKT=~FV9xT zUFw3`zT9UKPmj$4BH=$?0F|ctssRh)Pv!ThmW|oseUaZYXY1+dQKQT{SnTlz)Z?nR zws&^C2kk3#@F}_cOUwsp2Ncgo%=2=#w}wp;oHa6Dv z7;$He>A&g(2x`RnDKn`481TeUxs6dojSAkCJHO#`rOLz4G~}XOv0pzr)63V&(Rno&p+=iUEmLB@q+F$EC8Qq* zIF-cX*-<>;d-4r{Ltk7E)}!SZKYaMG*pt-!R6b3f@iLri(t?BgYol<^XV|!qd>_cs zR#Jv3*bkJ&VD0f5JJ-RwvZNhp0e%4xs&bIJi9Q#^uf8TH}g$9KWO1oNi& zaB($Ui!bu`A3c67vdY1`S<%woo|K;-2E{M}zDh>y7Ut)9c=gj1;xgT;99GmtS=IZ0 zz=j;U^zA#8jIPynJ4M~m&7>Yok`CoJ4tn?Q>12(239X$eNjellWM`n_B)}noHqs~b zu~pUhVm<8M_NY~DzosewuASTB0xT)kLgwwA91fXGH-i5QSDU>d>-z>+D97^VOorg-uc^-HW>UqL2w35N7o>kJLE{%5q zohhKc(6~L5Mv{bvMt5Zg&L5Zgj!zB2_a`30P1^8M!xPGFW(ld}G5UCwXQ%G>1wXC# z!5MqC5O)HnU~)g#CjRTEiXZgIthY5jg-IG2zm(AFS zX{zccdib4xbk+^JpKLWF#Us+9qd`BR6r;i6km4Gn-Y`H_8R0aRv%+FkBv{R43~ zix7$7{HGYV;_NSN)Se4_V-n!*KSp2M0~}B>22im-z6_#9O;~t$N9|)9b?xcCc5p&- zTL+*D%;ke>waJ9)Z}V@D&h^sQ#{v@bO?$4_9Ip!izqlO9uHOZ?r_u9lhYo&M$#7;# z0@b2E_%FTicUk3O1sQ5 z#iTpFuG!Ak7HAv(e7eFM(-(1lBcqU9^fy_3ho>HxM6_e+3%T-hri_*26Q+YXCvFhd z)oqLEaH0$@9RgaJf@9TqqUsfbcKz1a0d^#X3eQ9vg=BCZz3fX@(y{C0u48tC1NbTI zty=tO%A+f?va*z?c7hf|cY)hkRqv?>cXlmw#`rZFP6KMV0ISx2Rm7E>td8=?b=tuF zX!q;m1YyD5pW;ZeAUx+H9{F83x-jE35WvX2#C#K~YhOb&hmoRM1jOQbzIz0Nrc@|x zFaTsg9U>O0fti_5D+gT&l6stnc96}ZlqR5QovQQZi0KqO7_(FBa$UqVmHt)Z?%D;^ zc*1o`9(dIz z;KEJ7w$!B}?Cg0;c^Vl`8x!_RzkCs121P}xVja*1%6Wg-Buh|lFmGk3z-XyI>q@BL zHnzywAEO9&;7~7mQh2HkMTCWY&ncT|14>B2VR!-Xv@qN}UVG&2EY7*iJB)JC-vOC) zPE@-d0%q1Vo_u#Jz9m`aqcglW(EDU4L2l=#2UUmjF+r5v0k1Kz2An61LWLrQ-H+}< zS)O7lhIpZN*h=I<7CK8kXJ)te@j}A+$*pRaJwwQ@6TtD=ngwr8j}Pu2aT8!-i|9^&BnVam$5|kA*V^`5yBx-MCY^%BknJB^j%5%OutYlT{-Z zLAwqvHI0T(fi)t?a25E46x{Lsa>unFZ+<5d^1pI5)%OGooNut0TYF(1q|hGq4OtK{(5cR5%m_+EQ{ zY6VEdZ`k5FC?o`D)u>J2DBEy5wmp(pdSGh<0s{|0p9vhdBqI0qg@bZl;;+~wA=C-9 z;j#knYlJKU%p?H%3h-LXxbG(jE;3L|UoB^(y-CXa)!R$K`3(Dtj`f3_1<(0UCU+@= ztKf#iqoVBKr$WQV00Z%@q^&7$qDv$sb&%iGY%Rclu9Sr6Wp+V|Q~*Z;?xL2uuI92< zGPpQaanEj{%NWFy8@F!VgB>>0U={2GP}cwqqJbe)P|U)DO(j+C>D2evh`h4b=6nMV zZzM7)mFP6F~{xW-)oVkf5n=Ns}sec;~%3eNPRsJOUJsE!YSoGtk=k+or&(k-B0}CRZKk!paMkzCdC2bXOYe;c1*Z=l3^R>0t zS_fHI{_`1ph`)vXKh@!Q<=~c$gV{Zoy^x;ePo2+$q>?5${<{WBc)EegMNp5oW*U*C z21x`V))1IVAU2T*rdCzOYFk$L!lq3*R#NcWGqKnFF^nMGt906U4l-f3R!P9(qA8>N z=O0i*IX)3qRe`Ey2b5(8_WnbBd>5S2oxfW@Qq4J}XUaM{^7#7t2HOhvSOdR>AWvcn zm{9tkyCHzPF(1f&3bFzs_Wp4bMmQy~;(DkQ1;ZAoG5cP5H%JUNopNGGdcc1m!g5V| z9N+#DtUxL3#@pK3nypR_rb$%R)1!swBC4Fn z>Cv=3zs$pj2Ea{0V_}Q~CSU5=RhmRiN39la<4;LEa!8JkWy+30j z&L!dDAzV>WVZSkcmGwbn0zz)b$fm^(9bcZK*FeB+2eHHoSNcjrnbXh z8!a!+^zUO9C6Zvsr;wvdvQPY{j+Fyal-wn%gF z=jVI@>X4}%VA3wqm;Q4PKBgS?iA>x^P56;_blWo3vNAhTT}zUZQ2-I%^)BI0fXX)XWpGH@es$1%Ule!tVU) zS!7;FIzX1j1L2Cx%Ka7qI%@#J$UrhxEgSTRo@or*Vc#^ScJ2trl<5}jSY)hR1^&|< z%V%d@Iqn8fQZ7N5rf9eWRJ<(eg)L{miJ)$AJwdqFKg(K7`z<6KKw*?Me;oeRyIw$< zFIs^Pr?(l6a5eyDcb|7$MWjnxTh72M?1bz0DTATwLz>is@UTyJpQ3}R_xm*#EjDd0 zsDen!)SPTTQV`sdINM1$-vm<60q7;HW`dH8{cT5q8lEz$Ms5wtS-(gg35erBXqSF| z#Q=@NXmhI04G0+0P*F;f+WIL@^!~#KF=zmIHKc8jk(1lPX$zHJLPFv~GmR7Vqo_Ls z>*s(;c%k?74tfMaLUGWfL5phdf0ifx-^lIs&SgkZRTG-wAR!?^ni;jkPH}VuMwi41(iTeYsa7}F*2Z1VA9H!DEeMz+^a53O|NZ{OJXD5p3 zY=Xde+h~}v&xfD@KNWh=J(h>vHhgkZCWQMxs(ytT= zX=ym6a4w(+(TT)El!h+#rrE)E4Qhs=4*?4XJ)-VS-&c>*Jq@HwG69h|Wt5qD3Ht)z zG%O*|vv&tC=T_y)Il6OVb5G@NU2QZ-X=sU1j{c{1T-RCbJJ#?Y5DQS2fAH>?6kEUK zl2!}vc}sJOJEqd8j)$92{M?hSQeNiyERQPSA%z3yY`uw3-- z+nNUBk6@>pF^}AyR?64My!zFi>{*ZxP4$;4GVE~QyII7YQ2;El(IB7$>a|xq_$T5rI!hVaEy!l_BD!=mCD)d5oL^NenDlItBZO0xcnN~eEh z9lZ^2lpd1}jqEXeJH3mNwHuIm0E!rL*VPf{gs$uus{YlKBPT1O8~Vq_BkuBnN)$%d z)}Dk*-)?Y5$Wi^$$Y!MhfOjMAX>sd{8{#eYn;iT|d$TZNW>x+soB9EMD{cVgeUU;xhQ74hbcFQ;Y1_b~5zne(kupbI?q zsjsm1p-mGj##9c!bX`K{6Duk|g@90){Jk|xjIYq7pZx_n_uVUo2j4!2twO*a#ba{Kqp(#pggR{3fnbk&gFo%!l4 z^ibuF}(6Ik7D4o4MoI`W#b8Pn8f1u@?Z4>bx0WT%0{%1=Q z_Jf>FW?B0V!)R+0m@BPcA|Fh*Zys=j*`S5zzOPX!Vb;U{WKa5q9DhGt~i#%wGOr2W6Y0f4sg(c5#Rz{)|_u5=24L_5( z8ILRaU0Y6K%tkrvZ}m1^YV&-P&04(1b6+&ZTs+}{QZd=-FX6WeG1vCB6t90jz4uI) za8yA2Y<7wr-@VjY^=NOJAvsgAu1s1$feVkZ8l%`zPlK^in8HV^y$vs*Ze%fu2Up1TSc z257@hE)~b6$S<%u>#=_SJx+MM?l;8zb6zUn{+GZD({z?Uh2N{u+U|QDYcT0*mn|F> zedhdRDgj+-6Az~cITx8x+*3^(cTD?MLauVWftKrhSDg0T)`t(5$nWU1K=1VrQkeIL zjKK7PAl&nlw0ZqL0jG5dB~l)XA!4`e{Cr|bCCzFVZWQV*}e!tYY%JvGC7x$*W+<+VeCd|IqbJluHS+DbF`k8J}hafLP+!q(?#T~5~y zc!u2XSUh^OmJ!CG6Jz+~MEFn9ileYmWojoYrTo>?-zC(UnTbd3%Z}N#Rb9>fDT-gO zGANPG`8R)(V+2OnGFD-SNO?4FUG=_rTgRuntHU3W1~dXV5Jk*kWx!_KVUUE5t{YhE zN_Yh$boS{GRR#W{ceZY2 zBnWI_VPT>mWKe~tWMpIpu-e^3^>9Oyl1BWZv$J=tx>?CQaYz!98|8c5FzfPWrH!R4 zme-I`F21m3$hwzd{+FZn&5C`)5QVHI(!cd7u|gRmj9Vt=n~4S9iv+KpuTGiE6xqbC zH+dPwm!k5|Wvp-e%@7r9OVIgOUNn^Q)lgb{c%oo^?r5<4(bZc$OgW1x`zh)Xkv}g^ z_N~`@&Mlvnm0~k<^TN?nxd4>m=zE#UbuJ2&9V(t0TX>!iNeP)WMO_(OD!&tT^3E_I zv$p_oo`i~=@ghteTwz{34px95s*aYk5ZUqkxb_?a>1J7smA?l?x~fhx1B=cr4EW;Z zpQ$9!to;Z?v=`2LR8t5|J21F%ppif*1Wz^_5GnL8w}OXj4(F-#pmCPZF8eB=bo%zN zuVFrMgqwO!GfM!PbQ$Z=LAyAq9t?L__DKq}2p-lXVk;bz@2~ z0}JK2K^!h=LZWJQWmIjRLZ-MAn49bAXU^hWnveS|>#p||81Vi+eYw3eV#-09NuJ6w zA#hWOK(_Oqs)Y0VCD)uGVB8HLPt^fcM*9w3wm$%`KXDr4dIEmUw^m*1xYzv*;Mbp1 z0`1nRDLplig+PC}2*f#bZhju~UPNT1EwrRB(a_LTLB}H$*6co$G?S{rc%U3VhWD`J zkJ&ZdJ5n4{Q_N!$uO>p}Y4ZA^H~2<=)lNS2>MxfOlwu zgp=LJ{Xnes1I9&W75*V9(UbA8LTr93UrU9>O@bS>sDg8!mR>^khiE^7-u6iv@Fy=6 zGRwOPKDY0!QSV8AmaKYNG3dR0#qVx@nw2|4nrTXkFBb0n7)jNL%hja=u@vbKFCdOE zhz)32%%w}wQQ&L2tEdsFW>!xuN3nCqbYg9@$VP;+(&1ewju!@j6osfj$*Jn6DZsK< z;_mgaq^%GCS}rZl?wPrkI_pdN(lfOF_Kv@tU=H(a3BPg0d4tNID*+tn(or^kYh}E} ziQ$!|+UZGu(TabnYAJ1D-mlVGOTVGkZ%r@ms&L*AL~S{}*}2W+d`VE-;Cyz3OXT?G zNMDWrgjzz{QAxzo$rG)~l=Pw%k<69^eU780L5!q?F;BGq>hpWAOQLv|nP+}r95nq& zdex5w>#~SPb*AOBp3KyLfmAYMhm^nZs?x$NzJs8NJ5o_jR`kyeK}G6-orW&VS0-E_ zG{1qE=h&_SxPAnZHU}lq`Gdy~AEK^-I|Uj66klX}calJDW6xG+1v!rJIK#znJ7Ocr zZL%9Rq`aaYj-E69s%QUzX?TaPrcg)j{X2QGf_~;PK`fMO8pqX~0>8C9HrZFWWj>sd zf1$Oh?1XL@hwRD|Qg`|r9RmVNvm6o+V$6%*OXhYLzfoOcVRF%^l-%zPQ0Za#@>{&+ zFsd|B|E3D%4I!1&#p~Q(f-P{#<5>a}Ybd1*DGaj|ssnj(*n~A``*4c;!q zC9@74OU#A9ckiY_nVthf%5|_R3_LLbG42o=sGzyXedfxj8#HCf?NIXyDCx9`PFk)x z@-C5QzkW#}MQ}qpc68$A*&k1C-4^v9+J#gaO;M;H`_VdU90P5Msy#faY7y~ze~WEr zTs1VjYzi4%Cbf*mN|z{E@oVfU88PbMp!sefwHGnNIvzM2skLVFP9cpBzVp{~Qh z_+X@2>)u-Aof*=cKarc*q=G~j*){aT(BA~t7d2_rY8RNfXJ_A{RrTSgchg`a?F>nz z9lP+bj|t3uU_L>-V_GAx)hgQB+lPU;gT!|IdZMMu7U7(O@eI)E@=4Q|3|1j485}it z2uL<74_$j&)6Y16bsziqm(MQmx%F>6ZI(8fX76S=>{#$$x|{g!Ln$Ge6^?+gpto09 zbU2z_K}w$>nf+jz_!cklDg(mOaI~*@%zx`3rN;Wp{BxX~{9hgf67jiC*WJU}yn}W^ z-D2wqNzT*xk6M3WknX&XXATjQ=YBgNB_-<%L`^L~;kMk9E*Di#iqw{8*)KzK4tB_r zE=mu!51ls`ky^e|2~Z|b-95ODK4I9g-z8C!BIC1~B;nI{ zIc&16xc_jW&JYuUXF-@%#CABv)fyWTM}hp>+Qy-u&opzrm~{md{D~23dT@vC=B=7S z3sM!*_cHEO_PImrm(iFe4(UBYi#TRV_#={%sdby5-j$@;`r|DvE7LB7z+?aCKQ?@V zNQj4sNYc!D_qAqZUH4M1(l32#BO)Bn7{4h5JW0a8^>I3JaJDUg%UH&WHVxlwcT>W>z~-QNf#b+#c}3& z&0J!bQq6Gwps?Scf*>QXxVy7X?#0L~hjhHsH3^llL{$dRpIoGgv3hn^rrY`glzRxG zziG%Qg-@9>FGQ9psvQbvh1Pf4q5Ku-v=$mKkS0m8%AwIN45S7y{u5p*UGh^$=;2Hc zk1xnMtS0q+hT4BefZm-fxnpp>ay9Ht_|J&!nn6+Wz>D5>-=VP#?St=z1=J2k<~`P# znKN6?AmcR{+%+iB6mxO6dO^PaMg+|_T}rFscIqtC{^>UM#0TB*=Q$B%)5|Ry@sGDc zh|qHCUb$;h>u!<0>{XvKAI!t~_0Op$rLuXQR5Y8_*C;J^)C&!Rq$rUbzKN#9y`GV zMv3&M0!pg`DK`y*1z!7?Ro1SV0f9_mQ_Gqd0$Fc=kP=Up1NnICjSlK2VOAp;1* z#a5HF3Eh5^8-oH0SteYR9G~RA1!>wDbGh|bFY|tr|6;vE6~3+uZ175CG-0sIS)|mS zE7RB!52`?jaq!r+Zf23tw6hD^z|hu40u%~dtC;b+)EcYczrMoem zAk|kVVaHvly3=MmfM)QBrZ0V=bVz`tKUXB>iMh35LMai?M_)5pd}Ah1*Fbk+YC1X~yVq=w-UxIysFtm)fB~^` ziuu1)6bj?OtQxHwBT`ua3W508GAUXq!fQbtBngjsueijm^UWw>QVZGJQ>lEzA5 z%iWza(z#=gy6W@$q}~@@2e+gh2)%m(__SiKFEM|pQT}_!PsP>fUHQXv(8TQJIF>Kgob87ma*G|Hb)-6ZR^Ax-uF zlO+7uSfAPH>%X1UdZ{{0H7=MoEao~afT;M%U8qcu9 zY8?9m4lSE27RhdtkL4ZX=G#_A9<|1IBk?JI;aIlyudPGOfAhbpme=CZ0U?=~&y~M- zs6(c5kf@CL(F3DmVXzmHqE_-=O!zOs~_?!cMBPi*HHb{oRrlm8#2+dw3M(BvN** zwpS#7&`3*+PJB7Cw$%Rld(iw&fRo$9@3TLs$7!|O_y~j(_)?2X(G!~A)w=03+#q#G zJ*q3A44CL&SF4@)s~3Ka0u@W|LXED$I&KD?m-2akgfH>53^b#;6zBS?TYh*N6c35p zb|Pie8t5SR6hSL@!>3G4rgT&5^+jQdMgxmYK7v&2j?#TExoNzNna2EThE)n|*JksB zQ3111q??}TprqDvb}KvwL!2%7_C=%Ei3}g&;D`TSL`WMOEDZq)B1A?K+9$>p;j2$* z3s>G|{mRbUB7fOz5YRMXY>^Z&K=qqy#i>DS{C=`3fDkE6O1h1f6qXIcT z8&R%Rk-HiznQ0?$E(#ryTCe3JCpE!HyCk`}%Mi?3fr&&0leHyl$qV1fzlosm=*6Uw zyZ18RFjG9$q#oyxE+bkhq0w#jHcVzaa2>no>AO2J{bP1a;l+TNXkCxHa#H;0%wnc) z(!FCvbachJ|{z4kl;Wp2=Y%gu-Ms$c?rY^-uWA{8m&Pt3$4u`xC%q*W4 zi|J9Mr87OsQ1#Fa9#I8>jQ95)3B9zT&bpjsHwh^q$8YCHr@Yc%@miRrU&H<+BYP~5 ztTXk^{*A9(<^*5JBzC9LO`Y|sX2n5!)a6`k-LO&KJ-|W^^TM8Ps{$uXQuKB7ll2oR zky>7VMBm<7?fV>$l#0YToc|~#@nPGvOpMhkIP{;xAT@bqjbDinZ;~4Y`QN&JCZWqI z!5AOX*n`opFV!;{Xy5uJE%7BDaCl9_PXE0uI;EDc)O4*;? zAHP_MB|3aA_WrLb{528tn)#*h^9xPRaDW97{=HcA-;32{xH5YylDd0@lSFN%8s@i`%Qq7@wlN zqyv1B3LcpMKTQ1FV%$S)5_CxC8743Z$jr;4EHb`oJLK{I)l5U`vrc9*rt^TueMd_M3$B?p}sFmsN_e z1k*QW0X4Pg$cLF!(wb{jpppIkR`0=Qy~EI{Q36f+z008TFJ*mcC-kStp)peMbF>m| z)~|CEp7O50GPQ9h--`T#j!O+XQu6yWhMmIPBT8wUsDAKxBq-8ry@}Fuc?T{gw94_2 zaZ99U3(^}~xhF^}OaaPsj^H;^=W7O|I0g6`fGEMJmMu)kP466vohoM{t`F(Dhzxnq z1BCIsnPnHara)0e4Nj;zKXP1&OX4>Q)y)`uCy)-}1~qs?L+ z*wE!D1>owi4Q)G&Jr_E|ea63$m6Hp|HI*9LH47;nn zAtC0I1D+JxSHDR-j+SnDoNP&h=ZpGI)uz}PSlOmH&QBIZTHD%iC!pb6FeO|&*}Xa4 zu;na>xH4b_?<33!+5)Xv+_HTG+4e)p+86+DqC@;QjaI`AIY4<{veN@)dm+8QS)^qe zi|Im`ISXX+j0?<9@lV#>+~x|=^*=&NfTmw+Bs-p9LWQC^!(zt!K1Oje9AIb^Np*xv@dpXx?i!3o<|*z@$iB!;?+DAOY6ZqNjiLVRM2U;X?;Lgp(sYVc?; z!?+X}2R5IVjd~x~{F%W6vp@@Q@J^XqaX-L4i41eGS8bxxhDwJH?wVmrj?&RUQ=AS!|xaZ~1 zq$_0fI=+9G@dfJ|MdF^qO^KrEgX1Up255Jp0zq!Wr1J!8ndxZhZKUrF7P4g6;&LnS zicrIZ0rK(asKELoDJiKYrS1D!ri>K>UI_D0?-APo_~kW*(=u6-q=M@$cn}-l)3VW5 z(EOtibiPY<-|`2TJ*|7??{6)oB@|jui@}iPz2_YUyNf+;$7^NZU(=iYpG-TsPR{`@ z4z9fX6L_UleJh^KDzB$EBF48L0 z&05h`1Akhymm3!!9Y_)0L4wDny%H-{|IMYWoMLGK?2qRvcqA+l7{=g9WM*N(6}AL# zhgR0cr(@vSy;qhE zkJz}l@x{EnTv9cH&rah)Z`n)hzIt25Mo0pLx5>vC zgJqSf?OChoF5g@&P)HrJSALiqvv?R?I*~VI#UEp_5*?rtfFZ}<2fqF1qU(gD66PY?Ue+~Gfc6YbW1xWqTeDc zCpTZ67CCX*t~~xwV9)pdwOkipH4Vv2?Sb_885+8{tcSlHw#U}`x8Z+RBA%J2~rA78~&_Efa`QYN)0I-mLM81t&Oabai` zG1$PC7Zw(xUiyD(G=x#j(l$Ggm)NtxwVrwQ^%Je*SNqUSG6XO8nI9CZ=|FsG?#9q z5f|2a%zSug^(>P}$I7b!f995$iknAgv-eAqa1V@%vImDwQ&n`bdVQ(8jd}zDZn}t} zS4yqws_ogunjmjlE-wxg#})ByAuauf^jgdxWmubG{8aVDLp_)z{?caf+56>CJ{n>m zLK{KF_|dxfgA#b@a!F$%;s-)pUJN;6H!VEzfd9eBc?YBdnBW*#SOV0t)H%TKkN-9` zRLE{#4jIiY1!DzcZ7R0sP3SiRJt-$kWFrkOFEV?1IbLypPnztLp7!aUNg<3*JFbtlBDQKUPCbEMT$H{CAB;7dz@*p- z>@YI-2mO`kcb9Md%F`D?X0uVqWMH0Nb@@yH>z}@v}^QDtbwI&sC*s8-#1T^b&E<@8GnVkwB)KzdZ2%gG|W6#{-Y?9WdgMv8vyF z)h(?2J? zU{Wdq4DIic86&NpHVd92+d0{$pq|e}Rufg9#w(q$q9pML>CF-kZ8pv^JfGYNXq9@V zOjkYI*Vf~HeQw3`tLbRv4;lf2#-CMbjIRQmrrUl>Wi&b_WIw_TOcJR1RSn?rot&V2 z6#nfHc05_({!$thG1r%k_%BmmyQ8n36Rmopx1D2E9(%vMa6=ez{Icx}1!CvawpP}CbmGT}kcK~L`8JH(X z{%Z|PA|t4G@c(S;p%bBUFcKGBcXeV?pl8kRX^?-jMx?wmjU~W_1}6bh^G^6!&N0lRX$5T!2NFVh@O8<2NkP5F~HZ^ zqlDoB-(C3LV^o;SN~^9gxf3-vbI_9h36nKD`m$9m*9orj7kOrjT5@F(^hb|37sS_t z^OJ6oR^yq8!kGjV%~=_taNOj{s1NaxZ^DVu5z679{3JZU67#QrLm0;^ktT42$J6l)`iS3p=WbQ8(#cTd^|{KGel!-l2Do z;4yxTt1Ra4jp$trOr1xR=z7o|;TRQIp-Iytm8|PI#f9~r6niP95(4^zQe+V=DMN^* z#v%kkF6G~Xh3g>{=UbzDu}bMfWEQbkicN2?rS<6 zaK*gZZXdr-N@<-U-Cd{Z&%-nEDLY8A$P;Jr1JVg%=yl|*5 z?Q_9&U?TZB zk68^<3-z(EDe1nHo6{qexTYQ|2P_mFJcj%)8j|C*=a*trE#2l0NjFZ2y@qHtmVwid zOW#KcO8!z=PFD;05I~EQD&bzl6`q2Ze8-D$QoIkPIG%rQGc+Md#di}~iweYI6u3;q zr-8^pK_R3$y=MVR${|^w&ujO@{26b7P->=Bvta_N2|hU%$dAi33+avOa-Md^9=>JI zLc3msWSfq<^?6~LkKsrZ3rTM9K8TQH)_%*=|vSV@vGFRp&W#B$#~2q{Rbmy z2111B7e`u{Ulp-Pw5x%ANOFM%s`KlrbBw_##WR6Fw#IV`J=+oI__^#Th9BdZPL%W# z_Y8gsco9#t@j9>@qXNDjo|Qwb^p_P5{IzNYO0!?-t;r0hWXcQ=B46#|ddXD|4d4E7 znWV-L4o)1;Cxr2dYZ9eGPc|NQK5A{A>K;^|EgFiFTM06`!FTrV3~D2f~rua*B_|uHFpA?gy&1`>w4C7n>Z3 z9ZGl4N%o@jw>A<^mBC+hKae=_iD}J7p)dC94;^HpJ8|Ef?n)oL(^4`!cKt!)$$+Wi zGx0uCt?KyR$=s`}442=@(4{)XHozxhW^J#V9b=KqII@MtKtgto>EI=1DSts6++}ME z-N`;&`ub2rwJO@j6r5_uJQw~>RKvD5FI;a&X5K#oYWlok3@xauqPhhiw?JdU%9aum2E z-tn45-H$vk(=8UejsCn;oyS7NzRkv%sH#sA#7~E!bDV3a(x=2Wi4!m2&V7)4c<^8G z)NkHGRv35_? z?N8}D_@g?=ADB|Y&}i(dUW9Shybnn`H&@Tsn4yL##@EuXrY0bHy2OR6B2m@#BGUvB zz81zZ?LIu0An;N-9+@$HK+t8Lc(sI?{gYA8L@e#m^T)nFZp{(I6LAzh}O>&U+l*ja7~rz83SSp_^LQH4kas z-R#u7?tfZLy&`O>V6S6Jw%Vs%_}i!~n$(A%72QhHKwf*pew;A+_Aw@Azs8sJBQ0*E z&{$W0@$UUW|0?mtmUiCZYh0cSpNC^Fx@U>{a?&&wU^=GHkKvs_`LZX&4aNE~_TO~0 zrI&dWw0Nm!hp$Rg_A-Vab^dWyck+iMX~y9*5bW6h7J}Cu+s7Co#D*2a?d@{cpl@bE z`XWi}p*3M{VqdQnXHIEg+`*Vn{lQpcV7|rKd(S*-$QmvU$GAMLVwU*X{Lfyv)&=C zngXpbo_qk*B1DaiM0oFCcCT7VRVL74_7nPjo(w7F;1#k|f3W=w529Kay8iyTjX|qx z-@8KJ&wj?^QT4bq5sevSO=wh2^>@H>#U&%ehNCX-8x# zYZcD&5ec)m_OI&RiPvGj!=9$B^~2jM%`j;3t(~&{7-1Rs9d~R|$nWBV6!KGVBu7t{ z=V`ItK68p2Nf^^eqKes39~35A4H({~T;1%Sn;9*9c#X0hY%pEs3kSa$EV zX-8tmI9iyC^YM}|-M@HvS3rEyj08+1g9 zgS=+ir^&PyY@{l7PtvEppv54lDdjS)sx>{jp+>+O6^KN5Vfjy}rS-3b_bKcCxd*oo zZEGW8 z1Kl61mrkw=ie>!1@Hy!%-#CA8ul^~{j5m&;%(54SN7B?YSrx5In?jiSMP{z)40|TZ z5M_NE_N;iNVx%)v5h=nksk55b_y_x2%L#FCdWjegZ2a$1Mx&x-!;i+8!H5jX36 zK9^2YKmp5)`}Ift;#u-bGv}N*!x#(Pk~XZR=(H11)?B{if2@~NmBNOKH%Ld^(yLOp z+0fCwB2kaoJmtQL$vpiav8~SjQO&nq`CYk=(OSh_RbGeb*=w2~%B;XrH1T z)K}h&YKQCgw26{dyU2Yn)L7BHj}r%i*a*ltq@>N!n0G0f*$AFQG#5|u|9Y}6X$qb?Vq1J~}yC|T|sEL^6S zE@T6dVkQ1n=MRE?76-+y()af zt8izuBd9j$?}?v=oSQS9$3!Ry)DqdKUDTbC7}HEV4iM41y=JLPsx z-}Jb`sa~vz=9z01*(7)0`52>PZyJr^N*vhf>Yr$vCXIUIk9uHAGftU-m$y0EN68sAuvSB6L%y=)lX3)m-V|JI)e@K#bTSCGux zSc*sEHP>31DwW)OQO;zxWEwf-o+S}U@jF!*b zEwTdh3s^%xVKM~UU_oSmj$$KTE9rz3vM@t>aoAz2d1^nLR!@i=?kK!8D}6G+gkqZH z?=Y_rJ=jSKoU7+n2*;9tNi765X|C(a zR;UL2^O*rRP0d_6sG_HNu~$NG|5?435#RTEY9dgHKktoj6QI#M#=3s0?(-fBup|&9 zV8vPcMJ&7B4_9uX@`{{tlXsW_9<;w-Kzd)rJxYOG1gTb!Q8-y><^;w2D9CGSPkh!Q1_@af7=U+UGh1fIIyiw zn+CTducoSo_1oNW)pv0^zsd_W0u)^p9{{o)28*x}xNc9_M#w{GfJg(kwVO zFrnfp>TO5BsyA}eGNeErpeOb0!s#DLl02I%Dve=@sK+!xgo@Q)5fRrFJL<^Kut{Ff zWuYX@r=oQ8&Q8Deos1^;0j{(zZAz)__%-Ds$I%d(KX1ldPp@)$%S}tl3cJa($gHW2 zxqf7yVJLM-o4@RtBkH2Um%!#>PsJ4!_^@KNMnWdGIz~3^6MK^u`i;J}kc$9ME=zd1 z%U*N2TP;nyIS5hQCJrtz?o42r-R#C}A%Y6M>@*_*{JS&b^3D1sPK>GX#W+3Inpv0T zwP7eE%k^!)zQcK7Mp`1U-NlY}(mUjXu8jf;FXpx{FLrmbxMKDbt5#Ep*KWByXP0fe zNq<~xZb$BVaKn_KuLc%|p_Kl-a)yfrbhw0van`jGprGz-|J{jx{g9x^>(*c4cQ@v{ z(@HxW@y+RWGp7rM%lIK7C--C5n; z{L70~d+23_36c3w{Lf&+=U^SsjxMHLkwmwphl#A6`|cl_wYo0SdGqT(LqEAEA}zx| zPUTvW9!dA=+eLKWan?P)SioPl?XPr?t?mvtostR3E7O^;--&ci*&v3XoWkaa5yJi; z(K12XFO4M^2Xeq0_T*tF`BkZ2$!|%w*a`ihtn>uxA5T>g>! z57I*=QGjI@)T4h>xpT@^SRo?2Wr3LUuB|KCQ_%G=>3`8p)D)}=*zRdgBw3rTDD*DU zhdn8na}fV^g3N)&m{Rn%mANwPNnd++O*J2Bo=VXO^h-RqAu5@hIn_H7uYO&E+_;H3 z;EU}Jq~zn~Psw9^wL`<#1hHWUgsXko6SoScuvMX2%KoPbIPAHGOWRU=3S4Jo zf`Rwpre;X)gs)^)B=Sn&gz8;sd@PYHlQIaV7;9byP!ZaywDjw(>+*$ipPzl)SGBeF zV%A+H?kvoe#Y=?Y=S~;&3zj3Zu(4*z8@f2j+9ruUp*J1}ebnDkXJ^zIb;e=ExL$1??lL+2ih- zByn?ZC6=#D`8o*6``ODK8qIQXqwYUo!+X#C9W|A87gR{g0a@W$xx!+@irWNAo~Gkd zdww(CDzF6vM}Wq^=bX(gb|Lyj#{BkcpKJ#9QM;3+eBP{vA)Th$QH18|!${IV9yC2R z@!$Q)L0W)9fBoKI_Znl{V*9*1n~6`a!iN>hjF8StKkG%$<8SU3az+8A@w@Rnr{|83 zn!l4}g)XJ$?bux>oqar9^*+ykg%{4e%p1e>F(!S%5^L(K57EM@BYuIk7xuTz)y zK5sdpkMl0T=${?|Az2NGFIjp#(|god(bPeeq?8zqJ_+@aB1CX^pU~Igg zWCrKRT`9)4SWR6>?qloN?&+DofYG#M){os=C6kI~1Vd?u)-dYs$f#@I`9y?zvY%jZ;AFT&2J82#7&3Z}=SGsXX4_}02lu#<55jI(^qA~?%qDlr7M2H`#y^+{t6^h0UldES%S)VvLgB2^X-~mjV&1}s^q6o zB3trhvl@b^I6F0Y?gisZsMwR{ezkRB>}CoqTb96FiGA1BG|I7LCssooKdj&9^JwoE zcidjK6f}T)gC`f!W$8Q&{VDxK@=h0f)YNG{N&vkZ`dRw#1VmIi#Zmb-5>vCOTzJG) zt|!}3)VmNYDF}^j(4DB=>#lb3jH)+hx2l~Eux#tY$Wn8DH?z{ z7@R^`=C*hk2z`FrZo%N%Z*9q5DU!l0;uyaof8e>tG(YDMDA&@b)bdcBC4$k0EnC!FCSWnP~kEd^`6}Nc{PBn4pNsa#!&N%u|$zzthUGVYJKR)M!Mtdn@*H z6=x_{<|$A9hDXY{vwDBqF|OuuK-FqYp_c`pHO*z|T=)_!d1B}1*>C=z+QNu=`!gqe zqLS4q)c7S>%xdFDm9a@y)3RSWV1l^JdE>yspCGj4A3`z^w2*QIH|U?81uRC$?8tn2T5PX(b&&k#8Fo>!tnPp9 zu(jMqrO(~vo{rdGQh!xUF5&2ALo5K=bEl{&+qPJm2K+{oF}Cwjys*0m+gKs5?YaN- zb6%AT9Of$Vtf!!XR~4&!j-T=5>xb6eH$}=nuB_flE1xWt5lWOx(r}%;b~DgUx;OJTs7;gGXagvC&7)m#Z(?)IYM^l=Y& zTV~F;)kRYNxhJ^B!Ym=6i)Z+jS{YA$oxe9}tm=Uss&m=k(Vtb!*wrk@{eR4RJZ5^J z?fjBUfa-Okhvfs!6O`Wf%Fb+Ii6+%Z}nL`AAAf)}Fi@@>*n(uk4=jZs2xiEHYyxT#Fj-we<;c z$R1u3Y`cB1H@2PsN))5E6S$)Cxsj|YzqQe8dH2JI*P!8ZH{9PIpT9a27)fcUH8^p; z|5ad1o*R$Wg&^87=^V_uAC0#M+_?w8`l0Ki8|Wf2+eoYs|0}iDhE`V(Y5!0xefPuT zOG)m2=N1-pN^^ZNC|Opy@aJyX zWeX1^*vj9fJpKK%*^}s8IP2MMWQ&XUCAONj8Td0kk%L51yhtPk*n+c<`gQc}47YXr zUqjkuh=h_ban(c%=i=_!>D9TTGxOQIxD%o&dJKQcM>o~A6#7!oO;%kjyg)tBGOV7OGCWv11l zGBaA@a8XOoN`U)_)?B?02}=fFJloIG7lQ>MyOkVk+Wl zrP?BgB=lB4)MxC=aUD=74`T=59DPe=oo6eazW2baxYi4jwJ~){Mo-sg@)kgG>Ur3_ z;;M>m#t(u#fcx~}SlL$^b?=x<(Em=*+tz)5W9JQRJT&?Lc;k=Fy>4e_*7soq&tBea z_@B>5)kDOpi#;d!ao*Tm6mH2#C7~G9w&*t$DRl{=1`C(FlBZ25t||?pNozLii47lW z75$T=yE$Ee#S)(R^frr@7UShVECXxz z6@n^5k(^GkA+bltWptN!?#-ILGd!*l?e0E_D4Q15DjJ&mmm!tpu*rWliXUV|VuR$} zwIJgRFVTVyC7RXejczw;qzCW*S}D7D)nw;u4qnD@35>ArCe_A8$>m;D>_a`8EQNqv zos;fjh8EF`wT|Qg*3-MI^P|}E#1+`_52@p>4m}RB;fpxAR&4VoaV6o-_ivTh?@Exy z&LGk2aOq^cGK((L@Xx9S?TM1vJulXK!hGxet9$2VCYb+*dY*Nnc=!I_vQ7bRZVQl} z0QME=$9F)8;|@R{kY9nX1b~*FMMrarizfka1;}k5YF`3}v- zdXUtD{YjGSogJAk3o$-?k5rycKKyvvQ5mQ^SCI2-IK!UK*#O7!#$eN>LCsfdy}K6| zD=5WJvl^aVck!1YgpTI(trkWSt0Fab?b}5hw>$lwe(UomxBPVbBRd4a&si;A4QbXp z$BQm&E=HG1Q4t&5Jo0|X%oEG3V&Yf z%NphV0?`JW^HnlT+_R2RfbztXcCS)b%r(e=y&o2`tx?Gq;l}&Glpx?;UPE3JL-0WXO0j9XLi( zI2K;wza~hmZrKb_$WMCg$$UB(v%|!mR9@MBS0nq?d<}&u8HU?luflA2?-p!eXGm1F zoGeek+Us#R1xg#BxEnk_8ZI{K0Q4t=pg9VK@Zb@Z9Z;#I04|B8p8pa-QGzNHSOQ}e zZ-FGy3miCvwhP#Nd8at{-}#m#5+Six69m`+@`!e-@B|)bs*QN< zS4h@R7oyrc{hQjIlT_i_jgnj?`|SRzllG&kUt&(r{}#vT9J)PpS?OMHO*_hrKhFE@ zP8g2~*7EI>rN}Q7PMJe2ouZl-)F{_zaI?C5AK%fqy<~?GSKY)1*aEJG?F}dTvgiRK z%+UQEb!Jmtzd>oUp`R8#f~#8(mvC)al!ZRzK5HT-GQ;0nALEkixZFTpDUI6`WQaHP zl2!TC;c9TNnZeo8QsnjS89>M(!bLs3dzE&y2xJ#TM<_(U=H6h6M=rfVyaOoSOrN7& z;LTn12Zbs^b9xD2B}r?LHqp@1Zh}TFWEb~Y3~$#dp2$qg1C`d<7>*qI0b=!OdqVlb ztZKM4ZLY_4xB~pPAAcppHM^e1Q(D<;h!<&nHue^>ddeFyIZ>p31Ur#7-}=^XtMp&oP)Z zf+t&liQB(L6iq8jUK9l$RpUJGoNT%~=^%w`$={z8Zxn@j?GQ$CH>_5s z9@ltmu?!BR#(QhimE(pM%a(SY6qtfi1BHnI~zNoA<<&E6m zwb|ROUP>+4;qoTMKB}Zl5xS4WS`;$Zxs(C2?1tdefVLI@WXfwGXGhFrBBShx5by=a zQ62j2!}4;A0?c1JEpZNtMGlE_;qlrvoBaHbmK0q0G2+Xs5X(rJodn?EJa3-@>4Rea zvER%nfpU)Mj#91d1WQ+NTALzaI| z+bwVlgJ>mTyBsn;rs+y%r5fuF{LRaHW>NgmSmmsd9KR?(tK}wzU;VK+$c_|7=yE$d zJ8J-Qi_idDL&@=Hf~nQbL1Bs5mVo3q5mecd7s&x=si&Ya_v=?oN(zY#VC-O1@QHWQ zFX`6zP<27j#9&3ibS!rL`b$$#>J5FRW`)i<-qSzcB=Zbx)DNs;KbcqM_FMc?K3)rC zjE0;Z{B4M!p1T$e4&+rJvYv5#Y~Ltf2stDn`k=l{2Rcg6O*h-8FZ<*FrQKoTRF1#l z_+%Z|;_vcOnqSC*R!+shLX1*&DBt}Ht6grtX*R6n`eeC$^?4WLOZp#=4hLXty*Ji}*SM zehgIUy%Jhq^|woQ-&?6-AEA-^FIp3Z>w~F)X(@eBrrkI%;QKCR@KsKL5dE9=b%aj* zjR8ZjJl~Z(+Te8q_5|Dv5F#R6?O*frFA@uiClG5WV9wa{UAtF&_w5i)mqG>b5q9 zQ}Q2>v$%hzAns%5A<~kw=g%W}4vD>z;m2vIn#XCoA$=!rhMd0ca6eGAlb1RYDN-{-*gxahTcjpJ>bOw_al&H9eC8F7ep!O=@mhqzBJu*3*jus z#>OHm37nAx9i}AHytOZQEv3GWuPFAj?gILKRTv6M(J-W<(t7oM1@KL2g)z&4u3{hpl z^|MP>X^^ofd67GFpmJnFBMcLl&FI}Sb>iLdcZlgIrzcaWd}fS-WNR^@Lx z{%3c6S|gN<*&P~lYIetPnpD$0m$^ysZ~$%Cvg&%>c~KLv*X=XD*?ph;b5&l8Vi;jI zwOhXzvhBZo(S0VMw?UKgpQ#sTOB3F4NCu*T)0awrX#sSbt#Ic-^Y;E8)^?$bTOGPj~U$Gg|qgx7?b$IOm9p1cVE7 z71PzqnYgZ=pRK$o6VHNQP44lHB45O}lxncFxNhNV&S9f=xac2VWujTWv@DsA_sdp< zxjZk-J`M;2#ogea0-j$zLsj?lzr=a7qDQpgVwgLSQxF#$d)w1f+-vtYD<6^^nI#|+ z?XsBeA*Xmf5?ax+zRavxaV>2&6>cz>pf;WmafTKOzE_$sR&y4}+<;sbjgrNXk&eRqI&B7Xq?&51(#QGi!Z z4x1oO#{Z25);(YL_gqJs)sQy=dSf<-hryHsu^Cdma`K7yDMkaDn`QIX2&G99sSK_OvDmJhWrf!k0N*{V3MBCfbxm1Z7$}7BI)DW^se`uyK8Lq7*cj=u&S35_L zi3BKu73`np+j-rW;=?T*y7GgySaZpctR&w2qi8_M|9jPCI5$YFK_`aHkbyxQo8RDejR-Z^=jUlSQ3lGSP0%znL1PsX(4&hR8O z&XM$bTsNo#(Ex#C%%=jOw)XZ--~%I;OMw4QgvOow9d>7a;}y2lfQNYi{aJAN2nF=E zkYyVIgxwdIq;~#y(@$2UGbQboz<4|*OXS}QY|+r6-(dl*FB}h#3TQH zU_%yqY#SE28ao}<8FWjQtrGWU&>o?;tkMaO=w+77G&e4`MN0i~YKxsa!9R|raH8a5 zP8wdvV>QG|@4=UGbQFSavX+kGyDOCRR$E6W2+%p=Uw7YtJphbY zJ^{4&3kb?5K9`muU~LVcfOGQjC?h|!aL(Z;>RqSA#>&I=C0Ie)7%5+>fYb}aWqa$+ zpcszDDp+i(I#4lr8TQ2DT$i=EBa!W*14Aaefj@cCtmv2frLNVazxGt_pEq&D z@r~^%r1+6np=;!y13Y5A|JCBu4UHV?@Z8)20>~v0oCgr(F3{He|7*F~gqZ)q!-qIA zsi`Kpm-K3z{z*4Qo)`8l4iOPOcwRia=C5hd>#Q@OKf4b(0hzV}(@DET^}5H3G`mn< z=Ppr&S56IB)Bo~%dz@V*eq4@Hef z4N=}7C}deM3Ua@n_D9^QkRek_A{^BZa-wU~z{{3f*X(*JKyO?cSk6S{faS5yhBhcN z-sHb>1+RY6G=Bk@*mbUhhpjtnlgTW;`vHib9{|~CqC4a)EG**tw82gifZ;e0Wqkuk zvDutA{DT%BPr@y?JF?%SdGF(*w779{FL5|qMLmxG%T0s+zo_GLQiTCHZ`N++Ey9h? z@j|&?N-M*>E%I2hK5UEVP~~?x+uV(@Nso-9)G4JqKJ%g#p+XR*$Pe2NrmA zyfv=9R^#x$(9dIUOCicj1=FS(p?}fOCuQ8hnU~pf(Gh@uC{ZouqD>XuCr~8rtAJAd z`-bajAJuA7ji6=ffh7|Z>%tVkYd{sTPJ;-7o1fnrP*HD989DsL8u1W$pB`u9t3xExp`E1)W#3#YC;j)Z^@-w=e9LqS}2ij&N)*koy zwjY+;Z#77DW5hWNpEgm1)7y@hUvoiPt-5J&sV)XhJ`8jsYnvpwyX0cPiFE_QRZPbu zzmC^a8w*pQt{LtrqS27e5J3KXcUOfVWB=;6y9EizAQb%Ow0a5o2vvjo^*9#N+C_^d z#p}Uy24VZ5e_s(nm^e}^YjeJqy`sI!;PJ;1!yb>jpt;afqYHZ;HQL^;*`G0QyWY$n;|{d+l+ zWinsID%Yu8ofwzV+v%cSQ;*L$OiTXAJEni)gT+vZ4JKT|*C9>cl~hzz zbL}pQg6|{;&G1gF4rfe>Tf{i2!qZiDiAbjJw1@`=Dfs=!8xTnx*Or~#^2{d`h;PXG zo#3DQ5=nl}a)DGy*dCxgoAFlJ4D8QTrRCPeWSKruO=8hd7xg?X6;@dnV_aZbmA0cW z5MO45EK{%;TRRCMx&8Q2I?Al7(c|OOhY~ab->ZJE^&-m-;kP`qE=CYY_3r`OCZ10@ z`y{+CkRy*Bb@3sCu!Q~zezDW%OiimfmGC+z5q^tj>QlBkAd~wlo zzz}@@<+~K+C%~w<16k4War>)&vuVK++L>{j5K#&#<>{-TP^N&Cv)zP4MODiq6;cZ} zcnKDAh<0*B3Poi0wB|xfzsb7p;ieVKKD*9`$QOWJF+;}iRkbj&TMLVSAfHPH@=9ad z`$%`Mw(8K}vFD~hl8@7$Rd)I+{wDNO?R>fP-M{|ReVQPIgsf}<3<|?H1*af~E6I&< zqtD^*mx%S>_hNNeGu+>6 zx#q_4+ga?!qc)Q2{tugb%}`Mrh)6cLR4iB|n#Wji#lsTMrH|FQytRw9_>QI%FL+F!xqoQ#{W&tvk2A;Cp zN`G&^NQ02D3RY>vyA&7HNIz7jJ|^GHW9L!;9@w$f&BI{L!Jxdgr^8&_@L5@=V^ieH z=i+>DIMP9yUV%MVcE$}VBUjB|tI&bw@p9TS>mJX)DKTKmL^QlXhB3ayrk!a33svnD zA;;-I}w7g-Jk66pD2R5@lg55ws(n@M@&medQ# zx3febR$S+zgGw*ZU7!QZ#`P~rNDmN$pyyTyt1G`7xwr)$bFLSk+(xJjs*^x(>7!z} zpSe0Yw%h2%s##>862oOmGKDd>!6`pOf)QC^B4kqMOZwsXx=G_Xk;FdBhd3=voKRF^ zIGaoF0|9os`C1lVJ|A*Co+}>?sAb>Z{dk%W=X8ZG?H`uDs&QlT5SxFW3fW3r|Dy+G zF?@pslJ%I3U-_vwZsSJ~$m%~`eb=X8e}N{batNjxZFZ$v7!|x!0xvw?3Lnk!sWYzq z-KFGw?)Z{(dp#LwJLo$Iwqb>rn8Xa_MO2p6a+-|-VBInp2;3t!5*D7WeN5xi+!ZlL zb>#G#RHuEb(j7}byBYokPiFR(^-JF=PJ^Es=Pu=KaX2&7QUN`#ClSW>wWN$Z)jld{9X~%}ESXj9$hz_$g_-dQOH~h`taiPnsoKrsxuvp3 z%f#wtJNL1xos4Yw4gQ=5)oda`AG@qmS9T8GhqwpcSTfE>TS3vh3dHcsb;>ra5Q?L? zPnans^bQ8U4_0j1;h+)l55zLB2r6err;>(itvm1Nd|Lx=wMHyaZ` zl%wyzjMZj)bTElKNS8yFhc~f5iOZ^d8Qp5|JHD%1PS~gC-sp@s8`qBpE*aZyw{wzD zp;rKXMb|`cV9F}RRdtB*1IKyKHkj#@Yi#O)pWj!mrr1M+0w%6+H_9-UGo_H{+{BCk zs)zq`TDJu*_o~b)|AGR>E*+*b>aWSLY#XDO`C(d75tmvmRoZ{O!(A53Qx9PS3C&mXjsNIdz9)vJlBuGme zltDk;);r8Gat~&g1}{>ldam6j?P+>3g&@qxxK0?o6%(hJKZmCHiGFM+F)s_C%ALIM zC_{JRLKfMW^smGjN3F_R`P)XAu^+Jv<02pJDP;*xfOrqT@AK>;-Bo3Ij`TiZdhR2} z4@NB%q`N9f^Ni069%!@|dD$*xF%+%)aFF)El=)szk{tpFNa8eZYK z?W2PCEpcFp`quSVLe^@uc>NMsucHb6&o_jCxF;>^ig7?`Sr)WH6M*;_#Bj zza-vpSm+i1+k`*Y{O4E0RwsQtYa>H0HXu0>xVbQk#O>?u?^z&ywW{sQUPOAtI<)O& zIr+)c;eoJiNQBHg$qQvye)^sFy(l`lpK+?p1a==FucAk^mpAAy zwVSuwV5kFyWrfKivj4$tRAA!P`(R-7$FoP~a~hF5irRfobV?*iY3{p}5#QfNU)S@f z?xtx)()}diWS9lkS^qf4?zUt~RMyXn)^S-2JC71By}4x7=sIl`3YY^5z9`jcYKu2B zrTQqr(S9ZApXX_^=gRIwK_C%R7%Ih&u6Z|7k0Jti9Q27Mvdvy_{W#lBD|bx3D)A$z zfj)?;(N9ZnPzIQ#s)uFbQk>#D#*ssS#qnxl6Ib(8fxUaCc`+-+PY>hySb2a*+v3o{ zqL}9XzQzrjf5rR+DjZ&o8SV>;84NaV^G?tKdS_h;4xJ!ws+WAE>Gsi8*k*F!+LinP zCaenzVU2=U&%}+>_NY(a86!#gmpyL>oGL;V?sM<2&_aK2JhTVMhT%Z&>1;mUw^-!X zjj93gFZ$6G05ewjnvX^>GbpeA@v9;B7nLfF4UDsK{FhK?bip-?oj;&B&>`B@n1M)r zQiVCP#in>`>$gb<*0~F52&nCLe0Id|gp*rdd(0R0UN<@(d*$W1y@;U*zr-9{$rg^A zGiv1~UtVlL?{!f7%4Kk{vZSQWmEL8w?v)8Io3fS`jeHKlxmX$TC70!c6QRqDwydvz zslGUJGO3;a_3icE1UtdEmwP@_z1c+CY;2UE2z(~S@%8bQUV{)`M+a>M6KfZy*fOWk zH(Y~bd}T&nCY*WJ+7;L=?eO})%1^2fwm`YR0Cee7n`IV#~&3Ik=nWQv%z2e zdWBpZl&#YS3QPKac$Yl(anZR^RbsJ99ZxvOu$zr4OMGxd90D4y$HJ#!rs`2`)*3cC zn>R~(axkPl5rw?_ViTKS(St_kPy@P;GJAWaiDDz}hcc6F=Vz7TDE58}W5P_hjFd;p z-1ivAw=2ipb=3&D$o7Qz(SUGa7xB)^@O6n|wfn*%lK2IkJ~tnY{`+ZL$fspqS)c6v zM%b$UX~e7Ykw%?J@^w1JN1_xV9NtyI%;|31gqY{d0Y>Ito%%DS0?kj_Ca?Oo=`xE6$*Mx+cEA^fC4&t2UNr%I9qz*lnHj?|5W6U*4oN0 zrOS5Qp_l9CjM=eVbe#DVc2xwS*p`>3}0FuN_Wl3*^^*w6DnYiFQoP| z>BFAC)U=C(A{BnBvfSo^F2+4RE;hk(WP3R2@6*=c2Hi&d0|2iu3aQ1NogH8pMZjHM z5R#tOPWu~vSTYqvE;iXnCo`^4fVz2KZNkm@(lgsFm^X@&d9M z>Og-InvS0$HoovL0KXL>b72w&~wTp zU2#Ohuc$V3E!{XPPup8OM?6&)#dZ|RIzn%m;}fjbRb!S+)yG{Y$76#7t``_=wN-^I z9Eeqm#M1x${ksQ%2|EwjLH^RE;Zl}i6E|i=OaP{EUc!y9)}L|MiJnB)@j123UxxK1 z_-I_;NWSiR@^vyrRl42~=6#-v*nU`IhqwEmGRKtMcjxtM)<2>S>5_lsdX%sxqSfm3 z_gkV6;0+NGk*n7vxEDqaEIj}}O8A0s?f#`>QjR#^6MB@kg3V~!wsA?-)gQ#VGNY-P zKTWFxyC$)|h${?SElhmNUUu{6M{(EL3>~b3u?-^YUY4P9d1R@0zJtWR*1dbR0}GJ* zvg(%H`X>4uW20I?qMRs)|#Ad4aJs+^q5U=S&f z!C)dB!6CfGB9vJ{SCgMhPeAR)R2TMEW8uV&jD!#Zj%l3x-nL(Z{;q*lj z34waz!1$SqgoM{6t{C9MYf9=;Q`sA9TA3;>{BQYnAf7}z`RciijlT5@ran7*h^gUY z@JIgpphYDmQ2;I5f;X|gaR6K#Ix}$cY!M{M(@3B4?n0nEplE<}-%oH8Mch~#bfpvr}**7mt8ww&zE(_2bor0_hIMotV)m2UNPFk zHj~zsq!3?o!DrYdQ>OEsD%#mE@|&n~UN0z%p8meUl)ki{8uM3sqC=w$c+HT3c7`pMsI9fZ|1u%U-LM z^eFIT_z^@dJ@clt(GtAr@MkhZFIs|8XRX6TW1+b-Dc@v*gNRe4aFEu~-p&f*eJErkmm(G<{0VOklD@p;1iy7d9v&X? zb<*u8dA8agwmkzI?IyU7VkCcKBlDxAFkd$#Gts}=bC}+1NOrDCwxeO~TYTY1S$u?He*OZS{49{z9foU6^0;=u^PLK; zK#($ncS%7(*!K1|-SAB&GEhEn@$lF+USVg?ZWmFTzG3p79T-c?%gghnNl8gh8saY& zTK~N8o!&dr!U;2u>FK}Y$wt|-rrb=)oJ3hS-l%PKMsn`bu0hz%il41dW2<>?eE&8% zf4QosjjTamr*&(Yw6y5I+01~LVgLq7Q%kD_;lTsRrxWoZ2DjJgSOGr;!SBrxlPs=E_f5;85|giBLfk*=ZEbx8 zd>i<>!P^^PdC5mwR@TNw~NqOsjlkb-k097wu^5IYC{QB0`7BDZ}>!%bo9wc39 zH#1f2)en+z5&qKJ{a*Zq655f2EU$5Kz@#URr-6Sv@rgM4`ErW6h3-pw9_98O(z6n; zChPb0cScsKb>Dgf7EL7R#euyqC8cdXK-OGGkZ0Q|^*f1x)fNpKLABT|sIb8?bPo(W zLE*-NLQIfb%wvMc#0w6R;9P*3Rp`L^u_X+6<&vDg77V9X>eRqrKg;B%(vm5)Ci>CL zWfrsS#wS>?8PB)u*^Q=sE)|Be{_Z;P9VQhu&nRbtD~u!r3=-Yn+?Xvk#t8|kk$x#Y zmqv)A@ju(PARGy1p|F=~6poD>!wb;d!9X7U*W8?lnU0A`7Xs0%T}Z2+TnQz; z@CiJB#J~g40A?_-qRxZTObFnL097LPhs8$<_RRp3GJx$2k*gsV0ulE#`-Qw+a37t_ zi=wpmYTq5SR)-ybi)R=M=&8?U-dCkoKBIw?oWS@5dD!C*&JI^y-L&&32I9-;`_A7V z+%QJo|K*SO4C4-Ap@0oH3DoAXW&ker0FF__p|xxH16Y73=6wN#Q(dc&srwIH#7!K5 zbU}3(*lk=Iu)}R_fv2fA;Jy%}801wTFiAv9xYcv3>Hf4a`NO0u94c~OceAuRVuYQK zva-UCjpP0d(^GAn*vUOjI+OW%t*rg_GAUh-ebbn_aowKEGo1f zr?%m0(T|Ui;?vFP*uK3~C9C^KZ$@eQ;1Xr0esXBOB?p76rG)L0>C2InJ54t3js7)c zQ#*fG2YNRp_j+!Q*Pp?;_dChsSW1%%cE*G_eCn5}Mj<*K)lM_x|MA9?(R-z3idehk z9oN01@4p)GWtn3dIW!KJz#Q9c(wYhB2dCn5H(da(fceswAqZH`!vQmz@=rZMZX$XG?>@w$VtLG=@xVH|Ltjhz<0t+4r~M9Rcrwe2 z_D?u|TS2r|@?+t(_R1wqEGxH=G^KjlM~{hLR+?a@@FAbX62@MaV0DuUKaG(``DCAm zn_b{j*;1+0-za8C9E4U9&fX_0#veZl2hsR>@Z~i{6`1132>*HnJHGSzTkFmGGG+Us zk6M(ULVk2!&4}G=D z?0q97bJ~!t*vgIbezY=9v(Yws@j=gQH>` z0swdL>hOR+h~>z*$SZ5*JM{;4H{S1zOQ4j-_Y93UPl`z|_v6-5?d4@U@=oD}DKq1j zcNj1icG=zN!M#*8>?>w@?W#Jpox5r6{GDYY`k6Pp&F7P?TrU6p@%;HYIl-{F%FJ7^ zU%YsMDtP<$7kGUCLd>P~OQjsfGncOR^XHw<*^fAD1?S6DUy5fzJryu}6MltHis}@# z5H_p@-xZ~fL{}zP^G$v&cU>~2*8gY<{FZ(&KvJQ#Xn1`^@cSFc;_6&3PAK#)nuu!^&vjQ_|D<$mmQXA)Qv%*MR!)DS022jo5j{XtUv`IarV8sm8!9*zIHmTh& z3cQ4wFCJ|hnsdW~;HkT&5#o-eEXKxIwDwJ`1#~!S^Z1Y z#$AUpQJo717nE(e?h&Df`Wvo13$jKD-;n%!8Cc>$T%gIsW>CNdzN4YBfHgx|Q`T60IF@0_h zz&Q`%v|4z=k_iCQ7 zBC1b+9J1#1Jtr{vLqg-brKW0+9zEJ}0h;i|>M2kAtvw+jp{@=f*dlnpZ{Jj<&yJml zh>34*eY@@`o_f6M;5WY10KUU^-BNqT$QglvT_F@}1Hlcd8D;$;-!p4Ge ze;P;mUg*)Gy(aQf*`{GS_Rbz55(99gL7=(&n?I9#05}@+`gLuqko56}9Q>9pco1-| z#siVIfZxfAS?%taeJzCije4{_wr}6=E2anw$vMNhe%@=s6eWE3?aDuX z-RC6dglYV+{OkAH!n)SGQ~bN)gPR&-mb+M}U%KQB#{Qj>_;!a^O>}hRTwGkXJP;}I z>eTAWo1!9=(w#fDj;AnXW)2q8IYDmm!jr(`To9h)P|K?B;`>sr}LduF6pOkbcWUBaK-i zy7&664I}>Ez6 zf06dx;av9b-$p283l+)?8Ih5h5XmN#JtAdhZ)K0j&K`-7z4s=`$jBx{_U2=I&a33>z{GR8J=Xg2}$9*4-&vkvS>-|38=lMEcuh+R1;jkkejfNn$uY8!Yn`-^+><`&M%?(QNbCf#&QOny+Jf`2tmBV(*~ zGko%B<_(gn+9%g;9j|YoWt=WxCl)nD zP^o!N^8sD^Q49QDp`b$UU5kDtNcz6(H~xD()c~l5B+ih;gCid#t^dyYL#z}SD z==nI2>WT_OlRc7d{l%#LjG#wkHc9>}==SOxK2 z`Giz7hz8`!ZO!{?YHB-&P}*)oo?OZjAj!l-nR*bMd&gVX(1li^S+@a6JcrdCm@lw3 ziI9+#PuKNFSMv9@!L;g{^}Tl!kcF}HnR4?va-SVNfNVkYpVQko7AA9cL&n@2%vmqv z<|YiZI*?ZU=p$MVuLhIYv!mgLV)IdM#H{}e24C8Mmo%7kJAuD8EgF-2d@H!~-22kW&v3P@Cj@Q4^uSAwVat=qSaVNPGjHU9kWja>Ox z>r*Z(>@cR0oIv#8*A;i)har?rKvWvL{*X?wjZm>)v;2AjPx7w!x)Lo*`2Oa+M4LAt zO^#j$)9WOTs>(UlugE@OOtCHpi(%f#w=zaW95E(L$~SvOW}nRHsr>;6Z~p@1dPs~| z9sC$3irYvmef`Jm39_F@O;g@=&CkN`&eEPA;J|W1U_}rnSk`W}FT7fFfDyDi1jvj| zqmEEUKE9Ze9>HKOt2+BwR8ME;Ob<@$EPdLj#jD`(}OpUPZ16l%+L!2s39H(Ak?u-$ogb!?p#RTCLc+> zWPIJJ#-uT@bol4BH)yTYICq5fY%Ri;eY>MCnh@#P8*};-IOS$@;#x?IN5`z6sx$+H z$oo&qGa4@Ljco(zfr_SP<-jYs0b{7B<&p%W;Y79$YquJh$dw=zi2`1mE&L_!mxH&E zv)E%NVftTt{GphejBlM-hgHr_G4BI_NpI3y?nf4`XLf-5@(h#mefdgrodIPfB;7^3 zuWFxERYq!6;Q5g+Z~rmEuB#-$=0!Cxznp!YskE%nuBUh3edd8-Nm#L91hT$lS~X!L z0$^1lh-vai=`a&O(3ruW`15A~dsvaFxsPLRH_cdE!-QCyCM=589|sn?L;}{o?kBr# zcb3;{)4_{UK566qAkJAdN*X|GT?}V-b$$QJgRo1c_XpSUQ29RMcVj%>Wxb@{qQ0Id z@{-@*VR9u1YBi+3c(VSORrc>vKWT<&=mcq1XIIx;*|4q=RI6@KY}~zj_kB!EJ4`Kh zf&mM0g7&Nq$NSgrttr4e+^9p*IMgHoQU-vAkR4wHnpM0DDgJGP=c!@8qo zj^20z}^Rv!(X6?NPfowxPRmhm3EBb$3&y`ORzh?#IT+4GCv zALQVo6G9C1^Q)Ix;U}jsbUZUz#q($&<>H0%jXHyPCglIesAa#*WNS){e(O8x)jggJ zp?5i^z9MBz_(A;E73Xq5*+kjd7%^32g}=HP53T0?SzfdcL$dR)@Eg| z!-{?LpJq|#m|D~`7zf$nZ#DhL7-VC=7ap!F?mzz%AG1chOFV8$vURFhh(u0}9oiS# z*yRE;b@fA>uauO zYps!Z^oLDv?^bfqlM(Gl8MM|~6$kHG3|R(nKJoj7s^()$ub9$|edGaHyb1qT?&yd( z`Z&j8?#KFHq-e9Rs}}%tx)RHSmB5x=^$&0tU{?#5LEPIBT?3!_fpg6^c-A8iFcd@( zg}#wJ@TlYuzxkudOrNV?|50~afuaAhS`YfPOCjp*Z#LB8CwZYwapV2y95!t)s?A>^ zE7yM1V6F!$wd^dRL3_j4=IY<#Cpk@CDjQLQjEra^;o1uw6OkzbOP?NM93a2^6I7ot z%^p#|f`&#urzYX^@%VTIH4vGWD5xq>8>+Tu!V4a&&D23<+UGuv z4)j*QO3nXebh0OPB@4M4@zU8?>9MY%AswJ9_YjmEu1pWiXZQV4f0%pWFO*_exc!81 zE>GKgGU>q)y62iYEtk}7)vX%`cuk|U5gZ`I%=gKRQwbkh6<)MTfYxLsHo=gCyl2=(i2>l!k#7{1zqU9K2h4heT7~%0?!$ zcgN1vbLRr=2wL&Xg+$Di!jz?j5v|`Z5^U-mZj9GmB@fnYFS(Ml;1lXPdC5R?>}Rb{0XKJi68}bZ zEYBw`4&->eE(yT~j>oahoc|n;&B)N6=dn8NFqI+DfRc=i3?U3#!@LsPA5s*^rKj9` zm+bmSMn*Cd0{6Z(coJC+39c$} z9cMlcSqUk2vaCd>3P5QOz6Fd@mX~w3t>(DdA6^h97jmCkS7@h7m<$X=4(e9fztI)j zTkZqbo1-HasAj^(*A|v@3l<_CbC?Z$aMg~&_yE;|5|9Q`nU1tXxJH(H01_5foY7c;f0ub5Tu|I(Ti%AXj5%*VFf0tw&6J?5D)FO7SMM;i`qeu`}BJ4`ttU_RZT`wQ8+SU1W~m| zM3B5~(hvTFXy8R?Y{P<7pfdoZc7GTZKeOlZ7axK@g6Tg~bJv0c?3_(D|2$QBMDZrq zQ`4Ux{~Db5PQVt(erEMlIj7#~lDHo4{^z^t{reRR-sIYW-T}+@XzxDhDgU>yN8E+f z-T;EUpN4329dvC5qbD!m+7;6tLP&N(%B;WuF&EON_x=4U3*X}g)^7mNrqJz~YC|j2pvo5r9>Vi%o9cNuU*bNg)f`ehM!9IVY(R$EuX*$&%<>;b2F7NO(8lJJ>&6{R zZ6`hljFFG+H=y`$aQ+=Gjg$n?$-M&FC_Wf{)$E{JE-6_p@?U47i~mF>oEp)*LYr~o zw1CrHxRJkc_c6C73;f4CzZH(E^fvX5rMu8u%%%UEW%+dW^e~BviheO#S5{`_gC4iH$8tIQWbnqDe-p>Ou!3;zZIWDi-z2CM zj=C)Xuf5{+;mgMtw~oko7AFsb@o^~mmT^T*b|y$Wub%rn?><0!`5ALbF3Z_~N9qA8*W* zDpY-9OUu4hM(~=+@terZpHHqf?xF34_k`B!!*6kzvVQ8aG_!P~NwD`B3U6-KihkVG zyt6rU<}(uj6MWoTEsjMNLb|8crb&B7%wK1o#HK59W~Tjqj7yQE`0Z<#43#~LUy(F5 z1`@RynlDoeM)~>q6^3Se-f>Wce*xg?`tD;amT5GXVs1M{8ZYDWQ%fxWKz>a?PM=4f}*3#9PeLY~sTVNbh|mB)PaOVp^NVlJJp>SVKpB5j_On-L z(*mA`;HMO2`6*Yl)|X4VJdU$dl6zw*?fnJWXIn!YqnpB%n@ZdB_Jb$8OlX%dP2bm_ zvr{@~Xtpbkyb{cB6({4Uzo@t8r<9Uigd!d`HPmeXi?**oiNH8G}@K#p>j@Vu$syg`t@KalFZF(}vpEJih8c zv4k@bB=nr@lisAvWDMabH_F&0%=0=loTxoKkyUW1fId{fu*S9_(SAB6StVYYldhQU zKj(8zTQQ{=zmVQ=8VYs@9{H!)qnArlp$zzf6V=eji- z2n!7o+Dl7smA&{u7b>(a0K?I^@V${%MGfSUPg|fMRD{X~;_-FsMs%d-E;c$dpN-^j?yvW0Z$7wTB(Xf04i!xTI1w_@5{MsVZM zbnz{ybkfx<{im{uR)tRXd?`aU4P7=4cgK@cvuEy^cmZjkM6ibd%e@Si?fal7VQ2`Q zrMO)za57r|QS#@~JG)8Se9CqE%!|2c`ZHBg1t-jzX3rx2w(j<|p(PYt027L!@$h23 zdWGX`@Ck(tCa_dGK zTF8`3gjfLMq*!j<`UMm@OAk?^i`Fny59mUFt$zS9bO!LSaw#(b_)dW`6i{(*x?v&} zcT@kZZXRg9-0^l5WiKy#ncy(lm7My?wdQ@LMY-CLU#!sX@JDvHvV_r-8LRAZZo-xY zI-}L;N7r_kyAq21kL2p^&rW4wGCgNIQ<%x}WLV5CyBmwdvQkB8zq}gGw-|VJndgCr zoEh-S0HkG3b~4hdj3xVgspv;ET1=;rdp@2RmK9qf(d)0`(LE_simX@i56?IrgSqt$j_2w#?tE#f|b%bRNsi?P&}QZWoESq87eAQg%k0U-Z>V}VjCd6 zbsb_qmb!3}Q~Apv`73-j^)D~B>dfL{oZD-F!e&v&hj1jLoW2LFv5@0qJA)ewGG8;2 zS&>OZBne@vw2?G`6dcCGB0aO6sx%4ze!y#>XM@oQPl1y6rJAicu0HgBpl4X}awsQh zYI<%<2~LNTC#tHXXZ$R5;kmCBKHqr0fz_$;ED5`1p|L9OUTMWkcmIhN)p`t19Z^4e zzYkO4%Ep0eP^+Uu{sU)}%={6>*YgAXx5>B@EFZtdZBHXaRtAE2@%`3VU{TEFJ?mW{ zR7lO&PlGNI{4%E4pLEni2Dt$?KJF$AY)^0wfdWP?p*>_IT@ChYSy|Zxlwopl+`dQ- z9H}4}2!kBseDNgCt=U;wo9ADLM@0?JmQhhr0ocu}x6}1jZD2>fckMg1Ji#++!4p`mSq^|zM@K$!q6M(5R{ z4#AT%gai8I$&+rqT#bVDP1hh9pU+N2C%(T{2_I2tCS}G6*$|;kecRky*$Ua7=- zMpF#GFrgFc*Yn@EbAE~uQf7qK`+b+7S>%?IlC~3cXR4KHP8~ptEZ$g8TO1g@;BK!j z{TGGSL-<9(1&N7?S40}dn~5{c4Ps+r{90y4EdBbC*8DJwiHXVVo=f(ZFXnf&5Q5(K z@81_*#c=418HQv|9>QdHVx;4EY8yEXTsMb0TH+--jCmyo)4#13DTR^^Jw72qe#N$z zZe`At`?rA1jDLJE`2<*`X17n{b1rj63eSd7KKyg~r9-tUv{~wpugB!|B4e7@Vvv!o zmmd2E8#spB{92Rz6q5RTB_VtAM09GIc1h%Hi(n~<2|3I1P`|th%a6vO<6;-q5jK(@ z1uX#RLyzQpAH!7N#bM6futA^`5oQf^o*eGPiMk7-K?q@lLIWB(7+gU00w$<~tgI|F z({c0xe`a7{c=0GXz`S6U)-eZhLapo1z7ZCnVrG+sHW zqum3pn)O()8}@vIh4N;cEzaD6#A*^#8-OWJ@YG){P{>RsYog{O1A*XWjaedG3O%2S zm+Wvf-Cwv#C@Dwk4C^L5c@Z&88nX8@u&YZ~gEG3RO6NGQ*!6Q>lRx!`BP*8|}rU4ai4VV;&y!nre#`-UB=g zLK<)de4c9qxi477=H5Uvw~68p1PhwvLGpkZEHa?dYwid<@7lnYOCKQ2M5Pe|eP*fe z*db<7_xOk7w{bYm0@{nMSTvmovOgBwbRNN?^fRy*M!q|ZDSS<8!TL`kpX$$!ULld- z!=1FrH$eV_;fz!*^8Aw*8j+dH2;?>CINc46Yp3PxECdg~2h@gyj!NK{BHHZ7xNophI9rS>=O zx0q?H4-nlR?JJ+J^I>H(L2_KoTrb(&sM?6HQhve_BwB+|OO{_Ci?#TjS-in$YCBh1 zw|uVoXt8f%;&nc&DLHWT`4UP`xAtTQ`}g^kkxtq-qXiNtok>@-d2z++e8y@WfkULo zKuD-ax?fC=Qm)^=X?QG0_v&QMfT|>GRCvP?x(M>iq8d>4%@&4j6mX{N|G)yA!OI|P z_>4cY6t!f~pvVC1|C|X5meV5>uG7j0zX;wln?xJ;yijB#^;_zcwQp{Co+lt+#@>pA z7y~UFD8t&em!UcSFrhtoWD+GQDHuZKHQO~}CXS04#7U?_VGw^L>)d=-_1j(fm+`Ud zX2W&mveyMLy}aV z<4&&Jp)zXW^Uxql@<4OXs(lBHQgJIrEWDmfPzxBuas1V%PxlFeL>nNG zH2t%9L>?L#-1NWx`m4hq!h64oaPh|XM;}4ewB)>6*8)PF*X=0GmN!cU9eOF#>sv2( z9!Od8Y5U1#4q)KrbUk>J=hS;>s9zGE!W;NsjJtP66@hP$&T4m@~L(dBD1+MYj31M+%a_lDp z!0V&U3U`jD+dJUmpq%inx|yJU_OEy;;x{ROB<>jAckV+VGtNupC*J>y$A;2V`Pd_e>;(5o`p89Qp@{K8X8=nVDJb z-cK#$2Mj`s?3Pp%1eY@S-sQ!q(Dm-4F=NGLtiNACd#i=L6& zN7qkT86R7vn#`@hqHz!=XL}^JNnjrOB6sc);ji2-=3m((OFIsZ+&v?!3UUmv*Y6R$7ag9QwTt~i8@HTcu>s%BIW2Qxe+tlHVnK#h?g*qbUC270&HMHVb1K7gr3EzLJ4g_z4Lf9o-rR0NGX7 z0vlu-GF{uDCmJ?wSWSpyAo#zK37FaCagYE^4Mysc+ zGHW+mxMZ%r<{On337bp`$}%KR5EFQFG|Q+i9cg(Rp5k+us|wiHy-2vVj9h`$!j=yp zodC-}gkp!}dq6Kr1m1@&1Pf&~wZVmd9%)M~p|7c5Xe5W<0V(^t0rmWYGyRcE&}bR1 zuvi&-#y+{i1qt+>Q?>JhF@l0EwX^$E6Tmh;BuN0neSfh>-!}2?;D3x9aGDIDZ35v2*;-X$N@a`IUqimj&jI`dv>VDHI4^Y_fFwHiAQY_GZ-L>Bb*0qXjRlg3T$x|$jrn`RNpMUkFfMx zAMCT~uZ%s;m~$koK=f>SO5s+6|-(1rBpz* zVOg-UmmrpVV@Mpo<%aVjE!V20Y(up{>@eTnsj@NxHyi%}&DGy&?NBIx?e3m`FF`N^ zeZk*Ayb%FR!GcBu`Px$_T9AO;xOmA_e0E8l85d8ZdFuY>(Zl4;A&VwBH@QkzlH2eT z&T!XXC}$sQQj1q-$IDx3Q3I%vF@TUI!bFb(py&tX6^yF?a~)=blf)G5aT*dY)yt9M z_F{XYSNh#w5X(~_+5Ba*f&An0PI>(_a5en87QENozp z4+}~G1aXJGo@XuKE*LyXGd1}Qi4Nu}2ja!GyP@pzz7^1ZFUigCFO z2+Uf0)nnbjP?BHy>O@C3sUkmB13Ybu#cM4zW0FQ$=Fmz{B7O`vE^!K}#!BJe{jr`s z!*=UXby48dBVbv#%gNkftGYWn zuaEtR(h0Ydo`Y#IZ(>~#_(f4}&g?`PX-=2&E2r%p)ZlAyNFa~c1LKL3HSRC(gQfR& zX+wd6KF|sQM0rbno@D&Ea8g$f^h=me)e26b{b*+=9L~{#zy7j3_~IZ1XPWhvl>SlR zh9ktXiBN+QO!x8{KGx?9Z`uvN)z`%K7o0z^8?yqud-bFb(kLCT?qxJOI)mr&N_L_L zd~ZL}8jE7(tyT;URgxqe$(C8-)Q@$89+w3r_r`Tcxv1pqwB2jCSCWIN zc1gznyx?x1D#^Q1X4~1q!5}zC^!+}jZ;H+Xu3t+TrN~8s0ki9`Qxn1BEx;i7>Or;o zNS%3^t6M62d2*xiPXT9UksTEpbdT*`tpYR8Vt(Qw7_S1y3o`Xtf&*Anm439%UT{toHRoVMAy1Z_GO zPz{Cr1>*PQ@(#;3)$%{?=B{LO9(;ItOFnC(@PEY31+4HCVUmIr)=mUCGBPNlFa9U0jpjZho$p_l z!5dEG@hE`)@)Rq^J1rYY)Ywv4cg^~|+}al>k$4_HEvc-FMKyZC;I}AXRB}txi39lm z;pd%Cjj8Y808UD(Dx0x2WXW_sH*m@6n{`$Q-O8qCS+*usf;-tGiJmlQ4hA)xh^4Dc zz1p+PhBqSe2E>{&C?z)*Ck^k9{JUrTl#}OS{0a29rsjJ3!|tC>E`PckbsMYHPSIG} zkeh(%`12oNjvz(w$zc}hrrI;=$G2w-I1Rf_;sDRJW?YxwC+^jEWGr>A9dth@blkoO zfC{9858mxbNoL6Z-D& zMC}xhD;2f#OQu3lIST|;7!MvFIAl6>`FjOIzR@$X<`_gm9H4MbV&8|Ns48+RszAT% zM0JbbvP>|>j@xriz1+=B@T|HUj)ZXc!JUzhDr3Bv-Rn%Y6W)}elviczQw{g%4P*g+ z7U=|3F%J6FdTv`-z!w2Cbi{5B@Pqh*D)2K!N?K=71!@AP919C85peqMUK|W`gz^r+ z5YqAK6+OP)E4+ixKWP_9ZgoisqHVRHmF0^H5wF2(H}`MBisb%>#3W?ppqoH3X3wen z7$xbz0{a$GsW&pEDak_X@J}{lu-1*tE5*n0l27KF1s(1ofoLKx3@LRZYN}UJk85_V_T)G9kLd2jorqj{r zBVDE^|KhvYa-+K%x8X^=iLA3jv0E>wJ{Shgp7maqs$pe5&c`xmhqZnh(@ubyI5&K#|%N{UEO0N#B%|E!H6U ztSMk!qMf)`wRZD1fJ5fVC|7Pm&nu>Gp1B_%;atSN%JS4r6s!XbZJ8qOoSB6zCK4R( za63;o^eG*&pH&M7#b`e+C?Z^c{RhJQQhof9z|i0z0$;kp#pWC~Tq=h3xxRutrl-u>M^yDUNymTJJV$s)Q*+hGPC=PkPGM#dW_2 z9`VOo+vyz5Mk^Nfw=XddD2AF6Y`qz}V7>Fv{R*4dIGXulq1Hnzk1n(`arZOrn3Ii% ztVwf%tGaY_Bvs2RE9jIUbPV3{JnYg#)WnX5W1}UeC9mgY!Jl*>G-%iixle?>Dx@{; z7OeR#mN21RybvSe?BbH6X3|#`ttr=wo|7i+w0&VvuO#&12$KUfofXZ4XGW!ao5;-j z{+w~pm88p0UX2QE3Q)}@wP7hi3mk=i#nH`Fh{6r7)W@+wK~ zOJ%V6`T59sK#2|G`XmdAoH+bzcuERkAz=)`Cgu9Yjl2a$;nO=nv6b*Kz8saI|{Q zJo}R>`5~NKSmB$sqxtDpFKUJUm$V)5=m!o>c)7J8PiNc#_hCw+ZpOV&lKqI`KGO^9R{H_$&feL+u5I=Mk~7 z9V10XZ~7P#pj(mzw2=M*i3I2G3H+cu^I0=7x4*(GND-d@e1*MllVxP~<_dY?+7a_5 zkvDAFW;peG>^;K^b%gh8uOWzKXyY&T0Wr#XXF(5=Y#+EUPoh8=Sl zt0b#QYj~1Z=~Ea5jjn?_?=6<8szzbovSvRv$c`QlReNG$Q{hZYX!jUDel3vh8h&Sg z1EDV7?=GihfZTlbE3mg^A&N?0x48hC2g@^;`DhI|82+CTKJ{8gH2i_P@?GmwzW;@^ zO&CsQ2H25!UNXOa`3;>+B34~Wv7mA*u+W+os+jd1vx^W@g1y^fvDxirzFrXeCELsEz)nA@X3<5ry{Nqj8O4-95f7P=BSuQKe|X z#=Pgkk%B9s=@*ySpn%;AId^QEqE5Zj%*s;t0|nAXI; zZ=w4lOQbu3@SlP9 zR9V(tDdW#&P5{a6V<3Sy!8UE<-Q2Pz;*A(=Fn`dM)!o$mw#JSlAzw@3cu9>h;k}iP&mHyOg z{L$5I95etT0)u!JH4|k$viUqk;R&Iey!R2$ir`zo#&0PU{7KM;5=-`}^T7E)=IMcj zuIT$$QYDxO*)>U=9BEJw<~ft~I#yhmgpbGj!U$l&0gIF}^aa{-uqY54NYS(}xz6Qw zRd6TERG3m?n>8Hrbkd()Z2W1pk-B<}^Fx&TXD;VaNP3&+g#ksk22$Yl77%N_f7$=) zJi&%()fZ&+z)}3MK@TU`z8aKQU)2sN2WtrgZmv8pWPX-(YZeI6qr3YT_&lwz&rgdH z32G$anS6d^`QuM)@zUBQAmQ0@0c3H_{c`rPHrD+^6iRh}a+39y=I6iFL{b=1O_-8U z8ErHbj^>4yY4J(p!|U@guvLx~OUbeCefD>~NFab}c-EHCttvXZL=R?3T78S;i{zVX z`q&~hwZQf%y&#zpnGsU^p>+C$$}4CnOu2gXiX6`io1EmVA~$ltOxr-1WQiD=IEGFGdx)a=`I#J4#FZre@7;g%fGdW2$4d%V zHQYG=2|`NPUaUZzus|ry;f1Qm-tl&%Ces0({V`r^NCjV5fQ(QZO2lumELxSqjn7$4$ewj%%@vHl<;fQVpvr$T$=v=+VL&J4V<3>CMY-8S%c2{|wm`Aq zgh$fq()94F7}j^efO{A!R)vD$0WzAcdvP)wEh)`~(#m?3UT=N>5bX{pp5<$QSune|U z`~>gsHs_5Ca;Zh;_nxz@gYF5W7b8dn`4-$;1l41pO zW`GjFJXD~Vx%R%=vZ#8;GFcm7w1Oz9Rpq)xp*4}~%40+jJ9Aaufln*Er>mKSxC)oa zGtvosbSt!yK0kilZbBN({W?pJRVGmKisQERk(?WrtDWFfPMP`PBAMHsFMKHX_tX@i z!DPY3@LkECN}uF*z_H+Ry3kumf|=&xEJf{jmJIkW@`h*;_Mgma}ceK}!$XmIb6$K%C@}I#eVW-AydD zP>FMA)e;EXplrJScZ-z%MI;WFMSZrFtnj&0Ff>qWn9%Q{2dH!R-Vu4C%_(?5nRL}o z&*e?&+kXK86c|@c%XPO8HxLj%*RZ z*oKR^Jr}8&b$*S_Sv$xl`^|50^Q?F{*Bqj)ArHspc$iRK;R zy}`(VoYc3Y1s3mu(&v7k^pC7qlHH+yLZ3Vmc6*GlC9tyZU#gTAuP!gU5}w>m9Es2s zY?uj|`!w5Q!W4$S$LeKk?s1Xl(qi5?Z5)@Ov`#O3L+52cnL%r3`r^`yHAUEYk$=yR zF-as}5`OOZ;8a?__5M#b{or!gb^-H1f;U!l3jaLle#wQcGes=Yum8DvN6F ze7IyGTVG4ym67%*f_qyfm{cks+Bl#Nzc`?$2=%2QcCETJgdj8C$H6MWSJ-DO=R)bh zg`|bcX(g}XnXo4`AdDy<1{XkEue34~W=DWvA>#e}`@q-+sb_k5`SX$vFuAcFG4LlQ zCzn!CAb_5rqjUo=v6*4Kk`uuJzqc)su`n()ky$}cXKX78&TCl#-N_(~Q7T+?15<@E zLG`Sh$!%g#xm=JV!RcnO_`XMZHJh@=Fj-N;Y_$YJy)3G7bYF zWFw9y{&k$hhrU6c57s=Jti=J;4y!=IuVl&SAod);XLTs_@ce ze`J+3?UGKPOS({7=i;j5{R&xvwn>_y+C1U;auLreM2r<1P3N6#)hurNi(eBmu`Bxekn>m<~V=h`$Zx_@$U*$PY%fsR)PaM zuU8BVk4$y~Y9@5&`8cE}fbNwGZDeawk4bSXGM4um15St2qLdZ*Gib&3E_hI+znmdOF3Ww}!6bUAcV&$VxCbDO7OzmSxQvpNgs~Is!NR59_CUOBs>K zA3%4%WBxU-9*^_3F+y+y9iEJW!ul?Xp`ZT3%NyrpTy;c_7z}!b_H=;#wiS+c3LIEM zCk%Koilf^?EaUTgmPge5V(ECQ_0?{Cbt33Ii=%B%u(OYKgAIZYJTo6Amfjiup;Sy} zHGdW0wuse_XL-%K6s0B27LoZXURQ|C-UXbEd%)U2fGK=RE-#qnV~rRd*e|OAx$5nt zW!7I~s2DNy*8!yQ{8Hd$w38sX%W^CmUmTJ=;g_1DEQ zk?CEi*S7wBf8*XVJtMdo_!)d0KC2+v98#)DV01I-lW0^W{z0pbnH)3;Azn_-Qzz^9 zk|luUkkLs_;dJ~^I-!F2#QeM!!L&sB;+rirZru+KC{>rF_ykS9A8x`RphP-SA3C*B~SWRNqEgV%)DPq_TDH$di7* zLDYKJJI#n^GkESsCKcNEzB$fbURrh{Nip@RX+@Hj353{ZwgMMafX zwr`-oePn9FpA`rlv$L~ThVQyJl;}P|`)iY@>->BNb$ED)Pb(^{Z6%d)y#3|PY_LR! zS;hVDJ;y1KM68sSkD?%WU!q=3ea|2w4XWyo^^2-6`Rn8%MD;r^*ZfV)AWV%a#DXmZ z@G**uxm{4}mm8t72hx-AXz}w^kXWE0gU&8^i-UYUb>Wp|W@>xMTeF zz0Q8*>zc{R$@PVe+}vEDWs5*N+9vE<0$AT&0^-oJJ&TcT9|r2CaeglY%$CqM=zi4r zTA!K24W{>Bj63uYjOUN8*BY3+PW_zSqvVtGgm)Z0WP-tV@pfR9TZT}jKL`imf-t{ zh-UVRiDtlqAyyaz`}1V_{FD|tafZPEL&Lwu7lP0$rkww5jTnUiWv~(;1Z1G&)2C0- z5*^0OCSG^3BlIGKBN@%6vE7JCXbluft?gu~>aqy7rX4U|yt#7N=T8Kc%-uMD5kDcb z7hSVT!Eb+*8^z;FiRlecT`s!TrBQt7Jtue~is7Jv0jsug!MP!eZ-Y9=l~#7PQT0pc zkO5uxJtwYTH~TbYQ`5*ijac6J<&D!k))M85F~oKlHjqRk6poq$f|CTS zsKUd;)>cVGnuJK^0pO8_AwhsBlLA@K<4>J(`1)7;`=^E%$==rS9|Wgu7xmdb?R{hP zr^^Tccq0gaKy@w=^pgw#QZ6v=f{KCEakSShnYHH6X7hfis5ze}-aDZQ4PDVW_^G_m z?Yq2DB)e;)xOfRXG_Gn_LG*)P6Aa!|2SYeXd%qw@y^qIto3MmBr-* z+e?lDkhQyO);ev`{2>ib`s@t68_e?mqDfe9t$ps>4VF&e z5f`Zi11oVzX3Ru*h~jUS4d^7|->SMgo0Xdq6(B=-&!}X{apELkDQ-Z0a^BsJH+0dC zyZtN)L6geXr(2Cf>GKs)ABN21nd+;X)pfLL=1-}Ut)7We#8>Uw8Z7-8l^ds-WT7k% zJw3>1&I{PR3q2ycay^t`(7oH-cmkP(81qE8jt_IsO7z%A$JeEPO<#BMERwcUR{@Zr z2_$#yLA-x24A5cZ-Cb=~Pp2TL)Z0WX$a+3ZsdtRgXPV6xbY&HtxC+lt4`|k7C?3kb zoyt+K6E*mSKfyxpQ03P1QiyHBQpbbvvQ%(D59MR1LKn|(5-;&V#S=>{!n>ye?gF(yj~M^BH_={)8sclPg_+Ga*5*D;wyvNvV2V-cIxmCZ zM%s{~JhUMtpR6z02fHHg=BG&~e%uynLC^H8Fk)I4iG4g*KW%)(UEu{&m$&j&v5&Xe~;<8Daton-)IF_mOV&u{(kDaw9AEzZ$x-^vHA|? z*Y!*`o{2e=!^XY@3--GWVFc=|=x&tTqr)8kN7VM&Lq%wt{84?HSK<%J;xCoGy+8MJ zjkEL~Fm~FKxP#y}DpmKJ@SR4v3%orlDQ-fBAFyV77o>K|AP(j3I793U=nT@*qhw4+ zo^xhe{K4(T+z2E3GO=ZzdH>#rJ&Rub))Q^*;;fTd0sB9HEFQ7PUWrE^=@V0v8J}^z z^MI$pkl>Z80>T91f@&j!c2grLR{PQ6HyorUhHN(}zG=FWSIv#}*clrfA)Su#E(_(i zHi6G@b5b#(GRsG6#>=CYs7AnclAJ<4w+5YRA+5288Uq-_P0g`--{BEd1j_JS9!SAlV^C zzhTh$2+8fb+xc%DoxDC$aHpsd%9dCMfaN3|XHZu7Ioswig}G;%K}&QY|N5XZuwBR0 zy{`Io7ae;x>_#p8QqKMu*eM)!l&%QmEde0aAkItS4p0|m@RXK!sO)N5Z&a*M$(LU! zd>uS<5GnEavg63L6sGtpmJrTzmaWg=~CTph7NV4^mnjXRQ*fY3Xg@R z6A10$!9b2Td*tEr4Xjz0aEQU) z4m^`GXZ@L%_7bjvaTi@b2eO3yKD0dG33RCTDZtw|0zc|!6#J$?p(4lckFSN|L6tWTw%#ih{aLG@r-a^kA95f!_WNgF%jpKQ%IqsE{ zH#vKp5!@$X(8T-_3YnM*aw+Tx6|v3oqgUecR>9rb772o1GV}YZ65k>N!7jO z&z;gHH>+KyGxKj`qGrIVb~an{(fnA}BWm|(q%s_X@-4i_P;tUxGZ%Yixeb_Dbj01Q z#7UzQJ`;5o*irPXL(BRi5eAeDVF&b5DQDr|?0X~bt_pWQBn{_yjQnGjv#>s+S>N}Y zu6u@%w}f-tMEV|UB2&wh+jutjA_3@V2Fw*o-$zti(nx7u8i)`QMBbXR57yyPzIT!O zOrhGGohD750SklS?dat4Q!+E?C~OA=qkTRxAQ1QTMoPl5hsfoWw(c+9S=Y2)v#_{= zuy>ZWXOF4F==uD;vO>T|6YRC=`k9{9Gxz_1(s9pxQQ#2wRSCR!z=!llu4mvkypJfb zOnu!=3ds1?zvvxF+W!SBPcfcGO^zYDUkqWl>94#+7jWvcs@ z|N7(g%QF&)B3S}ZD3{B>mk5U1DU0hR4H0MHsKAE*sAitP7|lg`ed(tO^1Z?>yVhlI z*lh5i-O}6R0x?jcOm+GRoRr%`@=m#Yn$%J*M1TVdzC|&AcBZ#WbgPPf1g~B)14rhn z3xS^qE}Sca6dc8H8L2l9p-}3`bYzY=--;Vt=pBBov}BFkq)(8)*Ns*=pU=wbe_bEK zEqjQgWoJ|S+6CuxY03rO*-6zA9I%1Q3A*=DdK(#saICx)tyCM~Io+?ka=~OfRrnMi ztyJusWH4ONwlpI{Zhh%qgkKU4A2aBkq2vO;50aa!>&9Hy0dp>_0@`E5mzI=_^DR8M zQ4T&+jQTNo#HN(5o;T(%c)?l`sq$E{Xk|K%uJ}(*vY$RL@SIlF{#iaUgfmb&H+wCq zSvkdl|3oALUxhPZ2pGD|K>#RNK>W`Ypbb%8)Baaxf7y#CpR>-x789U!@$U8tAe!7p zg!6fx$vJzyq)GQeGn!0E6YLrMx~E31q^qgmp*DBo-*3ZAoBQ3>*k>&H_bUklvo_h-grXmbxVa_wpKmx9v?1-*Fo(SOfHt$% zmzidKD9Xpz-5w?cN&6W9YI70fMOo)Ic(B+-`84RDp^6Yh`Rbjypq6M=EfbyC`h)|` z8-~Ph=fo~@)oA8LF%OZi5uVKAd_ar-d7PUu0-#$T`zjbiys33$E_!~pG-!E9#6x*e!e!|a?Cwjk?N(_9H-CBk z9{qRy(0og}`(Z>h60q33Q5BJ=1Ljp=kZvuB!X2;VlLp*C;nPMbsxx_0Wf7HN@GBCfo5rSub*Yi|N>QOH>bCj%%EfRuKyQVwaW(8$4pW>BndSk`L`{|UWn zQREdj>0KP+gsogq$oJQIf7c08hJYmzn(sHD+J@b!nd%%f=oK07_;W?3XG9d~dSEJ? zB<^BvfQbzmPv3p}^~b;K_ug>(f@fO#5bQyz9?7Q zYaiYkrg)n8P%tuU8wc!gFz_S%_4=|=1ng@G;?vn1;UY7P0AreKjaB$Gw^3{kjQgt= z9ob+ce^cmY3l97?U zIrj_S-}!yd`JVH~xsK~{U6J=|KA(?yKkl2k^wo8nRk9gl#f%tCewB7=8Cx;*Q*;C? zg1VM+p@8OfV`zFy^w7LZq~1JL-geD8o-e0a8uwjhA1O>g{aVfJqzjlEbQslzgNP#= z248@0v#N|S5IW|?0?&A8Oo6wsyjzL>5&iXO0Irg{We?->gw@k(rJl*U{ii7F?Doh5uJs-DTBkmluQRLALZo= z#60$V5W!j4zEJpm$Z~W6SIPnAH54Pk55M%+UE&tlpvD2ixO;sn4CvEnvC0u@G4^os zDaqAs;W2pH;?-*ayFLLkkZ7~aj$veYPbxI3Ile@kRQubXRorNGsf<2EsKmSNpjR8;J@X}Czx=>SHzo*)_nW+-^O3K>W?N&y!Jrs#H^+~KU* zq8l+$4NR9%mgMD~Bi9Ws*lqt=k32b@e}%K_vr^Ee2T#>>J5B@^Iq>yVv!K^$*i<#o zRJfj!|J&T(innGw9T~zZB8s1O+U%%Us*#;?qN04%@LRkyQPX*qaj6WL2Wx3*zsV3W7Cg9=qo~t~_5^^@#~T;4lw00P_}`ch zeZb!7W@xL;DEAQ!Sfi@^lRG!eFnl4f>1Z>C9L!&7>`U>_MThBEQ_!4i7AFnJ?qcuxqkph3 z=~EETv(lw{9*PjqG*tDM7EW_W#!;A5wRPJ%+|!(C8~!g?kM)<|DTA zh7){zcs8b1UY#Rx1qF_APVvH*PR@sM)@?n{t+vEx9eVrGHq6DNu)_9j&=O$^_37Dx za-IjyPiW+XHY|FnE&b&tQ*qO8Slp&kY|xj{%!FFub|WJrus`nGlCqGvT0JB+|IgCl z0fiHHJ3CVjF~-cP|E0bE`Xp=Ul{IUkp|GEyJYQrFpj#09s6imKsZpXxKEmoKXdb%e zN1XTiTI*p7mKX*E86No?t8QuV!7BmRiQnpC-W($6v9Rx_UQ$GvXSCRt2p>esOh0Zl@ZU3p+{{!1Qgz5y0BsvVVPsk#YXw#JF|ZtKO$Iio%3t&0cia|!^S#IY=$S8hq5wz9ow5GxkW9(s&4+O8!9>Ar>YVQzAOe>FFiKO#me(PXDq#mXT@s+pL zM3;)dr8^>vD6Vou|fH=#mMr9s_%o0Rx@5-DnHRHf@E3u zMt-EsR_Oj)TcyZWB9L6?G89`|7C}aD}D5pEMoxIjb0{~(alq?A?&axq?t2QCZU%v{wkUc4Z5o-xcTD=$y*$Tl=J zy~{C1nS1};Z-$amQojEFCBW;ouN#rh3#)WrCn4$M9^a`Iw#rq0F6JrN>k>O=P$XUd zr2aGa?7+JV8KYb($)lHFI%t#CsKD^Ok zSS8laD80r6N)+ZVuI`mtcQEgJ8nq!_awepRKuabQ&w?}Ri3&mAM&Efd$-yp9aCz^*jUgAHYh6BUprk&c_^OHcs|qwCjkKoC8rjB&sQUQ zwPM*0vQ3*YQBKkao7>0)#T8#7$@1*IFV?YUEW?foIvh$ZJ-A^pOD)x@X+TKq5@JP+ zv?0PgDClsXxS8Wu(E6w4js>{9$Z5U{U|*sA7Ok0{gsunp`^Z7Ajy|v4ljc&P&qFFV4 z%Je{kLM6|ksqTE)5UIhD0fN;RSORDpjr~qbPCiD^LjJA}+y39We5ADbnQk8_1?;!3 zJws|ncYn*Pn&uUHXSx&Dwjd@HDJ=dz#D4H#CeG|2+?GlFn&3(yd7*rbhzT_HX57Gg`79FSF1 zH2U?~m#ZjL=`dQK5R}>AYFOgNYgD-#)9a#OTc|__=o8VvLM-*UvU2?o(4Loo=MI=& zVvl0z|0D780yHn1HhvG3?cshj(0i`DLQ^Yb#a@=4bt5T_d2C0nJ8W=2y_AE5gx-k^p1JR-D z&f>hhz62)+aXTQzv?9hd>lII0AsumFTm&o3EZs{c4`DJQ$XxL(9x=P-UOi-Ce{%XN z2Vxv!n^2}0+&;Lk})QN-eo!BBFi(>7JZxl zxze||o;BPUU4G)LN8~grcvufpYq41w!^=x=6Pi=2XdgjxtN%@Dy9O)EP;51C@?DiNovSRS9M)zhy_aFKA zP#R&S+>dofR)Qbj%!Lbc!P*e{E0dwm#~m^P(OVE;=ed_oSMXiT#}Nay9C+ zyISw?E$G|z6+kAGzQlG6aIyVF4!@JEYyOoh-#Z^f1j68WtK$oDj<-94QsyZ- zx0qEL>%9BFe$u-Bj6k7?A=}y9Ce-qSYHna2*ErdO=Raw+@#<9Z>cmt@AwO!!!6W$6 zbj^kw|3LrUeP-R^^%B#k{ie`fIRf4_Rm}5c3VF%)qTp&D`xwR#1dd#lYsODc76ZBK z9zfmAjr0k{W|?bSATRlsFD?0n!cj#>8=YfH^;w`HMFDiD zE5Kb`N-S3x@u}V|5L2Ux?7jw=IAY22-@l0iUlZ6}sW?PN_@-_m@!bBg;rJlRAaecVFIk{90aQ$WPy7VglKH;&r3wNl6 zJ_{z1iRww%=66DC)e~!$bZwcR@(gbMY37#$*+n!8f2tFcg{9Yab}ny#$NfqUO(=>+4jSCiwSo?E-@ z`ED;)ro7oi|6gZ3hh+$mxD=?P8s}(}y=i>SoadOA@*Ke}%Ss_yhA46;B5{llmt80v z;x2oBG?}!TbSTmbig1*0uaD?*kJ~c0k4tH{_IWT_uyZ-#tlH?*MS-ppc258!Ge289`tRa>NnqmgwARtNTYnGCmpu!^d5_cl`?0` zgV_i|yF+!66e0fDfn*m@i~JH%(_bTQJI4aT$0@Az1n8(2C&>!_=dpcK;a$-Iv9b5R?*TXjb;R6zzYNjz+ zUU%}@WW|bWUBrc}^-inpl)O8Q+mL?YOr22(5&sAs=^O_<4(T2THMq=&4 z5^h(WeW$JB=|bk<7jtnXp|IbkuO}YTDM7{8w=QBZKc8cMczAC!o#4qu?~qQGZK{eQ z!)z2n^d{$TqJ%EV#MS9PT%J!g(6Nz1Hn(AI7l=u}SN*E{td*Xx@8FMwzG%s&QIy<( z=Owb4;#%V7QPu5t1~re^C&ulmg(<7A`H+}Oy*G#}eaiN9cDC{y+9{8}x=i%p&J%sO zwfI}M=2yy+Z)?Fcne5kN9KK;NXn8Lx4}VDBJbm5c)W@}Js3TWTcBbI*1bkBD-b(~; zhXS!YoL-8@&w$El_BIcNLib9L^Vz$RDC`46FYW%fu}2k_g3M3m3mQPO*Wju0e1e-l z6mJ})e|9TzZO>gh%&8$>8f)tvYu~-^juXNs=E&#vuOhkaOWUL6H5;jY))Cp{^lesF1dKaz{3Z!vG5Xc0?!&N1Zd zVl4I2&`ACmN1%i}!;59S~B&HSp#_hUwim0E-u(|uQ4 zvN0UWPH^GOb#W(q=O~1^<^nKH*vEknQlwUzNuUn$ODuKs{6IZhezfUG0sN> zJaQSwqMRj1W`DI`^H+^T09qSym^evd8NQ%Cd=#=pLRap1jMx%6O&$eak2%Ec?l=Bm zSf8%C=Hw3<{_q%O_C9ZQlCLDfDQba*fCOFIO;Q9?Q_C)Y$mFLQn8vGFf`( zgKmm?wMy8I{rwR5&*W$Y6Z$5H#GY&k1=w}*$+V+T+ zwRrer0S%exxww;~CwCkAC>=%*8Sl7XWrE{!UTUlD`|NcV70>Kq*H&xv14Qu8tZMZp zM5b5}b!>10d&Kx>2Nwq5bU&$Pb@=HT^PntNPA1D_&xDS)-~K~-0oW@x0iDdN4Ybv+ z>`q^*-p3=#zYk7-z1iwsI!QTcnMiW*L3d1bVzvjGk9W<&K_uLrw73<#NHAA-2MVR~ z$cblVwy>9B?|LfP@Efa6WM{u*YUw`{;u8lkPWFoEnfV95TB?e*^@%0K-Zb-bOZb2X z1RMwUeQdLZ(qe?}HD!b#daAR;5+-_MYu3O+0Pq_S{?eUN?O=t4=&5ke_ORVeqf&RT{Rc&0#d<%3nQ6gZE~KDBzNe1mzIa zwK}zL8WK@>tdZ@=*>@H#XMtA_Ie9ZynVF0BkF_z`0PTaDG|zRneK7kxN6mV@N}ULt zcD96@21DOVspawf^|m=mGSDfa9po!IxNw(bSqTnBjF}Nab#f9v(hTK~iOD&bW4!I} z?~t3fp)$NavU3Cl5M7%_bzP^)Mlv;ZbzfiK56Iw4kS1zn7*is7?*(hqs_-vVfDIu0 zON>G$CnvutEN;4OJ;#_YRNU!P(+hK6qcSh}TzC7@f_~^za+e(w<_A|z@XzyN&z`be zj*7J74LG{|PxciybUkBkw-?LNISOudSYDTZ)X?YC#PhTWV1qy!Gvwqg&MY4?v*=9r z-x@4d`Rxv(9Z;j<;N-m0Rq9FVh2F-gzK90|s2eG#L4_Y1D;t{tZ8RCXQm6;XxEs0# zzoPw>%*sW~_U(z8s>LL_ho@({ur&46&BN_W*2mvFgoP66?XTtU`STHpRRuoXugKjW z98wnl`^+=`}AlZ4{|7r8y*)CmTE zF3UOS30t&<9lu;~MDDS-_g&%ez`$6rueRNGiHV8vi+=WOM_l*8g9p9u;KyxLRCk4M zW?gEGQJ|ICm$6g6JqltT?a=NRW|E#aXiz9;DlmK05OB=Pd5j8hUQsNp(t?QHk{m0L8N1iExXydg zPt8RmQKJ5D*6^TDO`4DfeiA!QU%qdzyq?cR*2ZB!VKLL{Z`e6xnfKmxT;086>3O13 zvgT}2wz`guZtql4WaT;L#5)t`H%hX{FS%zVrk(1Y$b0N`Q{GSbp(v-$=H+*j9XnDU zH@5C5pP8Ml=v;0RKim4ew)TRYinewTQFbgJ1z4Msj_3W?-xH?2A{Uz)8xwG`qxQtp zA|*D-8gVPw9Ci^l9y<6aTEY3M&Tj_kFg5)S$@kV$ISn)M^P?}V(v4Ev?(_!>&O0_x};t%(KtPSLd`Z(%Vc@P#d`RCeqym>>d!?b8s{TbP1%3C_J|v2 z6bO&XG34lvbQJDkU`WK|n8?}q%1Zg6jzS$^ccY@+l%3Vp)Q+4ysR?3Wzi2L|a(>@SN~IN^ud^Bsk&V)w?PKYskE zrmLIGBxc_>+NL+~@r8<2n_`IG3-_D#KmAOy|0G)ubmciE?mt?@+G{XSemW^(k3R7T zZf$lx(wWvpdDXJ@xWzAFo4zsEtt=ngV-<}kj{j;3P{AEvSYBEbKt<4t(c#9M9eeh~ zfMH>>zh36WalN`IsVDr7Gq)JU9ktG!IpY@%S-HgMXh}GS#FUiAUlslW&_Hv-2!kJk z__9_N$poFT>O5Cj3tsKCjI(apc5JV@utPO zzYV`Sv~JSK6041@Ryx-v2Bv3kmB7)MR1IzI1XouwClvf1`}k-Y0?GUOb(TpDlNhL` z{h~1)(+An-I>=BF3#$;Nd3iaxi>9Ut7J?zHro(NybLd)5l1_H=J2>9pEVCGvPk6)K zTCMlzQn%g);(ToZS{xfS%~k0iY`>S|Kt{5e9Ww$0p~JQahS-D_;t+y%46xyiA~Np*KB#!L`}qsg0~lWpl2 z4Yufwn>UMOWnW4esEc_5tvJRTXV0DuZRHogX;J?i%3*rz)~)lFv9`8WP^!v07Oo;| z-|e5IEa?NirJF6EJGcCRftBDprN$A9-V zB>2OF17{Zr-BLA#26Jem@FQ+{IIF)7U*zqlvqobo^ zY-*{WIkK{{GBDWh-ohvOBIOKPnw1l-Pg9!abo^r6*sSYPMT;|z4OoxZ)R5=oYB0;| zku0;5Vq>NKcJJGl^!V|%p5MPY+1aK2GC`-^GIW=cf&cSYsJ=^~1dh75A1j_@KS-Zd zd#i^IG+MSj*-D(E*5Y#5Fq`#y-7hK3ok^*w8qUr|W8>p&a^>EPs`$53s8A$G?)rRO z7GB>SYK;NKjz(^7Ztw}C$4X(sG5U)Gntst(*~Fs^7Q7KmDA8ZXXTk7Wcc(@yZn!;P z!4EyPYZ)yQQ1a;mB;it)SwLNV{Uo#)bIeuX$noRVqXoQ2g85DT zFy9pg!f|P4rwQNcaIqw49}W1*FnygG`reqPFHvreo_uO_G;3LTc~wctIndgwN=v(S zJDxu6DtMzc8sjEqrKRy$JNA$dA~xkX`?l4y9o}2QLt#rD#U=D_W+ca9?)vXm!!J=2J)RUj5*CnIjul|5d+Jer0=-y|;d-vid6?#{VCGreRARk@DvIkY6-N zPEPu4SUGm4kyp#vt4+0+cghQ>!XvZxn@G$Dg~+U5`QPD9c(ns98FBgUKL!7FYw<}* z09l1&hy42aA&%)EX|P-)5Yjkv=AVUyg*LJM5si`3uKQlEe*ZDAnl#M*uCAdG3&GP$ zvm3>K9&L#sYx9MF-MC>xA3W9A^tA2tEmsY9hIN)tSHDwz=C03cjS=n~U;q9{hCQ;g zv+L^Wehm!`4M&ot>=IbtMz{K{%RKpYDn0IB&$L{gWAy+p;W}6U70dE`_10Ybx5T*K z9R}j284A{iBqStY1OB`yUWlP$676gF4JGRfSFS|m-5ui8*Vji|LKkHcO9ezm)=$YXxh=`9Tem)b z{MgUk-QCaMpY)RHmduw#9|7~G>)+lO!Y23?7Z)Q@$pRWg_4k&xtr=#&5bxK4Cpi{N zGZ8#NdEiYU#0^&do3GP{zcu};JHon66m&llO(TPdd$Ih}lp=rrd;>lLeUO;e)=QMk z;=1rTw=#j=2y9Bxi36I)9Dg+jRZxBqW|z-GxQ@7O$ZWb(?H7swrWiw47S6E%?BD13L;O37-)nwG&B%iGa(^iptHC*;m!uj7uu8QH@*wPO`Lz_ zG!=viK;natAwI&*UDGhTKD#oRp&zCU5Ufo6-JZRBIRymNaRB>~!s+v2+_#dxB>GD4 z*|TSkbkq6u%#5AtZ}$)$vLD;xlwS$5(qpd)P?YdsOq7C~oBQhIK%=)H=sMk4SwuwU z^A?fK)q6a7a!2$PpNaQZY~eUTaEm4LqT{>xU z`s>%PgfN1R@efzIFUh`;js8T4zpwnPtH(kdz&AM94BW5ui}TYrM@PGx-l%MI^&ju8 zQSi&N?mv|9Gn)z~kU`iw{xt~-ZE4|R4xG3iw?+P`gM>R%a+0m{*vVq~ZFB9V+(aeU z{C~7p_JX>)6lEldH%S`SGxJWb5-u(0ku=rIk^q6XpqXV9vsVMc={VgfOZUchaUw%9koL>|HnUEX@3pl3L|-JINi{mr zN*L*_MI&Fwk;yeF=dCmrFF(kHZgdvuX&k*MYyP2g1DQL_;816=zCM!H8`J47%g$op zwu1Al2TQ-sE$h>NPKS{-n`k%@$f-*?w<4E7L&+&5H1jTP<4e+0hL$3ye5hG~g6TLZ zOhgl#CYZ#0hNkH0lHgh(mq?74Gcb6A@f932Z{m0zVcG^oYhfpb){{d|3}q_gvty2^DvUA@Dn zb&NHfl67-c0Ca2w0an_qmQZbQkU9&Z=Rj65KovNT9<9f4?UtBYc07T^#Kh&5bm|$Zq%sO%i(8 zis7Q#5RRzDcGTlL81X1~e0fKHduniSaA44uABT(^JYYcJyoiljeidEcJd{C*NCfDy z+`E1`;%FW3vs!u939m^p z3NN05b$|h3m!PAg<5OZIAK~Dz3RPB6Fn{aw_wTJZb0@&+K0!Z|B7|g2bfEhgPMaGW zhw;Zz)&{>+XMV7m+VU+4xyhH1W4HFf5173=fobDctRp;`a%Ru@6?r~QC&OrF=|I43c9)-j<5g+B*jvNmm z#p2Ei7sjgQAUU9zy96bT1dQOTrXr504JLvJ*Sp0ZDF;s>_15bkTBJwIF6 zx-WuIzH801NkX7zl&*CxUCVl5#!9XZND={zwa?DYak8>X7B5Yv*-Q;;%eX+R5AllM z^U%;_%l14|AcKz2ixXFiMS!c_-qX|5nq&3axH>e!n^8nKY&#`oW2q+%VF~Hoz9ugr zBq0*cJ-c@w5fjrR1d)l@KTgn{nz;#b$x-maMg+i;im!+)1F-ku+v1ax&x5+ac3=ebW_~2&dYm%zT7@5MKHh9j5Miy!$av0Oyyy$9 z&dwsI5YbMEwP0l`nN)|GYPi7Rc}q+WG%7%hy9s3D0w&e_%SWL}{s%O=`Szw(Z+PMD?|_;-TS(472h|x-QLSy%$HpcLmgqH1Qk)E)2Z1cp8Kx#9i{LVdL4bCh z7NJ!l@G$59@qkQDZ|g#Ytcl8f+_id&%P|gql8fp5pcU)Xm5(V zRM>eT2dTqRm|^%q>?CvOptWY0_;~L>6@_Tg3{-b-6bKR98!@Ek(88fR1if%1p!GBDQW30rMuzKsdRVT zXFFfaeEc{yoS3=C`z42(03IOpIy zA4#rO!C!(7cQqW;Y)l-S4WAifpbQ;sEo~eu%^zQPGJa-nZez{O#?QvZa^1|q!PZ`g zo!#m`FJQBIX3EZ}JL?T^f@>?MX^(+HXo&p5OchTt$H2tEke8Nt;1aVG>l{hZ*XOU_ zx7@aqM`h&Z9fu-rCJyuMtrby%iJ!(}+=Ed)JopksXaD|%_c+8E z>mT2dAR?DMtMK>NND#5S#ff}z9p`Uf8dolHVE^MqIV?8}F8u8kI4=w|rK?H*@!mDx zU;8lr{cUhw7+=Cv`{ymS+&Gi`k89zC-~H=`jk!%aEr-OIX?K|=6Sfo+vh&_ z$+UKXMJvDYf$7Fflhx>v%uu;&UYaNgy~1m^QP<76PyH3Em50L_u|eyF%g= zy!mlwNZsUhcJ`3OV4(ovmExCH=tABys|1Z%fugJIMF9)XRF+M9L}QIJ>f>dZ#|>reL!+m*WuF3^Mv)*MbW`+wSIWfOXFYez7<$4-~82+ zLYS78_Qceb+j5X&rF>IyXBmBUdzJJ}(*1~y!|~HN?skEf2~z&58XB+Rff*S5C+qy} zH{1C0;6`MMCb!*OVF?A+e~>WVzFocSr1s#!kF=Dy=BktJY`&r0O3%Z+s?$SpMe$>Y zbA;3iUS48s5pM$nFCOeHw`~3HaXs0eN6o)zKRG^ZYHj5Su1Sga8ZM_nA)A`vOONcf zWbM?tOMZSn4}K>`+iwSp+1c4-A#|Y?clcsF9$WEsOKn1tHJ`NhmxN-2dZVu!lTpzM z%VgqS9=(fVr$?K~j`OXbdQ6rBe;jNt7UUW=ygFXN_hc(ytBqW#a$X%vUgnSJbadZc z8O=amN#a<=&COjfpzmEVwA}M%*Unn0xw$#NwpKDRTS;vHtNDI+(*4APwle3{tW2!} zrYSLqstm{9-AOf$R(#P;uxBzlMQPKO1~o6v9nS3@7NloamUeA#ZfxW$i67_xtkRc} zkqNCrSy+7A>Auf?SI4^}PIUP7B|36l?}gqpEn{P2h27&J)A+lNI{t(-SyUn}9G1su z>$0{~WQ*G7Hw*Uok;L$Ixk3FWuijM`>#)@ak{NmIx>c~~l@C6c&+8Dw(`HxI^jwXZ z4iOiV$z0N4(fsaviB86s%KzxdLs4X1I$0^c-L8R3*4jENw{>;5$etM;0s+WvKc`^Q z9@DhmKof#q<_mxL;DPN*$^3Wg(b6kcWlHg4^@XPJ;{<EM*Oi zMs~0Dx91j1b=ZQ%4$NR1WU9Q568aGB$U9GMPxSNWS|g2;b{F{;Ta zDV@L5!$a*dff?s@@LL8Q6%}<)OG~TQ^Kd)cyDd~n%v|f#mqgLv$LmWnns#=aJ;^Ae zmT*=Tn<82Q(Jf`Th{>?n9TW;bLgyLoxc6yA+Q|H--LQE|?&F^q5;JVZD`VUi(nv2~ zCNqYep^ngX(p1>Z42_Fx?@W;T1b4#_=W-)f$dQXxzvS61`?*$J?bUE?Yfek+zHbkY zmTkPB=6fP#$v|@|^Yfnq)hV>#E;j19JDNP35QpN6Zi^f*bxc=D$;xV1)aiOLP0-sfl)6D7Oo1Gr7dZQNg|GWv354o1h!v)EUQcg}zktw@J`D2#TDr*Axwztl6uK!%?0#=t7h` ztapA?6uFu!3Khf$LDf_0PvhnCqp~BCvo4kUN#i>+Z!V+<I}ztj@JuCHipoV4!Qo2v3PIXS8@@96;BTs@5ikh&Au6PeWGX!Alflh3rP`8rJuwL!x)6SZyk{uP`z)%6Jql zEm?}~&xFbh43#=EvqiLM%nurc1Zlu3WO4sob)S!Q{$kN%2wqFlE-)RK zqY=gz9mHu=zqZw*6kXmSDQG)^K`6RK)IjANvt9-TiqoPuRlVVz$Ki6(Cl13inwpwW zVeOCB8#WIXvx{8ZySN~g+eJ1N)HKa3f6Cdh@>>o6xD}xz31!GmC|2iL(=Gh|pdSI3 znTrn=(gmkp(>1oW{eoPc;W+*_MWc2pGIexT=l?8t+9 zTbxZOw&#=AF7(#x_~3n9oOK4j!!Kp1dXgt={^H7ddSe;mOS2LBa}zZ$>v!?k%Q-UI zKTEvSsPYmW&~>H~6cm&xX)~FQb6-i24WUjxNYKl^eED+nwcy{se~&zCVXfb-d3kNh>V150h*US&`I_N{r(YpY9^``L`#^dYCBOUd;W3kvygaTjA^C<|#l#D|!2N=!0~=kkGDTF&CD_tnt3K<=shIk zH)cwXchIOqm+2t>{H3KO8KWF3$6l4;mC>@g;a#ZApC0etJ-A3IpnN##PouENJNJCQ zp28;bU?l1ORV#?O`i*)Kjt=2fk)H3DnbjkAv?1dzlafY?5G4jt3?#}D_7rB9%tfX4 zzx^Rgl*ZypdWAsL~$FBr`@{u{#qLJ=o>PWcPqA|DhG-Q7QjkiNa zp>5W+i+V<*T!#-l#FnF;W|?pCpRE;{o@{Uk}ppBs$^(^y-uJKxsro_219Ut!UFR(%<>roOPo%vK~Sa%L-0Y6r- z1di6~1h;$D1ebE^0>9IEAH7dgONkQ6C7;?J(4Wu9Yv&RXbKhBNf+|>_s*)I`bCtt2 z9J4i6cwo!(*wW121WdyE%}a%>V-Dr)=a|ij)@j(p8c8H4dyAaCIPa8 zncDpHN^zC}<{A$l{=9ot_Xi-UFJn8%`$AS4Gc69~F@!QGC8wso9zR}jX0@=l#|gTH z6FG&`Kkt2dNCW+S3*r~!8XzvW-3*d23E76^mQ8Sy?nu6Hg%w?WJ9fZ!nGHc^N? z|0KV+zkg$YKAvJ+%4kfc1#q2afyKx5QIkAQyD8~uchBsqPA|R({oTb$+i5f{@XOvj zp88c@o`XW$i}~l`I~t&bn=%Pc`jQ0h<5TcOa(T?p&ic6u^`Bbt*^E(MG0MMnNMH;V z>*#1++!U&EjBPEh!}4(74CgUah8VO>mFQF{l#=AVoWFMc=8eBlz9eyHC&z~J`)4D? zb`Gm!qeRvHS-LIHvCgj@9zzGaDkEApYE7=?3FVXGaYE1UCtY9evgnqEK_0wCwid}% z$E)mmt$?@0F|NqMz*?$}?5c z&|Dp>K#hwZ{G#i5H{aO-7&^#pcig+mT;mv4d??2dYqjcBO#Ebz?vb8rQf}+~=6bsR zG1E7`GeVo)18-W~5Kv_kK#)e-Jbyd)f~aOcmiIuU~2;&U&V zl*tx0XC0Cqo=bmi2W^w*x@m&s28;K0-y_XRkCLvU&V*kbqPvuE6O1;M`}9zqO#nw* zj+K8hjdP{{VmnOqv_FFr_b{Q>o2R$8*R}@xYNVt{jPsZ)vSRhS2U6d;xwvWz)v8!} zO|J+Ny3`8pb2iCjL>Vi4u_$>#C@}~dP@a4N(m==HL zz#Nw8`k?8es^iS{W61y6VBr-GSM>$GkMM0H_+u7T4_PQPUg?P<%mb`Z{GQew{)gTU z0DY+V(Ig>!d2=*NRxnHaOopk6-m5AeflV?c=;b-668x_CeIeL;{n|EmFyF{7O*@Z! zHeg@X@#&bydJxkN`IfEu_+5Ku(U^q`?ZZcpHWA1H_{guh`QDhvCMt0ZN`#D|pWPt~2jtBl&IOCdqc-N_jTpVjG*A6r+V5^LTGb4mza>$<~j$ zdwN_ao}Z5jyfsXz=Q4>6fBeox5MJZ(fe_>`_UQa9ada?H#phbnA9DWM8~$;R9)U*~ z^a_#HPz#=Zo3<5*6tquX_xu@f*>beBZ!Zo|uITQFk(Mb;kIAb@TF}V`e}%g8zRm-FMzaL<}r>;v#cjIniIk z{RbbT5Ya1Tqru~==X-Njzkla4O0_Ps9=+Jn0y8M5&6vm?SF?Vlvm`^#|W6>K9EIawXA%@9& zYoYHgq!q66i^jRO=x9=o-PLiMjXC?W(Tn6fjSuD_XKfrPa-U57cmsnc-V+lOK8<;R zqakjMF1KMy=kcV0fi-loSNs&lrAym_i%w-F^KtGMZ3b`M50CsnVhjVi^@u=L`Nlo3 zoxJ$Fedlp@9a`JlgDonS(M8;j3lG$@^{m2BF#_))F1TCOl)McSNEpMUj-|D8NvpP` z?}dmRq}t*4}nHiJ3O-?CRmW>+3CO&!24b}pv< zY4vBge07jH{)5lRh)xet4Qw0?dFDo`j;XiFm}We7hD?L%t1NL@n{JPdI0B472#M6J zEbH}3>xyl4BQMD5a-_>mPQN^dZ_#hNpjYAM_p{dh^mrFF9wIP>Q-@cOkWg(k`}+#J z+wMwR>nH9{kk$YquRsA83=!GDfeB(BHa5YuBQ7XwJX5>K$-=w^N7U4&>exx_WY4Hw z{L}+})v8%UA7CtWtTrg;`_nY1*S2>S@eC8#vB@8AFZ2ac3HRUBi-UMCKRr3Dx7}A> z@Ha@MX}KI0i5?WntTD-3j~+jI<+#|t4!LXxHQ0X4b>0rv7AnbjWR}&P-gRp_6)ml1 z7n?9bcFJ31_7Pj_C|3}6t8m`~47HQp9NoQDu22RCbIN#i3 zt>!$v-RWX>m9=tfrudRxIXlp2zS2_vVz!7E8frY2avK8ol~uk&3zw06|B?C8cY~TU zJ#Gn(i*GrA{E_L&ml2228SAtCd^>&aO=02a;o)JKfuNc9srG=+qlrUUG;)06kC#kY zuW)t<&QpfE>{MeBMt;!Nah?5`Tq#=z5&87sWGS!XyJ6ic6RSk1B=jNDAq^zqjbFch z{lU{aWRlmFq7EEW9-hjRgQwQTljlyLUh@oA_4YnE*{wSLG`tCbjoYX`FqP}1zu~vTv*Yan zitz{*&Bt5Jyu2S_?ed4vM}65|ccJ(Pt-|o85F^0JVvaHzTy|0voDIuaUZ{#5U!6y~ zsIiRLLTX|Zr5FLz+_Wz)iGs27sAI(YiKNofC_(!<=}~oNZqEaU(7h7dNlApPsbePV zE!mxmwjrNt2kJ`UaW^mw`%uiO3zuQ$AM@PRZ5LW(302;MbjW?uL@Xt8|Nea==wLDK zD<#Q>9r$k)-U|R!R~Yk1(EGT(KQDfY&R@Orx?e6&HCMi z1q+xHRi+Q4c%LdrT0!#x%wp2(X%+w_KG$V^ilfU8D4W(8!Ja4MRR?|9QOA!l!)|Mj zGj9hlXH6^@jR*hwNPh2FT8~itD94Z+hIEmWz3F6_bG%$zcRYdDMZmH@er9%h`ZTmO zZolXp^s?a%4>JmfgWXm3KU|ySR07hPUc4h+8mrL8sugo}b&VQdCU%=8lnZ9O705sA}ujs z<6c(*3jAb#dN5y$$8P!Cu(NV+3a@81!5d0jCMs6wAu`7l0D&W7>H2GR2au${Ribv0 z^)M`X0T2YAnwOo*c3^yu9PTW0wo!{!zQU%HI%LV$vjHX79LAY`Af2w{jyiNW(39(u#PPyplX@ZJ++<4^r$Tu)w` zyWR%e6Wf7u%jI&OIhW_SGWuy5)J&MAanpN7jx0gle=n`wj=f>Puc{3Nc-Tu5q zz86%a0yQPkJ^}wNsD?2lJ)Vn;bF;JN2+0HFREjy2wa!w9-^5OFah^Lvmk#xGbS#DV zP1>URrp8r}#y92nm+rDM++}rAP7v0X zJG0DovNp&6=#?0I<=&TEJ*hLv$>zhr%N79P5*;4@teH{E$|^J2yp5#Bx@@^H#|fEa z+V=YDG%MU3BO8YY8N|i)4*_bS(0ec@B2X9?^ESVsy#f*A>K!cb53Q6LQW7Sy!~%)zLFI(fzit@&nxtR zol-qZhfLkH<^{G&ybb$4MsAJi2Vsp z$sagz>HXvEyZ4&yfgF*cd^VzdCLZu;D2>H`YL|9*JY;54oRaI4gja3MfFeuJsm90zx_?dcv$M*VL z{QmyF2eifH$q&dx#%{e(Zoj zu!RVF9}(dXVvne3Y@Db&7mVB1C9_w?yiYxyRz}FeQ=fEymCw*F3P$b^6p0V;>Ym?7 zM~1#=i?%Atbz0U!6bh4~Rbb#I0Yc0GSY)81dkM-3LaswwY(Ofc`u6BO0ZM{6j}3WH zd}=c^^N^z2*xXz@`>dY(Xe3U50Zewu9z5O&1ta5<1#bl71DiWgrbr{9i&n3KrRrLwXQ`^i6L0pD6|mi)!-FbNij7 ze$0l?Y0`SFAI3l!HtK-;lZWCA{3?QpL7(vfTo?d5bbannbfb~31SSF?C@unf37FyC z`}Z|~r1v2XYp&{h)Bq8A2L{R3T`E@C9z?PL)+Yd$gub)H-gH_-2ujHw(kc*Q@Ji_S z0+GX|JfKISq38Diuh!k&ZCj$_u+aMk7Lwy>KMTUx0uZBm_UzdWYq~8DCguc#`Z zZzKHR@^e(r2bR7hB))JYxiu=>3gksRpp=&Y`kxxSA%QcG1O*TYXFda;(-zIo9~mY~ zi-sd^ynYx^q<$tnZaVoz~YkYu$?i% zYie#j(@Pi=8%s6c|KnWtKuhySW->7k0mYOU@)txlKj^V*qF!5Fcu_zUO?q~b)`=0P zzqXlAQ(avK-WxwQlQyGo;jAPLUtDZ#?1M8VGBW3ehK9n06R;ELZt%g2r7hKnGW-U= zUe_SZy)Th-<&8lo%Fi?(B#i?hobVeZn)=1)*0$R5B0xhu%n=mySu&FnMa z52yaIf!JXDVy3T3?5pBeu4&GjEwquY@6ZES4~bXNP% z7M+#&W$@aE%;?BV9NJ{!HwXdH?CBqxtb#rs8&DS(@=Rp}kXS5uzj0L_f zfZ^|A`*Oe&S{qt?WBG4sX@;QGA#}pl)|NnF&c1Kl1;EA$4<0>2cqtHn?^{?{lt=d% zcJkoIcR;N~_79J?5Vl0pQk5vfe=zB~1|Bo|>l4}#ZYTH0C;47g;;^7Bulv|+sc>QD zSOsyI2=jlJs}x0_+)STO*4Nj!ZVf?==^;il?saG-c?*lgH`r$|8QvAy5$eYgup=L8 z=vi+Wh(Wi3k{Fed!E)ik1yGjGLH~J~)(-8Z4#03@dwab}o{Fj}abYaXQO`iJ4vmdP zSzEJ#nn;GIB0_KlR-jKsKuO<%!Fl{-r^srE_iqUR%dF*-bhh>G+bf*zJC-2sF~e1* zKq`#nF(>}`@uN)aw{J{G#^u!%`(HPvm*zuMcGW#33YHE@pO1K@La`tvepmbnvXz!+gcpRet6iIcIwXiAmwKjT@FlB)b2~1$k^1} z(()U6JHW)Lh^nI`JFmNCo)s0W%RNaEdd<*kFnn5OzX0u}14P@1>wK(0Z2LL%cbHbV zxVg2DDDv}lPO050v1DX64y=DEru5(tQJs0dBLvb*n*?8NsV z>pUZYm9vpmk!n075rIG5V+xW2r6!k{uS!(eN(bBG4w_$f8C6TREqwZyv) z!vY)R4|;PCzA8!WM*s4>S3iBzb3wqfn}@ZPKC?UJz|#!pK5pbTBP%QRX8=qp*?BJO zkDuAwd<|8swJzEOKG7aHI^+kiXa1nsFCf?l5$30+9wUQl;UVx(_Q0C>f6Ue? z`2ZLK1K3AoY4oxqAnvBm!lo6ET0=@IFx=1zNSD-Oh z9`9%a<|C+vFllm3VupokI(8F`1KZd1ugNtpMp;VnNhi-+_G z9M2c@d?r8%))tjVj~Yfw>`V6Nq5+QEy8!G(+BrBki~)!uQI9Z6Dl`nJo;4SdJ&#J6 z!v|_=J!bKWV*5|x+!h!q3C<%ND57shCEK;I7Wr;BO|MTll|hra!ODss(qMFn?i;tgbrz)s+ahZwy0x^0@I}jv>-@gDCjPXF=<@ zNXF$0Xzem>^4n~*$KQ4)EfkJG+jZwF;G#M zA7$|zpOf+@0IfIAa)|5xt~rQB8Q?QXJNS2~Kn?XzHqX#0;WGcv_j(}*>*zz1{uOTN zN`SxU%M@OT-I})hAm$h&M&-3PNgthmFMi>v4!&Ve)HCbcOeIGIRDU_yBihw+OSDL&w;5INrJso&sz+K-^!ToC`j zq(od;B}W|z9PSK2I+-YEU~C(v4S~elT1H0zZ}CvGCr4$Ji@i9?CdW#cI&uFZ9NV16a?l=`B3_G(Dl1OoyCAjyAjB@z=ST~ z8VTUJ#efZ)1^ICvyf{f;zxpCNQ8|q9BcT2+4d%WK3nMk60aFs9vm61ZOt`oh&Z>P) z!1j8cX~$e{12x_uzJn5Z#Sx?-OyYt_O#-`#9Xy6DgxIxhZaf)-tDW<&^xu)UX@QxXk)3@W1W=yv5OUrCM41Jsd~LoD-l7`b zitr9--auIkBO(qcEf+x{fXs@7VfC_4hxlm>LWhB!19@PR*2o%|`xOBAfMub?etrY4 zm}7moHRt$QXW$%diozty0TL7pV%=l6CF+%VK6Yz2`c53ua(DPs{iUP4aQ!ZjaMB)E5cI!MCK0ItP=1IGmL6|4donR!{1oG%rf!g>kP$!ZwOR!gL5d$S} z+7`uI?`H`<9EDh+kEe%Kr_(mxhZGQi)8G-9gaL3C7%o#_`*pmJw~-*Hv~T646mfY6 zQw)oxe!@6i?5dmV*UGz01MKRVtOM+=UE#78_w8HIWlGQ~fZaxXEveqSbKxyeR-SLA zCGhb*SlQg)11_@8lKcH(uQJl!&i1c{4lEi&s9!o|haSkv7$GJfPtFt~8&96s0>NZ7 z+YQkaz1>uXM<5bJ$No&C#tgl(?Y0jOc4PQSd5D^nXKKhT?AE7QCG~QZFxrKfWNL%= z1$YpYG29B^Ffb&V^+L>qqy?YoX7^k|d^R9H(!oz5nt`Bbf_Xm;xIAzpp6Mkz1`qJhv_xH3VaaF|R=pXa_m54PL$v9BV76!LGnD1Rf*yuS5_IGW4tBpuUjJ zBBcVE2SGi04B>JK9T^^854fQLA>wc%k!`4O+vXCHUd)3M|2;1c)v$vIoiN$vu6wRe z{iL+}aR~uMF)mYYM!?I00ld&_D57g%=!`n65DOa3YeYi;uLT0X@3>+r#R?Uq#iPL^ zho}`|dlOh$6+2pqz*xNmnx&m|;qyr)kiNCU1y6&9j-mN(}V-*venzjwgLV{)O}Fx&f$|kaZyEh z1<;>!fNTcOrfjxe#U6mqv~S<0W8jcc1)>Os{p9F(ZJdQFaf6mB8-oKMqIx^ z7cB5a0uWiWO(kNNqQ4{%_Ap(29kPC7qlKNqI4XG(#^Zc*5-1~F74EyqpwTFN;_?F% zlPy5E&^YR2LApOP_@7B!l0v0K4&`aQZsm`i6Xqib6N8@X>}5n_{{H>@V1@P@7sR0T zI1G#+dG5Q`;GAT@0B%MYe)_8~{VGt(j~n07B3A%4_XR?sl$Hu*mCTWYvyW2hi4gR@ zV$iWlmcF+XgY5vALtgK_IvN)!FX&_=KJ6cdBluG**`a zBp~304I#k5c5t=rp~p`U8xHwpI`Fu*Lr2~N@u2;yd?>QhkW$X%8RE7RckbQ4KUCpf zH0cLAK$8z9))%LT)_6z{2Tkt{dN~;g1w*T@P$^ztYZ81F6_pxbz=~H&7i+^ow8H~S z3|vd2*p_y4zGEKvm|0jPBQR(s7k`&L>XgFcxg2nZ$am-NKS%&G>@nR1EL#qasDceq z+p|+rLT{s%gFap4BNG!44Hf~vU|4uKmtpPMfPjF&4n!^Ob%mt52CT#*9Xo6c#Ek%U zyd&^?axau0ZM1;RBofB2_iBoQeh5toZK7TyE;O_bG!rB!K$M>WDFxx5XPcR`EvwqK zhyeW{5*T=k;Pw;D<#xat=>m>QjqguzfvY?_0lEt0p&uxkT!_6Q1?m(=;5E({U_*%m z2FSM$_wp}<;e(xVfl&-qmr5}Ov1kedo(Q<2V;s8W>rZa1L&2krXt}H+o!Rk@Rtj1I zyMi&$fY?A!1zamKgebB^7X|^BKxVA(x&1Ko5c8HY0pJag1q$TksDK4U7ulF1l|CW_ zt`4=#_jm>C+(ix%;aEim#L854ylk@%xEZn4GxDVo=>rUh7WI_F%eCwv;}M-J1Ave(HhyH%+pyKYJ&P9KFjOS-N!H3rCtk1~rFsf2pvG#;DB z-0gH#Ec+qU$rA*g0J~Ag0T>rd1Ed7Kj$Dwy7oiTJH83$YMqs}!`1*jZ5(KmW%+4$j zbk~7;MI>x!Cz~K|J_En=GoWFS%OJUR0$#QasMntYO+mpzR8n9hCme)=GG^W*nsxDP zxV8(-9(7zH11T_19sx-=4>Qg@m@5%0CxU;WV{HJ$#H^XfMFe{2Xme2IXW(ik&=`*3 z3Ui1z@`qJC>B92Zk==W>RZV zv=O=&IfwwFmLecNaPv$;KbYz8KH&zzn-7czPrz|C14f~hvQ=aWphyoV9ZUA?9eeGp zjw^xT_r^J?D`#oN{>iCjUbhJkaQ!WcgT|sgEEU5wmrdKh@=L18AoR`9La=Wh&c^D~ zB7;n5sEA^S6bj&;6Fm?}6%k?INb4W@%1a#72&CtU0NYZ(b_}(%;kEuS)DT3g0+t2_ z3&i^~@ruIwIzK=Em##l9E#P90K#iY({IJf6g{lVvUno>yz_ndZs*qkd*Ad@=oHBqF zYzIgO%BI>NBo$)ElBKje`?>teDOkzZVGTlIEn>ja7J;zQkI&F3YZfA+sxrVl6K;c>n%Ak=-T4)(_X@IN56uuP)9Wq&7viLb0W z@jBvL7pat}%bZoHk-l-(feH#BnCFnGj5u3G&H{iq>=*9jB~~0N+<)+NwC8%Q)OuQ* zGOuui*3jRrCcOx+H8(e3x0VS7H<}>ue7;UKleQdS5_jR3BJy?nXE<_JQxI{)ifUD) zJ;{-mpQ5{F7WE43Jxmnk*Kw>u##c=N^5RmNX%c<7^gq}AMID(HmpS%;Yw#;hq?PoS z03YfQ2833W`x4jjMv?2N2}hFa#y{5wL-bs-+F1o6Ozt^=HW=RkhKvwPyrwG6iN)bm z{qL&KCUhMs7fH1>RAX_Iy}K64SwCs}E;_meFbO7{b5M%Bo(4>+w)We)Nx4WqygxSz z`}j2_W!jdyo@_s?x$e38k=^z-w>c=h_zZFtCmMWAB>d>A7^nFe{~ ze*0S|IMWjvA0INx*1iFvzz;s)j9;TJyx1lxBlT7P(op4a<$30Iw=O&|Ds;k$^-D%Z zAP73pSDU~*q|q?H33YOyot4CQaN4PiEkz+*vHTb#M+v(9LzFXv; z_&>1nP<8^8xR<#*S9cL&1E^f)#~-h2VEmsvwWKgZ*0E?fg*WeQF3 zmiAwd3$9B^(cC8-=zRM3L#L}}-uspD;Ke%yB${|H{j*?6Q2c-$`S-&D8uo3!cMGS<_y6{^`4Sgf zAx;11iD<{n94AJT=5FDY;QsX^+OGAL7oNM=HctQ6B;-WOg)#AMpVQ?Usn?UktFZj* zYM`Y;{HzJzg^J=qWf`4qrdHb<-c&pliTchqLJh3@ipAg2^3A zRkJgzY^j`m(#sd9cXvd0*`K5P64U|qVgb;#f!nOo!5UV zr59}`gte*B__W(!Kdp4Ke$eoDDAZyyF?!i!zuYD`D*Ti^$CBnjyMKF;Pu^{@Ws+gS zIxOxTTo2+=q;$e!`AXlkx$*>ceid_2Odk5j^V$*%J!{*)DiiTbIre125gWD^LH(6g zp))cU6`Jno(U3{9A#wNSbsmnYEQTYkpWef8A<6&zl3%%Ir>WqK9!X_ucv^B)f29@i zloZ9!ztZp`AUL2XQU8e#6_q>|fz?rxDkq2Qf3HB6^apQ$FR;Hfj$Oep)$e5L-JKGb z&)5w1G0lq_Ry8Ue`YSH}u9YRoE1a1Va}^#}{BOzcnq2BG!`m4hcxKm?cgf)0>iNxF%c1YSgiA~~O|a}l zmlMv=^G>h_YpV%e_^%@8AXm1vqRPpv&14W>1w(JcoiSABv?p&yc@OKik+_t~UCpdl zF?db>&Zf3w?Sho6TgK-O(YfRKO+i$$F332&z`c-mDHBSdM zDplR5-{xM_kS+RGA*RAz%`(tw#tKRO?r9%Ilir=jX{&GQpV8CSLP=J$zmUXfUTDA> z5U-wqx#Np7P?r7f9p?7G%(KLoJ@;G|QVo(N|DA!u=XG6%MTnWsP=|fA;n#Oz^43N5 zF! zU~*fL7DJ_pg;pB$-vp93k9hxK>sPJXYSQ+18Faz~Ze!FX-N!U=AN`*uTVn3MbM}k6 zipec#cjbAWuuK2h7FF4^;+)sS;x6);Gh!m-mI;vFVBt|wR<4GVgM08D1xFAkfLrDR z&X6AL+(40iH|?NSi$w+?t6?5+R)JS?0=(NlL3vnU(J6ih763RQR0~rh7_arTo!MzY z7Wg9y(n96H|6-2sVzBaBKU#?Bzp-#LR#)a;_cV*@nNYg(`Q#77?Ji9Cdpb+DEhLj1 zKJcU}PRWz#Cwss6HCVkTDk(FhfQ(QpIzd#$T(OFI?4jE3JHDriU(jFwzm+~P7{5nO zG7RXs2Z11%Yd^2pE!CHw2kse6SDUo`GjXDFGQ zGhzUba>ihPW45=i&#qfuqK+Dl;sU|<7zQ>7%U3_&UbX*mN%qgI(+;eC2^`hi2l@i> zCx9c0&q^xW9(IanF#LZ6P$QSpQR@clqUqhk^}}Ns-3mCfn&4OL&i`P=RshI3VYG3Ss;sOmO{wskpTN=V#O>;Na_in8ahdKqZ0ZMllN`JX|CKoYhf^U*Jgmlv9~zq2;GEd=Qvxr`Okj?jtt_j}Aal z5IUN{F&Vf4%>65Tih581hl=eIRS?z(hSYTzkqnL8+F~+=EiwFm3x@8Ubn<`g(DuqG z1wb9d>B_E5T!M&tQ~fE53#gO1QQg5ZM>3~x0!&xeB66QL5L%)ySsK-DF-ioh!6|4^ zgX&L>xwihTxyY{=f=0uzxDCh66dycz5V^#4>2T(IP_p-d+%sJX!sfPz11fVAn0Ho> z5}UesZnX|g90sNJ?uSfuN{KbhI;a%5Y<=o?AJS5m;8209cOV-)l-Xw zY^!nBS9kI%=C}w3vv{`|$4C86ekU~6^36?TS0+)Fs z8fF9vwBse)D;ydKFSfb8+jb`~?(DP=obILDF3B-k9CZH3>D}qY8hh@zt2bpVtwSyB z!jrh#0~&9OP%(TOG0N&Eq3R_oey@ToFGgQsda3mq7`P~?k|BulMJ?K!Q;ZZK5P5pH zt`pkA5j*6x8@21qCB#2bXgTyaz*H0LEI^MSzCKtMW8idjfN_Qs!c;P`z~@Fl6-KNx zD%F8A&w&zB0`27vc-josi?A?f@V|h%HL7Z~QSQAdECIebqs@qk z)e7>e#dkjz{wQXl|9Y)FB;1>!l;P#UdvOwZCAO61SMjg%$r9}COfPOd%~veKK73Gg ziI3n;T~M|+=io?9;nh>B`LX+*wo{8`m;K9>KMq)*?+6iaihYGj$GEe2a8Ya^=MF=i zC`X!ZkUiR#NBdl%MA9B_bU}z(HI|z2n!rv#1m;?bQoY{VJ17wD2I{P}C7U-rL?b2| zuTfbVjXEv4w>Ri*CgsMlpEBl?-nuTcQSD$Ucu{-Q?bnV_WguCTsS=7Z1=uGrb}E>g zrzK?Ht^Gh9IiO>Yk8nxINj6%&GjNs!KAqt?JlKAvzA4hqFb|k(X5YMzw#|GC@Lxj zCp7Y_SLGIJC;dk|vRM@~kCKs>mzR#Vv_?}fMNEf%_S~>kml&~|RG=Z)spfh_n95qS zGX7@NRb$YJWi*9;*eq%Kt2sG1bPNkWHF{d4A_efw;w~h`Wki3HnqB_|dL~d*viU8( zzd{SI2GB@HC|F{LNNy9~_Qv)%74%&ZeplTPE<~EbJUX(oMc2z!F2Jn!qP^(bMsJ+* zKC#*5i6y)-)L^&FlmbQRSUQ2W1pvav{_R1It#@ot9&+Hk9<^Uz22F~;?XOQas0k`fVi1Sd**{8V4}u7 z+rIp=>Y*_@<<7d1@cJCRQEyZoIs@kkjgmMuCB8dNVYqLRJPW-+JD5J<#K#*X z*FkuO7SIN&Ly+AGP)<5dL&hTxJt%~zoo$J*|D6=U<+P*$ikcdHV99gmh-P}dyfZuFiOox{@0?!}PpURx5Ug20FJ-OS zjw0qLJH=WOR4$^8v@4&{TwBI^q~BO_O{jy@l->qMRM@fYL;a$r-!~;pd>t$Zmxt;H zsv_FGLK`L$@w4w-)%UoxU+)dhVm8KN7qV>YZc2~EIbWqbN{s3d;Vra6NwR>K?f)uI zfUbj_jYbYffjW_xlk*Og(mD-58!lj(hj|*#H-#f!-M4I|uYnz{PVIrukwJ{Jhye|0 zU?66=gB4j2bhDAH#-{ zd2?C{OMLuTK}<@-EUu!4QhUK5eT4&aiR_)diUExh6X)VY;(~h$x~7k0WA&|KwE|UU zGB57bbIr?pv0U^LHAWVdN4#qTeC5F(?XEDgYn(ne(3~%;9>UA#+7>nDc@pzQ+U60> z!#Vc1|Q8z&J#a(F122;AqOIOc6K8Hy{xY znZ*Xb0{0RtE9>J7Q3;}9nq2uBU+0JeGxFXn0@C4^{B7+wE@P2A!EvSd1EFuwT79?H zF4qR0@t)+c@fb^ERMuRP0!AjK&^VrEN*b5xr3t@)QtV^UXPUj6j6Jci=)KMRAl<>aC>{F6jD{Pw17 z1+MW~YP`f$$CfbD2cn0h^ig%V%ICCBCQ28MUyRB}`7Q>9B!9*o;(Ge+$+V>G+Tc&$ z6lk)v@+8YS{l4BXT;d`fEn_owS<_=)HbXc8RwZ$jkB_`4*D5bwq)`%-d=rWP{@LxX zL0I{polR4;quB419=u58RzB~ZmAm6uSH`f{E$Vq@aOs_A7Mv`oYxGR285ect+j7yz zXJ+?M|9Dv}9VTi5vgeyW^Jt5`%u-(j@IU-?_>S+C{m+vivnEiupid{~?}98%h-?Y9 zeah{bSL|Eo7;VD;@d#H{%Gzt>PI3+}Y`(oMAxBJH&qkN<@Qfa>O$R6YeG0t72Ok6L z^Rm|WBEW1QBw*9=e1tiA9ALC6)|h8f2d~nS#p+<$L%cp7<7)zCsryTKz4=qDgYIPo z*n_Xu&VK(UTqZFY|L_@u?#!zRkA>F;BOS_w3Tmk@?nown3mHDDx}IRg<@2w5hTOvS zl*IePa7K1koS~%U?@r*CYya~3eDdk%X6qr+57J-m{vkHxu0^*-V~>v4ZsGL12Jhc} z@bvv+slg@W_9um}MdmVxG$=2ny>p6*%03Vf!c^NWw%@_jPG-6vj}b?sHD{MXNN2;g zOy$n+uve_Opgfy-FSdCs_VvKG;p#OzPZt-X;=^?F)bq(JVV#G}*C+6YW+w+vu1f#= zZef&qC+FhKU)~yrRTy}uf=b2m{s%djuktC{Z=^;M`ih7Qcek>C(R!;hfSs_t7tq)H zo-oULvV~hwxu^Lyw!-MN^`b^6(*w<)(QUiMJ$}mWDF&L`8^8Ri-QOmnl`=X>sFLCh z*aj*%NG^|JakG3fQE}mO9l+qtL|@d>&Cy%H$w@MDnKq4~M4!I6`BPQi;}7d+cIJ4F z$Jk{LKe#RV)q8g@<+{dEEQ)b;(xy$M*jp*3DjhP80-G0q^ZXG{reLQ^o4_{H|3huV)(R(Gl$WQjNyPfws0 zJiC+ryfjlHM8RkHVa@(o#f+Xf_)xNIgO-S)idcyG)k3%J;fgG{dnu!)My;E&@ z`+bNVU70ktx4!|sylhhy%Rs^{mGTy6{*n6>^e!@VrIdvf8M*jZEkUnfz-)eEb2 zWq3|86bj^D)eatQW6Dtwj-FmReCjLaA>#Oi<4ENurqg(K@A(^eIqK3KcjAbD5?aUv-2jt)X5I(dwN_~bpgA~<1HEtU!xM#_H zkjuaLhuID}m`6_8pPQ;SEAFzDRSch$5sC z%WCji%A@4!cwoFDrG51b0}YWT%CX621GLiL^6`%h)cf!c zUqyQZg&T=7zR?klT~T>f^`)_Hyv1hqByiSuqxQhOJMDA zVz+$p^BN;>JjJ!=YWs?xvx*$8(%5hGFJBC>C!;-Ml8O=S8P2qMgtJn^8ge{1X6G#` zju90gwa^%1O(jZ@JkMb78np6Ukj13!X`pXm69(Ak&o$ZptExzUEufBUzp)m9!CS-S z9(oZ&SDdqFm)$IJ8U;RUEJWjx8NSReESvr_8TAjicHKK#h%WVvi-Q+f;Kj~ zChu{>#ekgbC!W*=t1gD_uIZbFTGcG7>`Zdc7uX-lI8=D{-8VSw_vw z6vaE}R!#}@JLCa~vHpBSA2BuxPwbb_1-gMQQ4We0NxgOPP3MkU_EKk?i3AL)u%0RoO*tyY!+LrF2V(ASfx)C?TnIFGM<(?gm9t zk(32UH7RPYJ0oda*a? zkNbl?EY?t(B5vq-g z`pbv~AA^VQ06j3e%J|OTb-QhWxA+9&5qI=&{-n{9U@?Oo7y4MlOibwP854PN%7@3Rs!FNyaLJuFC{7NO{@Y=NLA*2`(vI*6M|!8PWlTR@TbRxJ-MPwNLa zYM!Xh)<`Y61Kr=7IFEFsdebLPXI5ZJ;S4v}@|J8cp>c^l2{zcpNudb*q-yq&H&B(2->+m3WPIBH|>8ebC!k7sNnEw1Nuhckz zyo$yZy1PmGA+XVR(L^Q)@hYIhzK+BhEFFj^)z-=N{|OY4xr-(kBK25L`|Hzw_q*=( zNA||LHKvpq5ncCnof?4bekjnlw(z02_6wyYHa5P0HlX##%wDcPfl2KJ^2tjtHlbT3 zxA?Ydu#BHfGjB!0#Hxprl7fbR=#Jjc%K1u_q%G4T*)N8T`zoO(M`luz>tM8@>;Osc z#llo_ZjA6cEDw^z=|A)@>x(dcF+V0J$nbs=j%U3z?z7@OvWL*ax+^b(q-?85(TaW8 zXuouAuM05?Jyl@zuvUuBM-UPi6(5EAj z69BRJrw0q8QR~3xQZeVxvuKRt#daR4;HYGlf-n#!>@>@KvS%nraQ~;LqdUVcNYofO z)%l}z)qIy7Yv3Z;msW;R0`5jAau~0UZzEE`)PbjjFxL>cjmaMmzGKI`7gy6K8ffWU zV>YnUmBPk1eoH&ft{SEsXf`djbIr&^0as?zw-4F#D^>~1eta&>y>R8$FKl`7`nP@H zS=`*9dc&6yE&V7<%muAWmlM0W`pnmS)%7s$K{pCM@)>qa)X9rdt^j$>Fh|utCok0q zZqjghz{WJ4$C51+M=54iTG%n64@UiLGH=}AM52G<@Puh5{9H)xukt9ze$)g9ON?(z zGQS>DWIdakk!Zn*Ds(+^Q0r0GlH*)W3NK%JLwjr`Ijk2#UI7}a|5F$mA~nMt(YRRXM| zg^td*QI%dtf&FmCRf>M9G6RCuhD}>VIeEal7;s?^}MZikw;MFu__S{ zh61=8MTxKf+`*mWq`6!lJ1ftq0gLejy{Mvv+05LNUm1|-=q$ADM*+DXj6%Lxt0T?F z5T`n_T1-M;?_;e`B2#j>OhcG(N3tdYTVw_wvvjmpk!5Cb9aAM{&S%w0j+qn-Ok$Fc z`xZ1C&y}=Y3Cd5oGJe^;D+tx(dF#-Ug0ph-{AhYj_PQNh%hEH>Q^tZCMWn|m7DDgqH{)0`>zGlUG>XLcMHhxYNxnUZl{v>Z0Ad# zV8fsutY^ek`2;23O=hnzK}XYysGg(o`sH1UR34GYMj^gP!x(G#1?eg85-wZrRi_D= z;lc@5$rW6!gf~=Eqw%MC3}rwuvOc_I66AFdyS+Xcm4KV{i4jus0Hgl8#+L;K+I@N}%LQXy zIDg=U{OyN=y|aaZky{yPw}4!NZ9dpJ8N&N%&AD2B{Q+-$|Ml$0?p1s*Ges6gW>wvp z`?T#nQg8wxdBfCEZhe{<{uMq!y;`D^J`ix~(P^-m@^ie&s7}Ji z=iwB;=3(D9zm}d}i0Lv?mZVzX&U2-Qv0GqauC$9ES|Map?6QAD0SC3Jm9zqT2YV== zParLiJf?77{Z!rrPQRN8CL}%JP-ooTlF19Mqa-icb2oiEC6;Iga%lT%5U~|Furh8H9hmjY%3}m}aR4G03l+w1^ zt=E?rms_P3h@Zvk@FcXkrUyIv!RzRovQ2WbnB%oN7?~vhy-FnWG7)}K;1dbBYoOOt z^;(9dP@(`wljS5g*Hlb?)gFhC-*xjK{PablG@6VY}L#6W=Iqn)Rll?-Cg5w zb3&+)PO{?Xk6$&0o}7o%KNkI*dg5xO{OHSqcsMyw5fXYPlR5t9pNr6LOhABF~ zqc&gaE9Ao|a_L`1UQnTyyw%4;&mFfklVZTR&38jbnJ}OiIWp)?j3lU@Mz||@W5L+60+&gZ#fF7wH6b4 znB>w!PpT633|eyQpy7Szg~b+6o$CBl#_oDDm(QCGuv88bKU!-G49{G2%@9GRZD{ba^t$l()p*|OmQ<55%r-M}m4SqevaaRO&t4w&i}|npjeZq4k-%^qRIHYr zTJ|MzoTT$mcwwQv&-*#$&2fDuTr_k@YE^UUwF94p#k#1uqtu|zf;|ViMxKMMlkrd& zP)WdCQ)py%X#!}pb@7{QGA;}f!;Gn4+k%X(Rjd(3Aq`zF-b zs`nW+@pwn&YE^Eqn5PxSnU_m4*%*?#_7AkXS|VLk5WY{Hj9YRyG#d+Y;~FI@dDSu4 zTYosC`7d40@i(AWb>B&CdlzvgMB6^Ws7sZ^IHjwSiT;lQD&&b2<<95OwkJd*u@9fT zixFxd<3pOh%@u7&OQgxo_Z&BH-D6+zUEmce%bNdHlNV5M-bTv;v-uEZND_jTS-`w} zqUnTu4(*0B#&dw0XYK$w6VhtsT;m*l+4%NxRhb@U1Fxnl0X*PX>I45(XZ&EUv8q;c z*&;2d?A>9RGkUhrmpV~FILVVKOORAFA)Z+BP9a#|h!5dzyJWHnP$j`T8m+aAZ!BeZ zdB@*qOhwW!;Qa~@BYp%$D!ZRx?FqG(g~eNb&JSt7a+h9fXcNRena?!7zha2(sS~ot zG3tgCIjE`12)EKOPDQ?k;wJCiy7CGN?D!{31yWNqf2(`eJac4LKGQL&vHS<7oIt`KWRSA4u8W8P(jGerCJz79-a? zBf`8uE3D(EeaL1GS8-exe>UB8z3DzXkWU z<>)zkX4e|2jrk0R_ZM(i(Pd-YUD*kDZ?9$Byl4gkzoVW2OEL9xw|;WPdKs(%5f7OD zNlOLwTgYF58&EgAb?3*D#s!7>B&&A;)S?u*ccuA}ocVe<6Bo2d#aQP8uYQL5XnrPG zjSd+j?wrS_hfvLYGwVOww?b%Rwjj5rs%vSZ4stKBV$sNzz6)KCf1+Zb_gQPf9|bme z`6Dgmg$kXNxfTY7j>>0O;Z=!{R3;MEhU3Y?f}hcf@_*?0aB>F=K8XGF%aWVa`1$AmUN#}U#GLLr zbQV)1W+%Z9Lj)6=T#$wNTkKheXzcUGZNZhR)$sXaEH`PE)_wIBe~r{R-)z3LqI`t^Kk zVrzBPz8;(Yi5_v9Bc9ib%`fKbr{kHciDwt;4kqNRUM_pXclX#xK>vDfwCi6DJwF_U=I=J{Oq1 zMBupJz+PlTxCgI*a%Sz9<{|aKiURMY3*G~bu>67>n9I&+<0czfKo&N<&a*P;rEMFd zrXDDE2p63r?9dag%It7J9u2ZW8I}ctUm~I}xnY}*q3&>M?xHibb|}7(&VHcCj7U=4 z+?+7v3Y~pNM6l%j9?2U}6UevX!mNu{Y;`FVvCn*^tUcCun(3BCWBd-Yf;YOcY51G{ z1*X>l`OfYREAC)d13@8WC_=ff=Y-r_v@u{>iv2KUqWm(ke8Y)pp=}L8e@V$otuaw` z*aS^Ukm zAJN2l!+JmEwnD~pg1g~dyhrsaZQrcw1N17f+;AHC`PH7AO0bZ68S#4GBEG)uBwH4v zHHz=4d%HM7n2Ex(HaJVYGl(adKwo9QIlE-U3|7-Ic0W!Lj}UVD2N$l=HlKOSXjA|A zJHf|ck@&Q=B(t*G_yG;r9+5iIdf&M0LJ4^|1IL?QXx!waOQh??;^O@^#PH z;fn7zureBor;gDwccJc6fF=XH$dT>8-~Ow0%nyGM(#ThXh@ub?69`l9aIFurEa@Yj zV^~-8c@eEXmwp|*xhjf$dot}W{!fPV6C}F~Nkl};!qoa>uy3#V`p_i#hzkTo=k#m39`?RgJ_1tcr{xXshEzhwI_J>y@Bl;B&evR-dM|zP%lq19jc{`)_6^Js@{k>TFf09InThW?M-}G59p>(vB(}1cS^jlIkUvP|9<}Z7a@`bvway5*b8Ef-COuSTrbyK(P zHD7VD)`_$I94xM#f5Q};QJ&=qo3Yz`s)%H9ou4>27TG6R(CR<(C!ppi^h6awgpl7G za$YHievm9OU8eq+xouJ?w)SPpZhlo8bhy1gQCetVDfEVdaD{m<{LH_yJ7zgW#l6bD2!543nnbB7G&y&ka8ZWwm!qeZaW$3)wkPmOo zKU2N2w~^Vm<+&h8i8#$zv}dz=>@9T>GPRTS=rtdbRQ@YaE3^I=QP_PXOd3-`Siyby z5rgERPvgC*nfVKC1t1t*!zMU8b)vf3=f=mp!N636JjlR(ej(G3V8I>CR%|FHcq`w0^(>ng z|8si1dV&y{VUuREy8!~QC$hR)#ver49Y~*e#@_hn^YLN*kLiU`$R5g|5SJjbd$enC0mLw*co?q z4*y;vq2TL$uRwxzZ)rA)CSo(vVailCNNTQl;eGo3K#$~lcYSALoE783+#KF~5r4qV zaw%JkfCfF_r8mmlN^jF4Gd7{*LtX~fWM^40O~$4kmAdxM_T@sDIZE4*u^Ccbk% zX2!J-*wt$Eji8|+-1K{SsX66}o*gBeKI!#y?Sz8wu|5XlRnm4d5TPF3vU~K5p2J)F zaz5B1q~qL`C@fyqtl?@{d08bB%B+R~9e5&-y0Zhzh|Bu$|A^6H8Qw6_m!AV0bAWt4 z>J@X@xhj!!2XUH1$hJxTVMStFgXD#;C+&V~F(SKStLq<_OhQ#}?!(wx;S+%#3Hd?F zp-|sbL3&9I5`F1lw*v25mdeBlp2A6yaZzKna^)g&*<%r(@%56mB74gua=)z3)gC7gU@}HI>niNz^bc#ZFBTdO6X~& z7@t{EsMrtP-Ij{vzm+r}2|zYT*bg+qX4V7pc*0_Ka71SaLeG@i6LomQD<~&?@(d=% zErJ`jCjPWZwl#Zy@%AWX#2kZ@QD7|!L>m5mG&cK+60Cur9cfD9_`iY!XQrwZNoX>j zH;iw#9?81Uj)uo7k)=mV=L=g+2Ix-Tp34~NY8|gyc$?GQWQ*RK?K~Sjyfh z5#d;IwQI#U?B^BGGxo*;N!jF+&nP4~_+=eVVCQ$`!5N zx_m)J%|6aV+2HlV{ZGP%LnavG1?PA6Ta{h@`}EBO(aC94mzVAZ9tw~9oIG7MKcVPp z;yOHOZ1^57U^7QTn&Dn9CP17!{NSyNA8yd6k)^`Am+OJkG{>gNY|QV*-AqU?O_RZO zxO%?GdXqHP-+$>;7_={22z^N9d^p6w;_)jSNe2Q?%@^6JbGKU$3XU99fJzyyhBgjLlL^M zXE(euhZ+s~DjLML^`+vno=+~Ig{I5VpKELrag%<2DQS{Un{Cs`#Ttlji`!Dbd81@{ z7dik~ z``*5W+>3oQffsSmkANZnJ585gC-iiJbOTy!nEdJ6{{#3d9(Lx`ob+&1t$ zV7YV*vt2Xy;$lGE^tSyD5seDnz@1(x;@f9sk?09zeD?rO8*tpfqKFJ~t!elz24FxG z&=_N@)xOmR*$1aA#D$2uz1soCTe58L&SiAukPR&WJl|c``*XUk4o1J{DiEuT(2n zwHij2s)Y>PDDt=y5zafT$99cMu`ua4I@1#nGE*Y#ATG~+jui5Z^ZTBy_QmQjv%IeE zyo|Vrh~x!uRWXp94evcSZM#M#XW#{O9VIylfh3%sl~x>R^=>s zTK_++*MA-;G|lg{XeBfH43E{}h{FOfl z6Y3z?HT0k)+L{App3i-lT*D9Unbq^YK{f8t)zOL-neP{k(ghMN;S31nY?<%mlQ&8# z!6~0sAI_$BkKD4`J#o~~c%_W4FltI|CtqCE#rV7nKNV2!SY& z8Rr5MF&N|o_+4G)0P7SDP}lWtL|p3t#Jaj!RJMA#*Mc&i678BeVoCv!3Yu}*B$Xc^ zF99+WXovtRQ$dYrIMIy0MKXV*(mrzDxUWr;zFq zi%Rs63AJO1r(7sZ2U(7qSDJ#o@;HheWOF1Diu=mAjIz;K>A2ToF9>sga;NKd{!*D? z5GK*!^S6Vw1|VE*2vt6i3Vdt!$NruY|Q3h z(xHuU5joA!tvDuNSaUV?p0OkKHCOg3$66ibo6{m`w`gUl7t}JZkt&P;6PSw7mU}#}+5P zC8A}U=TGTK6a)0pX|@{A22i@^wEu2hJxAZqoOa%Sj%Mum(f9DNSH3s#ki{QkN5pZj zNw7u{@%A^3@JFijb!tN1q{LE3yL_b+$jj`Boi5_D?Q<)8*WJ!?wM_dme=z|S0^7&B zOCnEcM<1ACDI2|Q1jc?3fO6>V=~)0U6qEyXdnSir_kXqNRStlBg@PG8=g@2%Pu%LK zSp*`?Rp1wZ-b2lvqNb)sTV7imYw`C74&M&ogNPIr_d3o1l5`Y+WONj^S_OzfC{N7h zL{UL$sSr}||Bo8|0o7w}U@Qg@zZV)B?SPXIncDVbZwycXrU1tgQ45(bR6wbgNAu>I zCd#LQvp>l=x8 z9uiSaSpV2nUhMzzHtwWLxdTg@A;G>~LrC>4HK!*-x28mmIx8Fp+FOce^InOm9_(m{ z?V8G;coFDK%ZA92Id5O)6!>@EN-j338A$2A>r4~h@(g)BdG0WF?Dj~t*JBsJYj%NB zJPj}`g{N151+llf=qzysK3A;QELJG7Gqq_7!_lND`yHMJkcDdZ5q@&30b%s1;_s1L ze(NON1+1rcC-piPlrtO*f_)1gmBUreM<{<1Aw67V^50-Ls%z2wbjnRXeW zFcpGN(mWvmHzav;4h5$OUta>R$q(~Hqb`6waT1|J;Tr(QTR>$AjDGmbBm!&!LGg7= zIxwgR1@S`B-|m$)e&8{v*#|Bms(ygi?*ZTDtoytuiMzjvQ*Wk`CL+ouM@xvqw?%u;f0N9V)p zR0K+^9{;;gEm}t7>WTQN3%98noYBcaoQ{aHMpbxe@Ecn955*~;#|M_iAx(>WR!xb& zor#n_ON3TEu#VRFd`Xe$Jrw}Sty$CF79>Dp^HD!@&%eMjn4aHXGYplyQRCUvNM+=h zN3Tl9FVFnF(?n`0zVhp%L}!&+y*imqB5^n-;=18?tL#}NFL>NnF203l0!~9ClqTs& z`?0*4z1I$p$p+`B5gAwXt0J!J5)-8zbvv8_@;W}ggY7+0mSuxxUnl&c%JxmHlJg8& z)C7D$C^1{<`^27#W&8h7+q0O8@uAB_)Aa&gge&~gu#)xj_zeT7nO9rM$m1S(oY5_Z7 z1T)?OcZ6g53(c4Ksg6*rxy2cqiBx0xi{~VxE&0(ODbGbdo zuR2PZUpocI;uF!4@6`9p>tFNyA=pj|Y+B5bLs(5qJRJcKsFc3=8j2t?oGrJOhC0#u ziJaN8=9bOInbk|^ZHhc)sp1XT$1g`X8fF=$@7sQYU4XLjk zZFeLDjpv5_%^Lynit&35qZZHmxQ`!Y{rvup00L7Mma4{7G2>e|-qf7|16x!*Ac|rF zSdBRl;iI9%)+j1900Ggsq6F4}?C=PP(h;?+w`Io!0RLFI?;BvF$l6r|11sXo9Bp!L z0+om*?g$eE8tc0lZM^GeY!@3rW}7_;_WWCft;B-;85WPu?rGM+eFZ4Q$vw|+W_aUJ zMQNARI_?|ywrtrCn(QZ}T{JzFnEvT*Cm8 z*xPcyIJEBuyE(7c(K|({OF(d9N15cM0=WHJGO4|Li1`R>*K=FSh|d#N97niJ50y{M zu$mse3KsUPh~;Rn%mL;{6!YS24 z+W@&8H^w*2h7cXruu+(3Gx7O>Y{%k3i zWKfg4-sz2;f&$A-P7Cnm9~^_06*0^ihhJ{eJ_@AJ2e*m}Sj+5dcy*zv^q&Lcgj`7< z#$Dc}mGp2~L zGg}c~V4Cj={v_+M6Iuz~nEleo40Np3zsn)d<9ut#^7>3P=8c+ICdb72%$^>MIb|4E zG&fDAw&*nC>GND47icCpu=iIB9TJt1&~nW~d=?}Ke+4e32@_OkekYAc4;{@zqot65 z7Rc-N%Y`g=R~oC#VlwU7xHkO|BjCEu>GQpuP$E%Z%boZ!6wlf^P2PxDSdfhsAM>)O z_&_kEFQviDkv2#XVi@RL?Qk!fp8m4tyc4rhc5xfsHMOmQ)hAh)&t@{A(D)a@>+TmA ztAO20<7(Li=s74P6wR!hjSUyLKbQlSB+<`}*#=>-2_4=e{sI_wg383sR%;hb%PqTV z#gVUZu$1?V^NC-H+5s+tr>K)4iN|BRveSU2*&K=HLzrHtH?zG>ra}gRnczLx>8(|B z>!pkfjeG=JbmQy*AQ!0^UP^U;D%Co^(0U_1boz-TO<3s( zRi-Z=)_`=JNzitSyf2#QP$2GuH%k$NILTuf%LN{_Pu4lBUY&i5uB6=0A$x$p@Wrh& z!WtkB-JRZw+LzIX>MX3=ba+!PzRwAZB{=A`sEkWU2vdpFAmIkwi2&XOU+bYNxCdUF zhZNBMS(i}or5Q0Tbu556UUkRJ9SC-;{*(FH3+4{5f#?3_<=nmzDcb%t+*>}vLi5Bv zz@?v0SZ7Bo;HaMTGrUeHgq3mA4}8v?=!(&b;j9ifiGU+MR}2&TRXUV^_}#LEmQ@Fu z`kR4{yU6(d!K=_D(vka^cs@?TW?%&pELnr#$_=py@0gHP*X`JU+`0dRfIasVUEG$)`*^-ZhU`V+O-+9u<5%>NAZ~9`_ZVR! z+*`gfjhkuuiwrfe)%;%zsE1fMlbx-LAmgC+0wKTN2HsWl5vBMM0I}$xO6pw+OeP#k zKxvHsK@_nc5TxKEpe>{1r3<7L-BT5`xBsJL=5dB6wb01xS+Vi^_m8RiIoG`nC_ce=)&rWjZtZQpy zEfOw(4IAQRyXOgEy?>LK0@)NQ@H}NYdN})ds*pFm_0Pke34>3MDuT?l9U5XuLZ)-d z2piG&dT)Ee`bgen67f|a;)C#@EPGwf6(Iycxy&|k>n%#z7rb-4SYbE`jUn3s!>ne9)2!#|;mO^r)C;Mj zMqfhc!0#w+e!C->)VE=BPuvpO)7)YN6}PSGZA;7AR%HTlr_i5EWzqc(ONah?iBB+c z^74C&5+S~>*l;gc-} zv9Dj?lV-so7Ndio3;JHfI5gMBOtFu(ylZEQ|oo-h*7jn=dQvnN7j}9B=O_kfb?S zsm;TA>D^CWvN3u7!L!Zwy}Qm9*;(N9rAPv=S!jop+A?{>DxTL0`#bPSh#8=8ICt9r zi4m_L@<#zcOjDZ@P(X0IdOkp0whr9o@wq9gV%_)v_XQlX|EIi-o|q3kHB6hFG<`FW4o z3oti<@mP8P7Gv8rLMxev$g2?&UA$aH;2+wjOVG;<6Rl{4XMu!5$cgS}{mv&)O|0a_ zSnF0l$nBF#b9323aNVJB)n_WucYPa>ER?&#jD73`LDMoRq-=r{@i@Y=FOz3=u-4c% zG~bMkA3y|sezE)cYfDE1A#V_qE~(j>M<(*&uP|c7ec-PXXtc2<(9i9j+rBIX!Y-X90$Y`j~SYxc} z^};63#?r*;=8$HtWoA39q90fTk|lD?PjS8S@r{Zjb=TZS!b^v-&pxbazG3!eU%pZ0 zsr-HwIV`b$T1mac>|DrIbfpT8B@9=v3bs4lmF9~zhHoFaHKYN&1INDyCs>H>0pYTC zN8GK*-f6=)bu~KjP)KgC&@85=Y1*AbYr#4Dz@^oY@wh<~Nf+F@jyv}LV(94nTZT?h zbbo3(pj>sE-MvZd<%9_d$Hnl*R@XIi>RlJ6SfuCV-feG%=llqtaWt4$Wj5uT&e;u| zUMWqOoqR%bK638B>4kUbfd6yLN6iKPu^!ETff?DfaLPqqJ^Z@&PhE<(U%m|K26fNJ zJAu&ud3tc{1AOis7j>P#3aiH=+9$1qoqE|XpXlYJ{cx};?9O|SGar~S`MhtKy(rag zY&HavE3sW-fxX=z|4C~=Xa1fXwYn`x$YMX`&qfFUk0b} zdQctSs0}ju(4EZ9t*&`A+?cRu1r&7OE=J5a(X%f7c`@bsl?#C+$T!UH>z@xy$)RfR zMz>Q{c&s|u&v!^1YMKZ)T9`$jN}4p_q_9DYD=z_x!!Tu5=dI<~p9w3j;nMy4Hlu z#ScLpZFY`gv;m^7grCKkopG}13PP5HTkI*(D~)b=UD3xrfpgUjOoP+R%DFKUM}dBrPLTeh=16# zx;J!-N@n-`?qRvP@07uA_3!={`h3cw$<``>ec4-jhuFerI6Nkg@cFd9z1#X56Q{ab z-GI*PwIF zX`3rj07~M&BHiM*yiQ{~Bx(T`nFLAA79Kv-2fV4O3*=!9j4&OzMe{7_3^~<__K{XO z_Yrq1UNw4Ie1v;S`Xj;V{Yf0gHwGVC<>h07H*SI7`Uv^iHz<+UqetFY;cST#iDGNt z_R!9h#v2(hg{g6oz>FDIT!~w_8hjHV+Kgs&^Ch~WML=YEbfnX#QA0k6$LPupE*MwK zbB9OhY6eawi_Sl;@!|&Vd^cN7-So-HEIs_yGylvfZ|W%wJblsGyVTvGOecgrbqa%* zn6Ld_ca=Pn5kY0sASi%I5C7M;diOBomra!w?)eKrS7bzCeXo$cgA-DlK#b_lVF7~X z7euPF1fO?iNXeOR^|Y_kXs>PAl`o7u{0QFn30EHV6K4rih6#^$fn>1@EZmqQ); zpSh{lfx!m%r<7d!1o#d!IVo@O4s6*6__MAdnO@h$Bk&?7wT?kqGS!g^Wp=u5udE4G6N`q^Fae79NZq3SkX;&>KVBnG;fTw=-^laFe z`7ZE2*y-JvAUh`*>FVqoWM?l8D0$I=@?iI>q`S$Daqjhvb7;>xv--nato}_Q4i(&Z zR1kqGw*kgHz=Dp@M0m5}$~3SDO$UxR#?qa`KDKOHkcx&Fj(u-BZ)_NEuWXRi^uxGy zgLl8kh`PAU+vW+=fDlr|!<95F*4w=Z;ucWMzgaEV(O$56ZzXy9dBKIDicyJj1dF22 zOnSWv*Xm~;B17MSe&v&OonGIW0HK?f<6V5?L|g5Gf(ruNWXP9UfVc|9qvX_x!LkdGe|KK$u=DF173oH1%^xjfV2FRdAg;xuOg3MjnVA*|EqMchGq6y_&A2*0&4GbUk_~Lr}`AvQZk{!!+RQLmX>0@1#X3}88fj4W*i4sfTHkQVmvFNRwW4e?)c$T zXgISj21=a>dRc(lhn+LIhEi`8G2q_*Ui#_d>QrfSHlgEuT3(EX z#*n_V=ZBUFj?!)|D=g>KqU3tq;;GT-Vol=uzgX* zwN)u5CS*=dRkJal6;d-Z(KhuS;t$m_DL4%F$M{=Jy<&0XUg0aZyjK=GGcmYj`Q^*| zH{PYevx!NaT?%-VDY6xvt;e^!8?aT(2$>xfTDOaG?YUvMT@Fnp_oa?H=2r1LE(qSe zVtYZxI0(^tuU~6qgsZ|x5UN)2aNa@WjP{dQ$(gn7`(v5+<&)TrjA>0lyoodK2Q1)j<>KOjp2VMF<^wG@O!n~B2zRCli+U9|=(^u5kw<5Uk}qpGTYG?_4Qrn_PMCVDooME3ds$+$D1zu#eh0w zZtez$R9pJE&+kfU(>gX|z03!E8E&8OdrkX8ewelatrUecYPrMKAr+vn`G)qettuG?HzLTmf zLhw8$+!#q)=Owj*QO)g(u`Edv>>J`CxKoGUXX0=rgl$Xaad*v~sAFXAvSymeo*Q_Q zwjWv(v5ZW>AI{7*fKW8Kla7x&_?>AB{K z6VBfUGcd(<#8tHhYiVHtQKrHo8ByGmM*$z|Ha|L>+ntyxK@1AXCK@l>(gHy7nEO_$ zz1rKPG+#WIdhJ1j4Y6U6y+Q6dE-F-+6Dk`;9(%2?`YC=A{4^{2MaoCTshK%Ymr*Y5 zp}?a~CH3y%X`@d3QbZw^^6Zv?uZ-QvZ|)as-`pve4bgLk3J*8S23?C?-~>G1b1gr+ zyTzzsg4~!rmQ(cz=Ov5`AK~5Ac+rf6WJRX!d6ZF!b-e{*}R zey0=Dn}hQ@IHfixSUcxsw*CWxLXQ0x8JSoTB*z2CyXs%pw+p@^{G}pYFpOScn5#@1 z%yBEw6F>GN#v-#cPlKd6Y9A4$1%JJLSR7H5SAW~H_HJ9=g@zXV!2`F;x122D9u@|@ z{km4v*U$DHaHO2+${=DB^Yr2pq|I89O4FsqW!iTRt%rvTyAif3R?R zld>7lpsBp;P{Hc}r|!ksRMl+ZH!m5%O>@~n;Z4b2IOg5p=a1#jGo?Xe($X}t)F*WE zqSZp9y~kFkV2M!)eM}GQ)*eo$5}JwP(up?mQTz>U`Mtnz%hdaShR^&Oy@Ofa=(8%; zeL%P56+}9Oa*1EBd<&DsshW@fD6CpY4+(C2gtUF!Qh%P@ib+T=Mc{DCKzza#TO~Mg6kwSGWn$Y*4r(ETAo)^ zK7`>hlN>u%g2-J$iz-LnFJJ95J;8wtC%_xbU+MS9zu?wk^bL{mCKZkR1)Kr0+Ah-N zX#d{#zoWqIfXE!eBs7hFp!la>+e}UCH5M}!WQ=NarvCSm=<{g{tD4zd1xalcTkU`{ zD*S7#5D!F7IzFoy9(t#m^aMvCx3lPYsV3to zDR8Y?Beq*|#_gq}1aqy2)MvM*$<3g@MkzBK_*1g(r4~ABnG4S6pLr8aobF&5(74o@ zyrVtgZXNqZnG32WJiXyDvV0HpW-aosl?Q9hf2jepmDu-)TG}#N+nJe~$1Fd-1k_eQ z1`CW0t?sr5vy#qS&avAUr)cxuhAK-l9i;ykq3B)Fn`>k+Zrtml6%^Hjaeg~n*!@I zx?gc#({NsYOc|6f*bFmv>h_NGGO2g|xk zaEhZNx`q|)vupeSNoTLmv@+_g#d;XczJOm$^KSYcZcxsDlJJl9x%g$X7pQUGlaohU9HiikeMCQX8E-H`%<}CYvuE58ft_I`d2{iL=cSMoo z=N-eC{Hrwumf*Kwi8l3+`Np&reM+k6|4{ZSq%+nsfMh-kqLC2ldnlt_MbfRQ}LCXq!e^%J!W8+vQP<3x5Nbl%iaLSislzT zRO(^D=Gl>%Cy>c1YM<4|Hoj7kU%v<6bfH<|F}bhTVg? z3npCu#GE}CiT87G@sL+N??AUO8PoZs&;1%AdG342Sgey`fWk-5m zeii?#uiEr(G5flMqCE54Okrsc#%OKo$N(gJijd=X(!9|u*`-&Jxu#ZCTzrVA+A()` z%=xbuWJ@alGmL-&a;d5w1#b2%$ZP={Im(J28urRA!v*%79<_nG1a)oF4>(}4g?2B! zvi?0bgaH{&a%+?KnQI>rdKsaX-(-?i`=$Y&GEvsZ_5>&aL15}HQugzl-%;+ z>{Vr+aJrKW#ox^0!eZGmJAOV0bx;+)M=keY{)rg;J@9a&jeoz5```f^wG2H=-Agjj zljDCTrBY^w-|i^VTnhKUnhBPs(Nuiie|P2#`;{zKId|-K!|uXX_LNOuz;$h5p{})k znLD#KS{>}mv6X@zZ9XHreMbN70qoP?xKkp5>W@+iez))cgwW%WpL#0~d_3aXEXgL`{hV__*l97#%>WX>k8qh$ zvZd;_^1oqHe<<+4$bsIwt@`7gdi!AZ!QU+~Z7}u#8{gygTaCJeoe-TcN6WaWmWSW* z6h@OQCQI+KDJw~eI4>291=MNU1-@SyU>W*!OZ}kspY%)msNqlQI=_XhZSMmN@Q#?M z*vHl*Mx8yrz@Ko_X~C%3?LD}n+Cl9|sG=pgHd?QL`?tQ8_bBHrHLzySC%L6nB~?Dq zy;dvv#)-P9kk`=M*nw0~U1u~3`OKz+sD6OuRCa;5LPs%qB|>0^?!?Bl|E?I>fy}(~ zQ`-#!!&p7OThBuOMz}aE&EiS&X^3p@5N~pJVq|pp<1@xcwZ(AjYbhiiIo0;u2V;wy z^Y)+kA^hW?@WPM0Sz%=&qDdKKY}#!ne;x*^Lma8`m@|(33VT(sqccJlV0FR*92>OV z(}IDd(D-u&dQt6I%X(C=X^Ji}JLG+=Ow(9lNY#=5CJYtLH|DS&&c4-S-ii|a=&?So7fuvQwr=J3VVOD{89N?=~EFY zYZ-8aYsH1pR}S2ruaRc=up6>NL>ylTjNutSo=ofE^$EGFe;Li>?ti-UUHURjchrh}ZZ<(FZV>s#GO4zNvg7zSRd>fPo1m%(ul zc8k7N!dK^BlTq9!d}k2k1C-BKJC?G!H-L9r5i~GxPfgO()^-FG)S+BO(vgvo8`sqv zOxph!BY(RNQQ!aeUC6qEJr@?|s3WMTwgQtyix*EryP;D2t$N40stcp{E{Fb3={VWF zEVhmXHTFGzu(HIRW5@{_*T$dD#)j?6;i#|flr9Z#68Gy#9cS5u?_j92;{CB{?SCJ92%kAnmr*S+) z5$RvDiC`>;%AMnfrxD$|!nQl~!hb_!cRBI4cN)d(Lt{0tiZ2OubQ>$LFKr=mYxjgr z&U~f`psCEg=S65fic7osUFxteii`FuPw{ElwSCs?Mca$Hq2qpw-G8e9Q`BJ z)|#3Pfz|ikHW28X<>mdj-m!>?-GL|JVJ}dQH@zam64il zl`gq1W}C0AN50#oKJ~U3xVSz{7g82f;@o6|SRDDuFnOj4%|o2mQ2hu?i=&i%XT}?1 zI$!h0xd{1eGUm&n@E;{5E6kX4d|_c>pUcrq4)Eiq?Hlc0O>?ub$nnoC3)amdX7vuu zeq4OKVqqHbkHfW4eHys=mkC;dts_mzb0O4UV{)MK;Z3h`d6!y3nR$K1XvArdZSQ<6`%9IwmI6`z|nU2ry<;e6i6 zOU@W~B_1Yo=5OW?_Wpfr%2B^`u?R=F{n@l&U)htx&)VVmaZME0X%j`Ax}Hpl?c6VW zWYl;$-c@sOa7b=><`>gChFF}spsp^9In$tp7J^ox{1Xw+E-uJK%4-3!02gEZO3S+3E8zBy0Dms6VjxP!y69L zpu(9uXDFCTtWleZA0cGjPdU@yQ)To-|7a)6e0yI1!x1EV@@f*T1VEVoX zTo6R6F!!RbyNk=v@GyD(?ARFYGyeOZiDUtl9;ABP>8_ewNLbx!w#FS!izoSWz1M!S zN#>{b|Lw^PH>fvE8G1e-YjaAgbMC7Iq7dmVD+6k<40U$q2Eg&ykHcG#j2mQ z@~e9)c_btyy?rXa_1N`x!L6U!eX66`ZmV7Hbt37Q^A~8mu%!4vgd3bP${}?oHYwwS z7SPZ3$|A&<)g3tGvW{OCtN!&XE;Ezavz6gQWHl4Jf1l!$QE($x}bwf&7y%9;fW3f%{N~ z_wGK0SUJN>W0mfrh_Tu6tCE!9Pk-vKz0*rP$iK)t6}yJNiHh>9cEyIF@lxTY*FrF6;Z4i<+)yM*gj*Eany& z-h>ZGgZ&CGIkUaa9$4t$dPgtq_;RzL-M)I@TBfuV2Wj`LkZYh>*?>$12l_0WLFHM zvYnmXO4`Iqp7)IOKNvvIqywLId&V1D-3=TCpl!>|;3Qky+pOzg>FQvfp%0kF$rYj;>If zmC-$i!sK)izI1dv@JDyw_{39Cd?tN`emhv((-%8h;l>r}2jN+PDYPZSyT(mqw?uyZ z`gI7{shV%!(p@|d-LUJG#7o8e2}EX?p(G2;XO^oi*OeKf<-2Lyw_GI)OG${gAp6%k ztNLv*?#5>RdKYoiPlaiUx9w~>!+-6kJ&Tx3NMNv-ddgzgTQR2|v#*zsn8e?*VlL)^ zKmFDrpWOxf7CaFhMlRKdMjD$cnz?Lz%(Qzv0Jrw0>I)*?PZ)V$w)ac*7;H^p4mw=^ z$+oRALN=UVl5Rm9LNKZpA&T>G88uEC>F4inJ(4Q(kB#@26H}^#2^X7mJsd(p%FJ<5 zHPV9wp{R|@=}Bs80Cw3Dbe`@4<4ABX3= z?voX#0(4VdLIvmUrq7iJsO}{WS}gy=sm9NZjnp$iYLcs$ITV@M&V4wuE6VLNkUqCd zEl+T#w;UdFjEKCD%@?y|v_nH4-S?*f%;trK0jUPJ5}6{ApT^CpBW<$Kw=Mx{jYKAM z1}<)Har-Mvx#^<+q}7HbL~@x5+CBEt^((_Z5YnZ`mb*4bR=k2mDJ~V)hh)f|ON`@` zTYJm=dx1d1Hvf43 zm6>2WfwSika3nZ?{4Ag_`0{<1fJQgW!6f=!+o zpW}Whz{5`SM_=5qFn#tQnb9ak<^_Nhm0eGRkhsq{;VUQcya(!isZ(tiD-9bPZt&II zAYk`g?|A1hL6-rs8&G2I(ZJMSrJ#2Mmc^RRrfd)y(vr^oDh~0dNIMzcG<-!b>-1J2pcWtSj7fr z&h2K>WgB0LTLl}MC0iI}C0J1VgPTvz`zA6A%ii_I5O6w(WFMBDSQW1`7v#eacdzfL z?e&Dj7)hQFHv4A&k+_nS%iaIYbv+U{?Xscv19STovg%x7a7mak%{E zSY4mjzm4gdSxo;NIUf-3EvWJ?cJx&N}dZyy5m>|G6A0!mAA}^wX1NjcL)6sqgh{UugC}%k#^`G(KIZI<-@t%LeY+99LS|h=;N2WFa-Z!43&iT?=IrU|=?s9yTuQSB z_C|k{JcYd1(bYWytHNDI(?)qS(wuQkO;RAEdnMpwV_^rL%jTj?U1(5jO8HGFSA0!- z1Kr<83a&)AgX1_q)>K^-phyRj;(LI@KD3M{Rd^gJ%l$ zmowSPnCPqxs82NA)oZN-R^>gsV+r(24z9x$Ld2!s?7$R)WpVFmR&DDi} z5&qU+#NwZ+sm5V{0p?xVRY3 z+|iH52GHklKyJNRntvJ73LFIh=L&Xl-0$<|=D7DobS?{2j?M!@gHrNNP6C`6P^{v3 zlFGRZeU@)bQ9V3lB?8et)y>$b7OP%t__I#+2i2qpr|(?fYIYb!GPIe*jVP0P+ODZ! z&%dgAg@~gzIAC#K-OSc+!)GB-siN2;cWK7oEyJe1XOuQ`O8JvI(}n`-Vy}878Cl&x zc%C*4aN0Jn*8gol8ZMl){XB;^bXe7&db7`Al8N7{#&L1-H zC=ca)`1b-YAg2^P9+2Euu-~7kxFLKAfkbe_5F3!#=CNQQ@*SVBzx0QNQmfO`O+9JRFcp|ln4bz@CnU668-L(QY#7Rd>ua5AS{drik`pKNR{ z)JXJ=jqEkmWsi1aXe+vq)2Q4=Y`j*au1#6Sx*?TNIYok*a<8 zo`Rh3?~o&@Himr4M8uqRfPUf>!YNNU zbX2EgdY1HcXX0)+6F6W5;$k}G%yfPm@M(0GAAFE0q z@+o$&Pukt}c<8;@iI!H9`|GPu$MuUOJZ~eVE?4#U4%eg$_##{WZ2Cpr-0asPe{ODe zDM;A{RTeLFv0E3z=%K4V4?q_hm?VomDK;d!)M2gc^M%z_`S078wS;iiDp2euBFiD%fQ{>=Js>SUMR_2Z>k^fI=CAW zyWMwY2nR&c&VJPgEStGd1ckZs`xy)wGW~s}bkIlB873PymmJ7WFxPfPQq2ScW?jR$ z9e(DgmCZeaBV^e-G-FaJ%^xi6c<`jk#HD9=w!i^*MTH-guEZw)7ER(3sPi%GBeH9k zO5BO~o_}w`sv2X{_}8QYm1gY48Zv$Y_$4gsn71v6+?VYg>f570#*)BG^Ft@k4ZjC> z#NnsuGsMbDD!03Wg$2DDwafag->-K48J<>j{~1PA4k2msuDMtu%UT`Gw_Rs|NY&u4 zIbxcqluR=mS0LV-PP8`%$R>9B4jJ;M9GMS!HE2GtnmnS0@Fs zyQgUYOMkE~i}7qbMd)U0MBK13-S=j`uRkD*YX`RlyPeMJyqA4_( zq*uvqqez2)g7m);YS^MDzcr90BR$#L>5h?445v`Cl`-*Q4_7Q!o#gN@Wy+R+S~3ATk;<*>Oz_&XuJe%RD=JLURtA&I;6APcRjFnGh*Tq)sN_H)6$v<*HXCgdA zAVq<+qOJi87^5hqwRyBzwj4xUqxy!rrI{Msptx(#;#b@0%IP0sf``x)`koedV|r1! z`>laR2R5P1I~`;*^rG%Z<&;XMYN|b}C*rz)3@aaU2vz-KVPQ#mppS$9oAC8{RQ8p{ zM3rE(D;-I1QtHP$&qntb7Sg3L*8K{548DwIuF|725$(tHI>1@9#D~X^_>A{8QKPGtgJLa+xqzCCR&K(v7i`?5GQs zgVJe@R%>ot!?5R$b+oEU;O63Z{Ulra>r$0L2$x&;Zs5UHoGQk~YsmrzcZKY01>7T^3~xlug|u6<#AQi3V4 zww-+j=$?&MITJ}JC6u*{zo*YsI$`$fxo3hXaVj(89CuteNy^;d*Gk;{{}LF8sT5F( zMI;Ikye$4Voe(8%Frx=*P4zq`06&A|=g0N-?eOX@3pCdzhEsAFa<#C#2B(r7fBzBh z=;7Nod_<6hE|!>`1(S+s;N*zi-SD8Qtlf*T)4D!lWZTY^HFaDiY3TaWc1Qys%uKDy zAT598@dV}znzL`_;mmFsaZ^U5m>TH4p1u0Kn?BJ({i#fCcD`s!bU34Iwv4_+lmNko z5%Fq82*%;ANnXRAunyadE-E5OPte9>29ZAZIr(Sjk^_r2wpZV1z5_}5f3E5MvzhRXk`I#onEt?!E zK6mb@qTU6XbY5!LqS;F|j?$v3yBcS0xI&+$&P!9q`|Sfd{6V9Xgt<6CU>?sVM9DP2 z2%hf$^!#Ot&c5V)P)F>U$`9b9+l-;dX^ee^4M|U_8tJ9=@HKO_7wECz9w({@Z{JMc z@GI2tu)q3cRz{DSQIqTa;7rzX@D-~&<<5EkO#QWiKIhTY$*byQN5TD8&qZ8|oI>WX z=;!xkN(U=g=DraNq@?^xdJZmgy4C?+v&)*v!xF3}kdlq9vzD1xqnB&GC%bl0bsFnL z{Yu$Zq$D66vM{8cWByAIR+$b#9A+=cz#HBE+;jVrIeMvGZNFOvtxS8$#*ejy=^yJ* zHO3Cv%5ozZ^AY@ov^MxkBlNk+mP=dK+$*@@@qT!uP1a@4TzK^vJJO@-5p?u6BTQ4z zy%xC|aonbt(6H^c?pHXZ*N94arDCAMp(RS|qpKzsse}oOYb;Y$Q?BMoLC()m-sJl;PKqS_vxmy$h~vmM-*9Dx ztdKe7ICNRQ$0>`~Ld@;2gNpRy{aEoHQZv1P*-!Rw+2!AMzQV48m{pf7@Ki}pv3)R^ zdB4JFh;Svv%(2nWzAv&D%(Hs<`8pOoU%MK7b#QmGknSZ@NnluJ>UB;uWu}mRGbN>w zUZjF}YN*d;YOo0Td;~PaI_dN`5wNRSP~znO6%ZTYkxT*o?>AoISM|&4bda+P&t$v^ zC2Xg&?)72c+@74S??mt_$t3uX65+=%VoNPyKfpaT!ACu-Yw?sfgm=ryyl2l0jylMZ zR|LUOc}GrWw@iK+XYK3Dg?_beP%3~dy3-X7tXASBGL2plAvt!nB=9~4Lkk2A=DFI7$)N5wRZ z34Yj!@BU_uP6#hW;1yb6SaF|Y~nH4$d%UJ zJ4~{TP`U}c`$!?XscIKJd4=Ei;%Ohd+*Z+5Y*g`EFVQsa2jO7Q&;YR1>q6iz7aa_+PfZZR9jcuITh2io{{uBNN)P)W_k ztb}Qts%7G;srs_4{bNd}c!q3?s*U?lV~4%vrwN4ejCs}Y@89R1d7Hk}9c3DC{aZcD z1l=u5t?T}}?k5*%jDz%j*kIykb7k{p{E4Fk!bWGHf~z=eN%Ox-Kse+bi|w=p;FHoy z7Z$$~d81u+Nou2S18=(@yau;D-L{6&;rlwe z(JeImC4NrN*xrnPmKn`iq$&%^T8=z;W$++b8**Anh}VABdXFE8}U{bv(~=TLg7??d#6LgN9R1mapc1frrdkV-YT!RR#k3cFI3APG_Uycefz8| z7`WN>bC#Uf#IbsW?c=9)vDKLO&(3rjX9O6ATju4qG_ul}O@0 zpD4&kzSTu`e%^_kk+&uF2@j^ z*sd!!N~jxtbqI6S0Hdj>{E(`xn1$0Bdn=mUZ$|WKP?RwxBcW^N#p!bLHUObVSx)MBQATDtWW#>0$tC(gT=J8th zNWnHAa^Dlyh1GhW{!9FgMu;dTOtrc&|5hs+V_lb6J-UCO>3@kNPHyG$6sI%&Jw?$>`^8Emny}x zQZbwA{!5j8Ps~6?FypoTQ!Iv3T*T|dDn@+mK9kQudxDN;7{J||^(Ju9UWZWka6~C- zPHT;%uNR?V8pldnYXeSyeKU#!XUZr)Z>G4N4Ug+d^-)%&Wai^qlv7L0WAi*ZH+60m zN>KW<$i^?xWJ>0E5Oa>Z7Pz|h%YHCC8v+S3AsO_injvnKy#sbv=es}qewHGS|K?Q> zPq721M9EsL=jC@FI;vpy2d|fg>9BVBkH|>-$ z9x8yVFXihJQ`TGqKfE|zuL9)V+|o26-szgj8au<6 z>RXS$sfPKggpsr_Vw7i3XFN-R=Qgi$XHmEPhw8)U<@6n)Y8HIA9{7T1`qInPo?!}Q zM~rMiz{p#lh5Vr}GA^*^L+IPXgOWHAB9@OoleF$7`crnzk+Lfzc8QFt3nc%0Z1%F@ zU){qL^;T3FCm!7qweNEfuHDAW@_ZA%uQfmv+O17qzjpj;G1Qa_mIKOmqvQAEg~P{< zb84HGG@W@7wIAhGZr?sqzH#)~Yuw*EJ)fvBD=aRicg$mxww=yzX~_VG(vL2>#%zW} z(@>C=Gv!+YK(oSp*CrQ^ql2S-H-R@aj;5nA`oTTF*vDv|&kZs@L401a`2HVicn29S z{OEO|{`MbsQ9drMSGuDpmC7*A4?-e=n_}{!=7FH_e$cbH+>toF?NVM>7LRrsuAC)o z$KHW@Zbr+1RBErwfPde!koNJk3_aa`w8=-VU{4kf_R|@0{>GX>O6X&Q2XxMi%-~)C`F%8ZvEP_P!+(Fc7RJ_W6 z`Qc~67Te5bHR&)=pkBvZC2w4?4oDtdUvg(3CR?;VYU1xQeKPY9+jJHB{u_U}CqKSm znIRlDEdKYKQJdmz#hu=sT=Zx9$#xe&g;}U#!np$uv^SeDR;5gQ}~M`PT~{nWExip&H4G zS2eUX0<@cxWXJ3Vd(~q^5SREwJWFWkD+y7#j=}6Lnl+j9fpbsM^r5)@+EoH8Ljqly z1i!fxw{InDDH90ENj5&oxquu}w1f@h95%pI;C! zE-u<+AEGllI*!#NG1ok)Q@@1-xC)cKo0L>Uu5Z8e%|niJ!y`HPk7Gc}R1+Vq$2mjC zbJ3%;9*OnuSjssMGRoMm!tfeKo;h(X@lKM(;}l&GaHh3I^R>M4^c0`J{8#J95YBwH zfIs6lZI|YA)YAk&*1+#ipi?KYJ&9P|D$Z7L$4pS0d3Jv)CDo>;Ok|qe@|n4ZUw^(L zBIx-oR5F&4DOJjJd$X^}Ai;AZj|k66nuq>LUc$sU8Ik?nQqbT!iu%S^I;bftXW4aq zUQPClr4(qw7-YR&>YK*T6ipoF6$W<~B<&Bu9!y+vU@ObJjgPwf3hr2$&&;nFdLq3{ zNHt?^|2Hy_)UAycsIO02W}0Kr*G-`5ccW(TMV;L|Edjf!Hv^I^*5r3XCo0Vevo#*g z>X4J)i^nxvgFq-hOAl%J(l^CcZZYs81`W2qy?m zyQ<3&bu2DsL@FsUB2RmJqm$~(bRvz*W-j<39Kn3C3FSPGpblr##%le-;Zc&a;jM-a z7YdnLw>PVz|F@FCe;OjC3#?bcTd4fPh^?Oio?THv4tE+cq9T6}g@32SMVX$s{YX~$ z;2+k0+vedplW9tJLK0rycw382KSNS``dU+ta+WQ@*!&$e${PjK$gx-YboOejh5w0Y zyUD*+k=I>EDz+~vpoaY?_`3G<>zr@T^8jUJcPGs%`?32Y^J`v<2HYVzQsYryF^?o- zQuQ#)51N_ zi`6iTANn|xv`!O50YoTC*Sy>MF9|x(2%528AS5N{L$m3J4zIAcLHARa(aw-Y8@;7% z;p^H-5DreJa?3Jb`Qvp3m)*aUisu&d$LQP~VRX3aDYQ6|Y`VfO?fn$LsO@n;QmaB= z^-ypGkqGj1Ya%(~s!w7K)y!8ylY$ZKWW|cc5R_*ft8PgAt`;<28VD@BhmP4p=6 zq78@CaVe7X%Y7gWV(9nVs?#8yxRYl~FMp%D!vETyT#*Gm$uQ+z-nsXoR$S>Jo5&Hb@7^_#KibseTn@#ldO#1lGQwM?Z zM?o>;iwlhTH0yz@(wT6S1D5S0F-~(G8uHC}l$Y=l&R6dsF32S`ypr_=_gD9IKGD&E zTh%i0Q#Pa=?kiEUzS8_J6g2Ig5g_cQYfi-nSH}vqKq{XO;AY=kJidTRc{=}ZR(Dka zBNKgAM9sFHPzl4*`pR@GB4M|2ts8RGIp9z0oxTRufluqbC|h<3-S@UU@!0X54p%W) z<`ZUK;9oABa0!nSz2d3I^&0m+Z03TahY$keSBheehFA6NbUzI4hGS^TO;30`?CoFl z5M@LuDK*cqt)X@qzT6Ywzw4`?QtVBtf|Q^fR|pT# zn`7pscgp9ARyA#C)dB|?gPr{oxA|{6QdBT|?5gX$6?CBe6_u$xx{!l5MV98JKWRA- z=-mou7LtxK%n0r}h)7-H&N{HYi99QXAo9>Vg-yEIEBVaWhb=T($PTCdRpkEG=5w1t z5)GB4sa>alZf5@fUB!iUL3&r2-zhf8jcqi@7gKNa)WUQh-CH^xHyQlz z$lX&OqXgnh7K?-nf{|&BguCPRZ+}?n?pM)br1(X{Ss14NAO+9oLs`5m{p&J8^9l&6 zULImb35`R=q+Go{#v+l-h*A{=4q9+M6naT*hy0mt+~%KhG6^~wpjHHP zl$8M8hpngo48^xgs>D_kw9b!`TM;LlqgWGlPOP$*!?8aK3m1WWPs#d)`GI(hyrH4t z%d*$(plk$B3u1Z+hk{$G7W5sXGe@dj&I=#S ziXUG;@~Ho@DDS%Zb9VcauRsIykF699hilko&klE39Oh&1j80cOn-Hl_!MZP%57|!s z!Av`^ss((YMZ2_|W> z0pcuwX~M|}rQ}1=jp>nFn=8Ru5@)6>;Dmbb)i@n z6%p}@kA(m+{1w8(kiR}uQA5)>>xb?pP;p21?Exj|`Wc}L|MUbC^oeMoLEWn!2Bp|A zDvOB^B@KKpkf5ZM<}qWu44tGlA!s?cs+`3Pt0jQ;efvrG&Taz>OK?x6%1Gr!?9iDr zXmI+)jUIhGnK}D4e67tvK}Zuq2~`iA{dauoj;Y*en%VSAuZFc-3!$u4Ors*cPX$mw zZ_&JS#M*B3XDot;CB;6NQTVF-gfSST~8Rt#^Bgt_)(#R{j&Fd z4$5zS`!l{RgE4mxEXu&xu7LmO?D-wxz*aFYglc|F!*c=^rPzs#cvsQq+Yk-Me1imh zijtv50uoH@B;WOTOPSFreK+j3U9suBt3}56)nsHDH;drCyK01-{CZd>0_Kq|-G$8( z4Vk?P9~R}R?0m7D)q{rnItcn4)$^OQvK~vlP;4;aoTcjaeX*vfz@|(j7D!-0F(eLI z*t<5&b{R`MxQ zLiY~!V}SI+U`QFPeqMDh(3?|0jT+mSGi-)7L)4BtXR}J&9%rmaPJG@q&^~z+-?rn^ zhrokvM6bxVV%v6$KTQ3s;?jR)n0+vF?%y^mZu~;3mr{T$m|J#cyK;Bc%3xBnTm1H? ztism^f$ik;G={vpsdN$@{-m2uEVuJ7BPV z%QC~$VrG}sX)qaKYCxTrm$z9O77;?c4JGPA1g3aPnFjjak#n^WOOW)D!dx%@{SA3= zo?(FCbbnoIvrCM8dGLG=f&R;C$>PEgvhd_VTHDUd?GTl+ur>i4+pLd*gPr-)RbtvU z-%y^j6x%U4{jsUnamgos=?c~dn@>FeG2`z0*bl)oEzq27#K1KZxX4p7D2yZ=vsmR3%N&ga4c z8&i5Cj5f7(!OA3OehRsuLI}zC8fNaNwAp%g*+S-N(vf@y;*|YCSQW>n4f2za0*<{+ z4ue5RMT#UXcKkyi$i`de;Gex%oSF|Pbu3$KtJ`33QcPujGCWhx!n9Hkg4{9H^SK@i zs)L&3hwEmhwH=G|u;oyi6x=maM-ycn_=~azYVa=3EG+ox{)*UcXT(_z*YdbZ-`FKlse76hIJr{ zgI~EUsx=9=gOF~)oOUafe~oRNDh!JywaJL;e@6AWfqKgxG$Y@bh^*omY!ske|FUWc zh7^3zysg;o6W?ZQg4f9$oFp4OdnfSIqf0Ve{7u4Sg|fVCIuE36RVD=6rI~8L0ugmE>pH+bdyf1X@Z z4Nc-y0mC%XhPm4%8?V3PSz^_~a4p;!Vf`Y=Kj?9G%bdxxe>hryxbO1e+K2pW4W9kv zMW4(YO1|FKNEk>0$)H{#k5kccq+@6hl_0fPc0kmezZUxLQ{LhjY4r4`EBlx)JNj4k zX6xbtY^cR=0ZCpW5IItrr-+$ipp`47>VCo2cz%f@1Tvu;9Yf~T3TN;eW^!`cy_vaW zU3(V*W_*}Az&rdGew-iNI<`aObL#+B|M;eT*k2mDR*=Qo6hJETKeCQ63g|a3=Yr>^ zQeuq53VvC4B}B0q$)F%bTr3`0atCs;q;y`7RQi6o5Ug4yfHbbe2YZ8&?8f$5!~q>? zMOhv=cvZ%n;4ndA!0mAb-mgsLgVgCyH{o3)D{T&oM8sh)0_mhPwOQ=`k zc-DHrH&)3b^qC>+(65S@X=N^Xmi_GvkA@vZF>W?Q>uB6rF&apHyk+crr~aMzSHFtg z_A0>7zd5-GN^{^RwB3+6z|yqo<;kYczW4m{4Tu1P-p6=dy|N$(l`AoBmRRO=qw1mV z5aDR#TfkZ1iya7`tQfZSRyM7D3<6#Kp`VF65MlbPurj}&sdLg#>NJa$rgopHED4d7J#QyvS!a;) z_rFgXfn50edqN`+~RU7MpLTWgd&5KTI@>F>hkBL zd;B?&8axpROpzsZE*jNK)(5j9G|!4w&DiI=T-Tb_wqxTc*|%&-vsPjMf~gP5<4WSk z9ttp{ZR*&*%kklUGjKz-fti zHO0OaNRW?jFip649iMw_)^Nqn@qV&G1eC2sCaDj#6@^?xEOSzztu_TI!IU}CcOyMi zheL;ID7GB1g1$;hr;gnt@6m2gJ@~o>U5u?C?bop3-#^^kd7t4PHF;+FkhylCeP5x^ zhc%}dMj9fC$t%P4!NX~diHN`_e)L}!E2yLE%6SnD7&vdr;N0BH>xbt+1=J?Kp4PF_ z6OVP%8c>(HU<1N#I$++6w~*nzx0nRd#?g6a-0#B4@5g#-C*!eTPwz&LGa+$%t3`uWa-^IE=+Op*&kB{+!2EQFBGd;jL)?*_( zoW;CY_h$}J(|>Ei6~kN|1JkCP=Eys*&Agii31|)r*&mIB64E%s8Qq75h5+Nm;5TY} zVLs#(&#}@||J`*)x?55)&vqu__LYBo8d4O0-KZ&Z|-d23b zY#<0Y^#=e2)wvD9)t|Ppji|n0i1V>=^DG6&8H^hoVRs~{1Ir9epu;_ zbCT}|s}F@gend#}k=@}3ib0_9V_gS!^jv#s;3>b1IZbM7x;~pWXz}rkJpwBXZ}j!= zw1Ghk6o9UPh&`)C=JKVsk&!AG-8eL#Qh)jKCGH5Q(6!#YY47?%Z*5}}ouHmBkqB@| zz#yLn$(AZ$b{iN}+=Sp#67a(3RaM0UgGPm3U~~$4O}P~naX{AfvX>C36~!SOH&YTTR_q1QvIIE+?Xk4`kY^8thWH$W@?*=F>+Qv7{!XEuk{Yqx*Z;302@ z1f}1@H=Q1MSwuM1E$hPy?|U;K;F6KJw;PhwoGw^(`o^7MD@7zE5B|3%Acne zZ{;|@W+uZ?y#sWPuwLxvYL9|U`@Edfkhk<}>%V-hlGwbFp+8NV9vdER2OlCUGga?sut9 zA6pYoE{c4~s!ph`+5DcPbPuma1G%TA&4g+BKJ`>$ogjuAx9VxAs?DgO?M$OrTWtJn zOZdA5Q!NsQGUN1r>vP~4+?ST!9fhipHAHq{VPx&R-!$a^s`__3 zKqt&|`HScc!$%xon5?X<7H*o$;5+>QT9^0keRqo?{=dq93Z_f|q`Eowfk>_XeWzyH zei^(nO8{!{S+X`KCkX7rK)~{AxoJB#hidAdD5_zdSrLc1o8$Xrlc&&VK6}PE&l^(2 z;W8Yu(1sNi9UX|kxV1Sk7<=yu-y9z6E%Ix7l;=HufYmGi>5tPQHsht{VBQz!W$p$0 z=9zZYXkqGV_weZ+tq<#9^hq0Td8&UbX2?j)Y(MyFG7jhh4i26@2pFxoZ8QEZ=x^CG z^iHmW7TgPae;}H{{mP6$b!v3^%GPVIP}R4V>poGX*XdRrvd^WqXR5Wyl5gey%}&ze zB;-`S!s@1de1`XbpXm5W&haNI=*c0_&k-Vjn-92x6@APSC5`MaZA1l zbW`?i#-GDP^3->t2O@v{almU;pEd_v9TK16k=;ldNm@=FKR#2P1ACKrzWwg+{p>d(-@zKp;iz%``blXMC?6Xd8tN*+IS4r4upV22ec4Kf`Ib7!%=GN~#OK81 zWJRz76npgS!LtWs7)uxC&wC#-*?JP(Tlb#z^7g&f&-fA3ZpwcYf=Ch}{(cicyttXS zL^?@om0Vg=Ch}Pmfr!4mzt#;sQ(>{!lIDc#+*Qxnmfcu>cMaU;5Qh&*<}b>qMr*KY zdnBHqFYC1^(fyU1_3qz~7UwwnDk)k_@_(tWjz8;R&(HGZ9Wy3QL@J`|k$Av|{5?rB zys*~!7Z+;k`(SxjxwTf--ChUwud*_GzAde;`#*i!>>fjjRY^@lX^xbNRCkLJH7lb- zN1%jw*7gY-^CR#V*GDwX*{b%U@-ga0WZq@oC4;g#Ip`MAaa9PXcW4`7Sig6=%#$*#e@#U_RIZ3^DPIw^3-VoMQVIqg%wTS^s z$nYDPH@sc zM{2iu?)+D=J zJ`3g|YulDlyBNB>H3 z&y=5X*<`?};IA3y68X*Du)t!z${jU~-E-zpKwi(?Ph#H`;xW_u({V5U|KaVeqpDiF zxKX-81Vxk(Bt(#wEP5JgI)TRNm$1ylqHrArW0lvF~xQ$PWc?(S~*=0ZHLug7=X zJH9){-Q%2pR5p9BwVvmh^H(#(q5O1?*PYq(&j1gMpRcTsWixTDh6cIJJjem3pbzDt z>N%oh&yW5`w9pQSih!I@ERd|j{_J(*9i~~ufqj+R^{y=H_lp~z-WLelP9S~vX_YeX zu_ciCNdr9jEFLX&@4oe&a#g&7HaT@mes6(R+R^#l@KMQ0FVT4aYu|4o8s4Hxc^#M6 z*hZcQv?L^mjK-Wfpy<@B0w5IDf(g6P9Lu-tid?y}=4gyGIK;MJzlkm*nDc9;T?}8( zASz$n4gVO;t_@XjFl!P<$`!SjQkO4#PmD_*qe$msWPEUm@vCa?>ZBMewg~UT-aS8z zrem4iX^G4GlQAmW6FO=Q5kJT%7?CTIb&d;96z4-rBz17{7w@j+_g&*({9kT8X&M$v zyffL2wJ)%jCYg+#!iRt)(6!ydm3s`{;-(k@?!Jy=!I=S%>!J03&A&XHbYoJ=MaRVe z$N3fQ@K(-FT$pyYR!vn(9YJU*PmWj$+3w3{8`YvN5N6~%0u1Lp<0?%()2Z%0rDioN^(z9 z13)b0P)w*<=t8~FO_(T{6VE3CTtYz6%G~HehA!r847#5O*~PTt?y$KS{lHZ3f5b~+ zIH1lbad*8cmME3|I930frbUkXMIKRuhSN0D?w`IGI9rg!t9f7Go_Ov1jMz0UP(E1q z8YgpH2p<(*GtZ9S!KsUmVnUbp8Si{AVA#)T6IY>Q*T5sy!c04VN5xr8?ykN^!%L!~ zi_({mSeerjY#;#&H?fKKjgO!?wK>eIrBTJCk|2w}?hg{B;1ikz7A%QdK^)UAAm*y@ zavnNSzms#^IiX>7+CEDDc$?{Wdp^357a_7bTK7AY_ewGi)scOEZ(oFjq#h;fX-_+= zci<((MbuNSLCj}N*rhTq4xa<9HmL$Jsx=(p4{ZdOE#!_YC!H0Y`$6 z&ucLe4%9nwoIShFt?PMYmn5!KX}~WLg>pzl<-$D+i`OOnyGiOQDp=x@lISS4_e%Ru3V_A@TdZ}WEG?~ z410321n@md?W5RgvEB@h6Jhv3Vsxe(JF#+*CbD<0AT5fV?IDS=i{9rmzkuIM*yGKy zLS0$<(xVe#)Hw_B5>{>_XWBbDY@p~OqU0CX)TDypRNQbH2!kEvfu^GjCm4;Pc!mdd zD*cK7^UItRJla}PAwlS4L^Mp;Zq?F`7lSW{ab_`d$(?7c4t-K_PC4q}SidONTw3{s zhaoKt`&6DXtJizeE$aJ%`UnubznX@-t&0Qay|vC9;9X00`WCoc?Cm24 zCch?a^>38a!o=4)ps3=rWgA*EEuz7{Y_OV~PS-`RulLQ8MQhg(#Go$wzJO^DC*6~Cg9sLN;HSH zcO0B&{tuo4r($GRjw=l#KUiM1JhsMARb{`OI}_Imzw(^kx2$qevVN%Q6+7~KJALysRfu%g z-`@bgkywg`cL($q4(;+_9ogA%nepz5M&Q3k6B~KHbaWJkfD6689=;5t)>gg-d4wUE z6|q8&*>)2Oan9ouY$cm|`#_#8g2h&}<34P_88)GTtp@selWXebZsn9~$5miaiX5$hJAoto z=zC*(I~yyrIW5^{oopzKauEn3M3a|!Blq6Dd#{p{AHuo(HY>;>z}}r1Ur%F z*;>KfQ$>!ZtLsaCO?XkoZ?%nlpKZL}RpDk2gZpxgQSjSDY>DX1!_$LvH-}bA@Ua&# zQgNXNrsIYw^Ip?wAa3DQ^OGMEchxX=Lgx%@>9$Nf6-H z22vpnbyChUT^HRsJ+54AM!;v?88{kWR@6NmT1>JYEF7vp3D_gy**n>-g~4K+d5GU8O%12eo@e=;KcZe;!uk<;80y7>nWF%H|<2u`7~JuM7~6Y5Q%kaVyPJZZqHB z#kmv5Q;W}j>SGE)*wMxwDyuUOvzf)o#XwAnz3Li5ook__t=$3x#JJXRFNVl}I~_XT znmTy-4P?I9`MF5iPbzU-M$2KJU-%?S<7%wvcy9Bmuhq<&bdmf5NEu&6khRG0ToLwk zXbEP`>TS_N*}r*=z%%6nKX#2zx~O%OH%MD_o}95>CHpCWjJ%CzH(d2t z?PbTpQ$LABj|0HToWv`i#7V~MP29Eh6D`1B$Pdx1s}-f}W9P?*5=_yrV2*vp@xBy1 z!d!P=!LPFLe9)IF*+n?M5*SSVwUc(C{sj1-3>Vw!Y9X?{RD}=NPe(@wMNh06eNXZw z#y;Y*;2~M@{`c^Wj(-8>JP$j?ihg#>dN&JwfLAO5)4eKm)dRFou)TZ~SGJ8e454s{ zGqFh+KQQ(vQ;Ls1x=_xypKj(ucm&G%^XIQskI~EbGJW)SdcdTYZKh!_X8&elsqWY^ z%CT8bw46cKQ?7Yk3k&ocbf&|Pe~<;^R3{Uh$tvd2i1XV%BfL`}^J`mDD2AsX8o^JI z35_sO@5z%Vr(jT?s^rMW37Oa)^ ze!kC=8t)+p{noG#KAR3CR|GF3q{1#DhOH*o24+~{nyI0oHIV!uXb2ohF1$eJgRKWT zFR_O)=~WXbqY9k$&E8;$s^>5bk|%kb6cP45bT-qDSm~GS^mqjFjsP^i*T@SDy&)DLwQa08rVcbL31 zAuDS_?47*4{9$VwC$jT~g-NpUP}LIr717FttVh_p>U^%OEF`9NR6V;9gjE_{CYOtC zP~rPO7_man}xt-3p{S~?5}gb`%+Ab$twPwMA%t~%&5 zKvM4VQvIcMW$Q-+nl$+u$+m@`OCyj zAdo*6S|(>iLX&zT^GgY^cHZD;pgS(j$vi9qM6wkS$&`v{q=SHi8beZ8`}gm^P6u&A zL&Js(OmuXndVG>5@m(||^WGHiuv6PuyU~{<>vr1E+hPxn338N1AV5t)Q{J#u{Uz`triU&&(`WT{c%w=cJ^Dc3I?%?$rV@d{NW_0p z=fs+a1sGr|r}ltU`~B%lR;AU>(!+!>kU@OyO^G0VVzFHg0D^VkltUg3$b15s>XR^) z+gREhr$&)Pwo?Qtu%0EN^pTTKd@#cLwcg3)$E?HLr{ANU-L>csKDiA2A6HC2yHt_X zZ+B1bGxj*31AJ_Svs`W^aRMy>NOS2{Jgl2zNzeBIE-VNJWfQzrJRdfH!T(yo$7*CH zdD|GB0SAHukz6BJF~^+mqHx5BOR2*wWdt3C?0;W37dgg0bbz2^K>~6qofYtJyK%Xz zfdLCr+z|Oz*Dy*)7vde*j^2hFWxxQ}g}(H7K_8{4Hll+=UZZu}pZtR?dTjEp%gU8rjd4rH}d*Y_) z>3dq9duz$f?ocwr*mG(`Sq@-0OvSD{dhTJ@=R1bRLW8E9^4^uW32s?Z8D1y*6m^8G zj;vAJ4#?EcGfEXnA8qvD3S-Y7M5FfD)SaH5-WJYCPY?8?@rb}@%O6B`2zEX`zCPt+ z!KX|g%YYfB*&wsRic|oseVwj@{Ko>+y?e(PIpCWSpu3ckEuE}R_TM;cKS2&Kg)y#L zx~&ZOBZAPV6}#N8utQ)SB&I`Em7K5NNxzgO$97CsbU8SP!?Ks3wQ)GBmU_mf`Q=58 zd`M+uW@d&)={bNkSuj?zZV7_8(jn3a$Ry?q7l!p|c1{7>|Fp1XzOQhr)lam_pXA(| zH*W@0qAeRHUqswuAj8W7AU7cXhcdlJ@E4{xRuz+IIikt3simrwVT!$S^Ck%}q~^W(!H)gTevrFF?L0~XpmzI0 z!^e*wk!K?P^YjIH2(zhc^DKI5rc&dZhpV3gBO*{;U2Wd|@$v5NZk>SkR)Z?Se{I46 zaRbn*LqzT{4si9j4)sT3_esgykXaJsx%(gr=4^nuKQuJ7(ju?#`-0$8e}mX`OP1&8 zn|S4_XbwpfSE-+_m8`@rEPl#xe`eVDa;^JyZc@^Nz`($| zxfI3~ViyQwTkT&x3S$e@SggB9{7Ay)>6tZ^`Hh_{)->r1MaOiXd5V>P(R7X3C@wMa zQx>wf(|O;@M}A}6h`Dl~vYq#ltB&t3sZGU(uKLOSGX6<(`t~I@`;H-O$^#SDymS>3 z(J~@xw4V7r8@xyiqdE$b0uM&9pUGd_mXN|GGX49Twi>H_lCfC66P;ju7sB4MmuzlD z``(B??v8}fgiw+6WneIt0TZhZyBdlgF-;19t&p8`>+ap&f$M8eEqai~dAFx@?+k>} z8Nfk;%xaFdDv7+#R)FDk$?SV;M+Xv9L$g&3ySVLaR&DmZjtdGxb37^^?o`(^#W#Ut z@(3$a0!}fB$g9b7w9u$8BqwdJI%`Ntv0)yg2o1I6ztl0eF|)-Q7oH zU}pe*zw^w8JV*r#2)hv{90`M`c`bXdffDj=>~&!GVbkdiHGu{UR8s4wD#RS;??Qwf zaQ%|WP2gR$>K8tJ=1kY;`)0{S2?<`2+{W3S2Ohar1Jumy%*;d3PNu?<^vSIAswe?m zn-uxz8t4ismAP16KcBQDiwnY7f_a%EbL7l; z=80UyL{vnIDwuE(oXwl!7{O2Q7~uWvFTrL#i2?Yo5(37hfl`hw5UZC9BsK4wTJxXw{H?$ ztW3Ow)3jiXm`n<~8WIZmWVe--IrXY=5WvB3% z7lPW-om;bBDt6FV~!{#9&5q#KuCv?OcTUFe7)A_@K0am=SR$Bl*WNG&#v1v6%`?J6@-_rh_1c8VKWiy zcni!^2=)VqbN55ZDkyq=`>6XJ);$zdow&xu@3-h@L88pgml82X??}kusKqK2aDyTo z&MJ7>8pO#SM&v*l&t$vfd&UxFkUM^hpme( zyCEjBEF`u&L=0^lLj5GcK?5R@<(&9ER@>f%jTP9i5Y`#Fet7u!TTRBIm3gqf6V2ZE zt?}}C`zP1ltTo7F>>kOUPczc+Bn{Zh>LR`^)q*~0t=gTF;BK)RBd!dk?&smVrGC$Q zI9ZyQp$n4xvn+IRIANP%c8DB}`lr!9_D@#cGa8)ETxzsyv`e)UH9s7N?y~!=T+^kWXSv zu0LNgJtF`>RhJa4uev$U%Ww=`vV(8~IWnBZAHA9_4 z9bxa?7Mw4dwW58&nfcFhRuW{h%p^Z!aegM&(lc;Uyg@63M3S@1Ay&`4nxD01aS93- znF)Q|Bg7$QIUj+&mGdP?sEP6w{+9SIXbrV*+Lz|(jsj$u?e*tVej7L%`e*^7cF(?9 za`$%g>*>5b+ZmT@qcax<64qCS^i|i~MI5Q+{I$!l%a)}`LyJL1i|O{{I1Tw>J47;7 zqx5tW9$!36Go68Ft?S3twiNf}L5KJ{{=s*q#1;7;2NwLh{sLkP^r!X~Qo;?*GaA(Z zCMzd6mq(n2opSi_`zHrLR0vcCn3$MqQQ-X>@q;i5&rsWN(Sxdu{i7%5u8hm`|yqo_Piod7Ibu|l&J6Y+u>V&kd z>>I<#o^#-*2 zH|3r<{j%XB$p_FvLDzfT@zND~*0&J^^M2`lgZ35WLKUU_r{8&CJ`9YBA-G*0VJMw0 z*LCZZb5@s?HvT8o4az7YXwjl8C*ESG7_b#<1Hr0ytIG8VmwOAu;*Z=fP$W_CSyGC| z3r;*q)(Apuzcht}>zc+2-8q>P>?b`TDG2;B-@J*>1ihFoiu3@mrR&CjZ!?l|Mn)eD z72)0DL|nOClrIFEA14njKkc+YYLve|-O>TGXABVPW0!d9HNIDAO=2xc}={x@xApE zhb@2X+)%XF;!*D^IXNvO{88w|b`&3^aQ$p=>8p9*G6KK}MkT;q!{r0`96^aZ&hUkes_&Sik>sy;wgo%hF>chc65hN zuh=ztZpi5bs=w^VNa;auGsRBj-jC>`w2K2&sNe{1C0Rh&^8dv0tgWs6blB%wu`bNf z;8R5>J(}Nrxs}rv{bp9)T<;qd8#O2uIQDeL2-RO)x%CVA{s(k{-Ii`xSKvG9`}7Y} z=~tKEd#Te>xujpA1{J6wp+)h}y`Nqmju^TJ=MF0h6)bZDo!GAW*tq?zi=iDo5~4rJ z8ThAI;s}ep8#t=6?Oj~}MKl3hbQxYg3PpK}yEV$`(d3z#HPQ?m;>%2F!y2PJP z)4db6kFDcd>6pKM>NJmSiq${Y2lq~@q+`6sKd0?ZxW`Rmxq93G?�xaoH(lgxJEN zaZw}p7~UgrcY@mWw23zU#g@u`7J2nP)r7fAO6mO(d&j5WcsF0Tu7i4{PDwogdg@$gLjBY$?1JAxo+pq7mqGNMrY+*9&TTWRE?e$qi9#IP3hNp zYyEJ|Ezn(KB0VlpiT1rX^7C_`XchZl-y6e)Og1D4!K|r& z*-GfZ;rrpkMc9f%XivW96oUkym3XPFA`rlX_@LHy z;wlE5`zG#~)8T6(#73FpbrS~B>tBw&!ydF=3|swfc(xZqm%G#n1x4CY=E~*UM%L21 zBS^&1;fnz5X>?rHhS$Hig`=p%b*c2zP;vFUJ2@e;GH)MZuQsCl+Ky5 zKTb?Y5~j!j3~v4B>bqqJ51*lW*vpqGg{MPgi24c39cisu$+U6(JRC*`aKC%C;W5Pf z)M!U#=Y}WM_9Yu_)}-3ou2ECp+r!%8r*}-9er&SRuqY` zyqvdVofv7_^#L8-eY{Z9mfRf5W|vAOvo=>6XOY#WlDZ}S=LQB(NEMhfrqX>3d~^tT zdM(yhZafGMe_+VaDVb^hc4`c#buqqm^Q;=C;+`?L2)perp3}ihnCj%vyV+tEv`5* zPq}?2QM4#NP`Af|op5fC@a3+OJX+4&3A-N4Kx!pK3WdD3FH3^2Ng(TK6VGlcb7Qoz z3JuNVa|;$Dv>{&_$xf}DffAx95B>G)rRKSi1ClFW%G>k36y>E1*LbPe-C9RiZSglk zsp07>=T5GcJlR&XCXIOX^cy$1@jEj2ALfPqK05C9n6|cM;o-UW5bhHy^YJAhX#Zj_ z*+n|Amxk4Qcb$eF+58WS$%OfjOmFUH{s+6eZZ$zPEijNp;D>x84$vDE+(rg)sB!uC zIx{;qd#?kIJ@RSOnR$mr5pyh0d|$W?KWE>}h+)xP8;kP%J_cDVwjp1ce@^0T%H+Zw zDUNk&Zpz|8Ii>Hr=h#^v8VyZ&JN_`?;%*+*ipZ{W zN938%E$*{czFk&(W<1_+`@=&p|Fu7-`aaM5Z-DpV1o8zDL^Qa^*?CFCIlX9E79<2t zx(5FRkqeaR9i9$5x{@m;1IoTj{PXLW$aL^f_)ggjZfYPo}pv z-9aIil|~Q(*}MeX*S!}PXDTq?PJQ4Xwr|7d0t*OCePM}~w7)+Cfqly!N-EHkn6L8b zjMmCIx1B2xm6 zeMDc0zVUaqBW~I|GNANeZvjRwD5|K`6imc5BHtD$1yr?9_fCKhwkcMK&lc`ed=Ld@4_v z3~#84z-sOT022D@DnVm&ed#5A@z%wNYMQe4F-smRe(AtKQlN?x$;q@*w*lqnfXmRq9tr*9)(x8Kq5L%qKs-1%^L zdU?%%9AjPqiDook5J-V?EuW>I(o|F|gKod8)Kd&%j)KC%!@{h0mulPk`U0@rkL z$Q^8X0v@|gh(r<6+@Eg^5P=39!oq6cTA%BL59B;`CdeEN80$)#QJ&Y|?DD!Lm3pjN z*t+U;^D6YDZO&vc@QiD{_Yp{uwYfUZI}U zNBKE3olaqtn3xgVXPy+L9YlUA$4+l$1P?8gpbu1ZF1p8rq~Si>>S`5LSQm9NrX)I< zSie)QO6mL{@{*a#DCf0x8`%`MYc4Ood!8Ba*09OUw6=c2R{d^YtU9zi?5hPH)&s=O zG{1)|kvB(%tZjlcAhr6D9DI@C-`373zd}$;hL-7nF#4;@W{(YS6F1F+D5MEglFk6X zBJ3*64oil}`}vrkMvu4ec^(IX0%3iwhuksHwdZi=K@l}RmbY^z`v01EU{C1>RI3!) z(6xyTWyg%e$p>vD)BT^ib}jd1j(NmUDo3Mrh<}>$o?5vqvWY(-b#i#=k>{&GZ_dVR zYAcXbvgF|gaVzl|I8WHnSjeZX92N-7RvmGE2%W>nsqVybGO82wh@ zjyrugk-=H8+dy3{mi2 z1GFYezE{s-v~7lS%g>@G#%20#u$@Z!T^UtX)zKKpMDQh5;7{y?3^f^JW8=?hXSK#L z61jUT1*}|LWH&(knO;N6c^VSW{TZ;cWZ*iN($BmHj72pm-1?mrbrZdBMW4@1v zkI$}6o^J_E5;>sTMCKeUBU;XpK%qc5fzUWCx_Q`&7A4Y4w(n`VuPJM}Ofi55R1i6F zLCJ(&c0%SN5Bw_0Q!=jqvj}}hX)_sDh%^E{`C`83{mD)@#d;_ zZ84<6B65?mYs9XOpH!bG)@FAYTh4wh($eTo^ITu0X}9}FXvs^k-1BokG= z^If60>DvsX;JcCh^WBhucHE|pG*xcU(Heb;!Ym`?>xDtKIr(ERH9$>_RDY1;6|qsg z;Ep&?z>WynUF=naa~@#oh=isJo@;7^j7GFzP(En?W9mTUBh4`ay-p*~j!Yc}bv-O0 zHiEp77X3V-ta6_q;6R->6Cw_=08#9JA0Z(YriHF=2@?;Dr9F@L`MuEZ#%f)?%Bg;&5syQ3=dEqLUOlSUG|nWA2t@xdw8f^O z?bS+aqH&^RA<`z*$W4xM`b5uW!WJs`z*K~xq}IjYq!&wB%pr!qDSi&oW*bW2kwLpr z{!QY{H_chR(E=vupC8oA>o}C)Dln-Pye&xYIg>TzIS2t$@8=trCe*fUib<(F4UK9I zw2SpF7qc_y|A}SD+yE{96hgfLL5*n09=x&B;7{a3vt>*!S#jm7-T{9Y0dg{ zP)dUg9WXkRhWHmq<+T`X7kTZPn*~}k=~nc)6i<{|AE$JtWe6sC{+BNRZ4}tonTVS4 zM&H`=q(y3c|4MkyaUyRvu8dU!@3l6^&OWD+#=iWU?Ppy+Q?dLu&$gH~x({}K>bOYi zC8%2@{QZrcoH3VgL#QfWRrtpDLM{pwHlDqj*>LwRb7?I+2GyvG2966=NmD0axFhna zjQWSEpb(<*A>d-q5Rbc8yjC{*!O<|YrfJD(lQ?tYxYGA+Vgy~Xk%0K(| zo`JF)wS0yeNl^W}A7u4tPh|cBUjl%0#8d>iy&|}wrR6Q$u?^WGU+?wY@08wvrg{Co zk!RD~b2~XVt12xQrVF4AlF2$0o&M)tfU)?UoX{Gvzbx&9xvU#pCR}g+z%^n0j)@0e z)B)a3iFrfxfu4&BuNdZz=guC!yo^*^GO0_w`o?>TQbIf@AA3#1`xk*?R*# zERPlnj-8(Og*eVZg&ZH}jtAp0;`f~tS^Zyi(LE}nps$Wmv9l~!SKPpy?4>Ne zQj67QW;a2}ZF~es`O^bfe+>b3!om)F-fP|3d>RKFYL^AS`UwAMb&B6YHOc4R&uk;Q zq#6a#-%!Ls;Ci+>LOw{2?L8Ok31cWYo(G&mG+Fea)cPO58IihArC(wEUDN)wO_M6P ze65)b2V#li%ihccxp^?+f4>qMbkP&!ze)AAIwF+&VyB!bFltugVglq9b2Ba#voWPV zjzerP$V+CT6VMJMDH=-MfHQnV@i%ht30y7dT5u(-!ZD)-q@0s6hf=4eOb(>7QVQKLIxI8Q1jY6{pd~{9h7& zQ#5T6ytRC@Ugl`Gznn@tiZBqTxQ*m$n*Gi`NVZV^Y{p^E{I}(xLQ8WN;r1muwSG7d z=#;<7h(1y0SJ`Uw^UX*o?CZxnx%k#DFdO&qf|tH=Qbv=Z8q#H)xf6zY8QA^6#rN+! z2Ae<0q0~Meh&q|9b!)U79S@foPPxB+20${u74rU~*sjnQ163AWHA`fot-p>h`n>=1 zAxHzZs7$~tuYmCaN&f`mNG37x{-C{=C(o#yjH87w1030W%)I}tr6fo$L>s1>C%uE= zPa|rnKJ}rI|rKU{;#*uJkh zO>^#%e57uVBsCz$=kOJL3OE9UjtXVE(TqG`Dy>v8$X%-64^|%#9``F_xqkJU;lY{ zU-1nxSTXx`L5lXbXApvb{w*?q0A1x~i$12YkEYeST_9DriwsEM|9#PcG5-x!r^kFZ zxM)>w>KpSm#e8*6XY6v1?AhH{C;1sIl*!=7RsXza@Z`B*nalc0tT-=f6btuMuRto;Cc%N7J ziMuK$&ZqB@Kj=FplDB>j>f2qO_osS4KRvqi^a)VVB7yhNOhdi|5Z34&%X#PG+jjH2 z?qDj~_)#c`8b!*uyu51~_$lL3ePhE8t!FMX{%u0p7q1=v$IV7um_NnFdnbTXut-bX zPfM9?Wlvbu{!$X{MDSfa6P2jn!jfEzY_IQ#Z8iZmG3IZp=^jqO6^sX$kpuysavk`9 zdtWmv2$uTuc}m$Y&sfT!mtuc(yEvmXU^NA?uoXQ{FO{!A{2!>C7pXL2U_-Ae#%~qZCDPWU9 z%m(_MHJ5p0!V&0ZrNy>y-rWL=e*r|NFtf3xzzk6c#cAv9rF3leB|O7F62M*8(qg>3 zxzr0iW()>9*$R9DMBXjAu>?VaIf(@jJ;6JHf>`>3})1xyEf2L)dR3eR|^yT)G~EY zk#UfK7C=_7m`+!=VXxzWJG0e|6i`nzMR1-28tJqH(Fd#cz}G_1Tj` z{O^K|8(@jR;am*~N12HC6oo7nRW0X7*V&81kfFwa9oL9hBNL4Sh2|3y6TP#uvmb8s z{SGs#*xIVvEFWoTYjWr63M`$^lYx}{+{>Lk57x%%EWxm7<^|EEdsbsGxwh737;+q7 zt!}(YGF1NqIAOTZvdJrOALdLB@rXVYD|(e5D|AA8=Z>96xnJToozh17+UEMj>U1^l zSXbFiqO`@X+`Mkk+9~06|0jjRW*`ju^q*Q;?f(qV1YCyU0wVg8GliBNfd)6=ha7@_ zN00;p+eQ$0Fl@GAlHx^K5%jk>7-()V%w5i@C^z>dn2z$Z#m|<#xta9l!-r=vh}J&e z4u8q&JDw1~A<7t-)&VW{2q_I8~B;DEr9uRsX)*B?Jl zF~2uKix&++r)zWL74Qy_uh%%;kv1~T@qeq0)dQFB$Nw6) z%UvR$Q?qjoN_S)C_fm0T?`ow&OCY9`? zX~jca6o~Z_n8yzT;Nz!W)9n8WpJVxUx#pQn#>cm>Uq3QXQ!qc>E(yEES81BDkn3!y z$eKi!iQZiIr{Ds1CWV+fSOCkTv+I8`F@Xak-x4M ze?^3&7Wf=*bnNqNY*<_eJ*e)kv9uO=8)YBwi9YD~M1kTui|2-E_hqXjD|qXod+f~8 zT%5GYZW_OHPEijsh4@x0;|AeX5e`JSs$p@9SPoHSt3>}oA{l#Be*O{QJ-z5TK&&h; z+d{*6ZtK$(t`zKXeD)&5$XrY9YM#tWhGzp-m*pgyJ%6yk-cnbWfe4)51xIVlgB;e!)$yu?xakYAh+f$qfXIP> z%k~!i2o2><_7NsGPE%c61Py0iGYccerh>J z@}nD&4<-N`5JbX1i$R01gOp^ zj9wk@cU^c5fowDBg@KLirNUgZyH8lsbzt!#@K1*OoEfqxk>HWtML#jh&%Q2d#>Pw_ z+k;qAN*QCPsE1`RWkZ1Be9m8LXBRn_ci7{wZ~=lnnPU`Lux*(?gaxou^~Jp2kkw0w zxdq9Cf`hLX+4>PvhWkbzxq#NKTNNNA{Q|1k2ySB{aHO2e>$SxP)=tLRl}jGzD!9ZV zzZcigfR)SnYdvvC!L!Ev z`jtP*)H-WD$1;s`C}#qDpuqhp&$>c?jv-oGi5M`SLrv+L8TBoh2kDL|XWY(}Ye&v^ z*PZ?A-3FSF4qPQO_|Hy}jw=A9M-$d%J-nM8_3v6qQtsY~Wz=sMMng^pqFV)_?HrTqMcHCX zExda4=5*+kyN6cp1FwlYsGY9%{`IQ9k33p4e7I=bN`6dce{?iuy)9=5_VnmJKzxSB#uB`!Kd z`2XWtUoog86-)y~A4C?Q*;}GZ46^u$D+`)2N?!Tf?}x0DrFV#8oLU}6&QzM)F-l^! zXwV*A&u=u)9~(SbUo$$x&-kI^*wN>rkoC4#6)&osSm88kI^`xh_Nk3gP2VHt?Ce1< zvzZ#|BYcPujKMWcizB%B?+VB_0`eQtla=cX72DalD{FRcWn;ix$vyEGx^xW5RGYaAQwGZsZNBcF(pjm{?0qqmX8i zCt`(!`LYw=u4dw4n0bAPQ7T#W&sLQiff>kuO^q;_Tqx3gq^|7RLN}?V-*7L3+9S=v zFDk)3wu_ygyZCS{5& zHiS|~q6yRj*cxJF`b>so>cziXd_!wYGr5KO?AMP&pU>NvUEz10Lf2;gfn7eu!D2zo z1R*}>+IN0kEeueMV)X>8kU0h|95~v!Hd!dH>gEjWcel2Gz204cD@XWC3r>OxQK_fk zxd@$3xTPmJfK;=g45U=ZzF{N7P zBs9#L`F{1glrXI!Co>)M>mR>6EPrMR!F~>^GYnR3a@e1j2e$n+H09Q;npyHV zv)uANkrp#gLZXB4u9kSJJp5}X;adYwVSteoP@paU8+R75;$zFrp60SNC+T#1a_QIuO z0QHmnV{{Ihm$=v>@rGzONq3aNXeh42PQFD})!eFaSz{y!b@Qrt`PqbrLnFva$6qw$DY<_d&Oi zg3`pJDeV6HB};e1y4S3XQuMF?Tx7`c^N)y*fAQ&$i`JVrbF^&@TSki4^5v4nR&=n; z$}FD{sWXjhJbD!*O^&@BlKnbGYa|}Mf}JkODoDHOn(wEuD!64af8Mei3>>P^bW4ja zlK=te2gybd-(gc5eo>2g?Eli$A&SZNW9hi;Q$KIQ>7u`TrM0Bk|t3^UM#DFp=r z^D#gQTGvn*KaY=Z*<2ba0LmV_(3IjF86H(1CMez%@JHpmca>bJ7t(4C9WhtR8@TK1 zoAb6s`5?zd?BUB&l#>A^7gH1t%*Mx7yRB!%Ur=17=|z7?`cVph*srrO)3F_%;|CI1 zzw-;oK=R`eFli1lu|kpg&A36O3+@XeVh1Z?hbfdx)#Q=j$HhO%not7zj%E<$)PwsF z(OEfx2tys>?4e?NOlfuRo?f{RCa4{}!D+epfM(YVJg7DU?i++IJK0*9SkqRQcB)m& zzBq4ww zWk=lDTPe4bppgQ|!9~QQ`h;p#A538>bRP7^22&V1LR)I&nh$}M6S1@F&-WIfz<3{# zyY^qDdhd5?0%U$@uRc;qg+RjzDVXYD$pT2k@$M@ntOR#%`(lgrr=$clH2x$L;xhw@ zW4NJC_O1+AW`kw6lijE=ECHZ)_FaGVT_!b{IwxLloM`bv{nW%@P~wo7&S>?xAe?9| z23_A)*Bn0fB#be`L-xr<^QR%q-`{@ZEryXNhP zfyFO=LKB>P-i3E=Z&;T8O8{lL1@>yl>qWm8+OeA)>CEMLIK^}o=ud(6%jY= zm!z!uILoyWyj?q)#QT(m{84h0O||v+oKKgw`H;S0(pe4bvyn%}@1E0J(3kLMG@xf~RC&sxQWB8M#OQZZ(b2xuFuZLnVBRxYLBKbC zy{~9xT}X}{Z!pJa^URlaw3ERMR+HIJP4Qx-oU3n}Y@+tuu}WdE_c2Z5emo-Gp*V0` z{-!nFBX0|okEJ^&t_EnzLO1`SZ2Y2z31L@?eA3J!)h^K)NBP7{Zn5QVF)0B~&p8WP zBVB1{zQ325wuyqgO9%@vgh8e)7WTZme@6kPd3x>gGXZWtF z*!<=zCLHB{-+AOFE$ZfhqPHKq#(V|w$bJNyXiphxO98Qh4n)xEEfaw<=lXU0`plRg zJa7CUULAsC8W_Uw9#`!L+cAvLgh1kn{hfsgkQpLU!bAX3{!0Pnc;UhYHHZf2ylY1Y z+nWx|d3mpvMQ7`VNS^?S1kDyQQug7ROgp+AK)00q)?N_Res-ml3eJ5*jSco|>2&90 z-md$3gF>6J4?Ve23THKbjODGC$`cNh3og!SW%NYrtg#rOQs#ZYF4gyq+9+pJ^AF|5 zZRA6XAM^92snRrVrDkG!=sA(4mM9oAoeJ}FNd@?nN~-H?tWt{F8GCZo3mq;ZsnzW) zzjS@O-DCt<>JaJByJMJ=$9%H@Ot*%z(OAnA-)D||*jg5cxwgOA=s_{KwABG(F>p&3 z6~)xl)Liqp7#uL;t*)k4ha@Z@|05%dmTGBQ(20f1z#uCJV8Z?T_iZMy|36_i0TiEm zljK47g**Oq_1R~vs~#BZTBw=}5nu{RsxK8kQ4(Rspt+IVQdtL+O4dIqx?T#{y1Yvn zvBoF0kfx8{?)L32)A}8dt;d9;Sg==?n7Qs>?2hxv-OLuZM#re^#J%mE(IBjlwPJKf zdCyE~WBI!(?QQImr6rT1JHUm*u*>oPUM-w#z zszU{e9%d~&Pm2}GO;g@a^I6Y6RXncsk@=X|YZRU1DNz2z`8V~@xW1xq zq_IkyX}c||dejveL@eJ%%PA;`1YA7_Qfg5kvj9oM?kaZWgHsl=f{ctAB`Sb?1Tlk8eeP!MeP zEqK(zkLd&Y<7L(4|gS;k>`eE8MEn@Err*c>e9-8*^oLaiv z_Vjqd@&tzsAs7$5AHztrb1CM-QIpQ~vW)e(&;u>HyMOfTJc0m7D6R@$dguls<`_E# zdunmMx0{hIZoaMy#o-V{z6@|_7Gx&CRujo*MGXQWG=ThrcAG1S#hT#ouZ69|4^+iS za*5bh{SCTW$bvyawhPv~%^+_9$zC6SsbQ%L+=*nTV$d?sBe6oA_9JsROhXccFla#V zdvxeMQOpx!55y@3AGq^LEQ;XBdEL}T^PDPk)m&#(?8tF6e3k8e7yB#+V|QbYJ@afS z#T{+0UefY#tK-3QW?z;*d-C<5AE1u$UClV-`sEx08|obui3tsHA~LNAw=)K6kDtnr zED`)E%ZP)>qM4|uC>YT#Fif8mS!F{BiDT#MENZ(;DT(%y7qm}pG4ttI3cKOOQ%2JI~CP8OHg;$FF zupuSOle2nhEd))ZSjV;}P1sHAj}d$;TagR)Ppq?kjPpob(KhMWwe^kNEErO9%s=`| zSNuY!oNwPioJgsi!#cM&d+C6{tqxgcVdZJf;hD&C#-d33f}%ny^hq}ZQV#q`j3!Ao z)SQTzdb1B16!-B31XcC-IH`IIW#->)u(4=;PJWYhD|{<1wcI8=&`)NqP=r|0Dp-$k z%Qb&MTO%*lk6wl(NjRv~Su>mUhBxWI zGh-tA&GQL+v6y_>3m~2E!4dYs;W>J1K^>#cNiN(7zq@EgS(1#*Iu$H$wl(`sib$2G z8f!YN#@yZrw*Nn^U3pN`*Y-~Uu_#De1+7IX1y>Lh5CtUgY}EzQ}?I83DKMj!bn% zs|N4R(@J4bQY%Qhb8jTbYaCrFPgU;;%V{>)5R}#A)5rLR^mwGPh-fle+HJ?K4N;JMN*0_R<=L55)psA} z&35&@xpzIv{me8;_mlYrBazMGtzwUNt|g8{?7gev%T;oBOq)*l6IrJr&^^$_G9I13nb#s8i{l(#L}$>BFKy4-c!mt zbb>zl7|>FQx(d8&$?7?W>Cge4 zXBdT#&Pk>D@eE$(s>zEbpp4OkY;loW&Nx40xl=< zh@$_XUffl3O@Xv z9xh{*dsMC^%};}Hao2xWxE?Z8Ma4*4TN}_I{a)HJzF%x|Ugfsf-oTS@` zEoxPoA{2gtk37}BBA}0F=`fh(MkGF2&Yl9&*5&y4Y!HlXtJ(onduudXVH^*JBV?tP zM_grPWmAc_L#|cfjq8~U#gu4W!}rcF4M36uk3*vg$)>DaBi|@062+kiV4Aoic87i& zW=2LAP0h^4#yPVcYRAPy&U4h+!IQonP*~nR%T2UZjTM(%aSh%Sfm67_wGTa-Q`KTnrG*XbsTO%x!I% zZysK9hcS~o0b4C$t;yAv?vslaEgI!2UUEfx2{^Pd$AVGh(W;(n%Py$u78l#-z^6bv z{NvK4W>ni0`wiI(dqPt6 z)aUdhfnuz&_!2o+z&Ht;zR6p?y~;7Z-vPeZgB9YC@AvvY0~6JTy81LLsZ{ubRCkp5 zG1Ak2R@{B@eLa^r`Ic+TvahfPcG|BdCMF9nmIp)H5U7$6piHKUkl`lKi}^=#PFB`_ zSJy0|DlhAaytT z?vX=>(!hnhy1HvHE{s!19X%t2fpo>=CxMf`$-ewxO3?86t0u=Eo$J0RM%o(q(E~{Y zZm4u34Fv*SO^4bWfnV3*RNc6C?QWEvSbBM}PMs>vT3-6C1HXXDG?L!&o=%}qE+;3y ztEwmJ8{z7^#G$agI&`pweXthHgMxy}Y8SL5>8lIiO3Y%hOmzL;H33PGhtuuk>>QHv zo9L})2iP7S9!>Z@v%GxA*idJuW!0EOjN`IxL&>Fh=^-QD#`-i z?wUkSF&Tp;A?ew)(U#3PR-xq~P0toNGBMAxn6Iz320f zNUhZT1@5#u6nI@uOziK^CfurzWHWPfc|ddB2h^)QCYfgVsnwq?Cru7$XeXHA z^E-KDofT>}L1nsw_+{DV=2hQn14jL7nbABQ^g(AC5cE#I1h@4S5J zI5yB~mYSMs%?YW1Jd*)bRz(l7<$NB64XJ@M|u_*i<2M{SsFA;Ax}3qPdfid5BsDTyJgFk2|&eKSX;lH zj@LeZBLvcrQB-6O-{_u)Cd0Zui`ik1ll5$X*4K!l*sR`O*P)dQ^Yim5Y}-G=!gx#f z?MTf`4luMU^R7p&+yDJF#1GBUY#Q8}jX|R{eO?-zJ$LRcJjD}` zx>+f+Q$0GkOaP{t3y8q%($Z3m8&WH9J*YrUgVEw7HF zQs1fHTO=h_j4oY`ujL2{0*%<_266f<tp8N@E6JHD-GMF~P$m*8{hr@rMOHzm2WRa2OAF{d$oySm{%@hKHm?X0 zR$LHS`_~r^ANWfdCOE1r`hVySpAYJI85H88)eEh%s)~1gkF?W~Bd+)VkbyeoX~{um z@}nnDEG#TyycbFm2=pcM>do!|)Go)Qq~xKgmkk&wMhW=EZgtoG)mG?Idt%(u)D*6_ z9dnZ+K4@*7v+3G|4FgT}aYt9w#;RDQ;i!dur?DGX77yTedgjkGzr`GSMgN3C0tu zT7&H+a5=qe0Q%~U->S~JVYHRoysid}zZ>)n}qLe7tFhZ64@VW z3Yzj9I9d+U5)y(LQE{xVY>pib477a*;!p-4yh6wg!1Ff;GoYIAC^td@w`&y4D)hxv zE@=ec(W(z5lBPkm>zENcdpC zrM0NtKN=}m*Li`8ii&Hpd92sa6fJ#xZVnF*TaO*Kx^ib`!oAZNPZOHMl!eF6F&zlJ zLId}xt7{#S11uoeDl2!wJ-1grcr+5nMrQSD7C^OaI6(TOet5l0ct0d=^ZpfyevFxO z((lK;5XL)7B1U|3reWAL~Ux|0b&|8Ka|A zSaw-^F0I})Q3g=MG33YfLhG&o?KstgzKrs6Td1Gb<^K7gSspa*4QgupqEH`{jz_~* z={}=H3(2Uwq`!T + + Weekly Gold Prices + Average Price by Country + + + Distribution of Price by Country + Trend of Price and Volume + + + Heatmap of Correlation + + + Distribution of events per date + + + +### 📈 **Performance of the Models based on the Accuracy Scores** + + + + + + +
+
    +
  • Random Forest Classifier - 99.5%
    • +
  • Support Vector Machines - 97.5%
    • +
  • Logistic Regression - 97%
    • +
  • Gradient Booster - 100%
    • +
+ 		+ Accuracies of Models +
+ + +### 📢 **Conclusion** +Among all the models tested, the **Gradient Booster** achieved the highest accuracy,**100%**, making it the best-performing model for predicting gold prices. This demonstrates its effectiveness in handling the dataset and providing reliable predictions. + +### ✒️ **Your Signature** +Created by [Filbert Shawn](https://github.com/fspzar123) as a part of SSOC'24 Season 3. diff --git a/The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589276.Shawn.25944.0 b/The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589276.Shawn.25944.0 new file mode 100644 index 0000000000000000000000000000000000000000..fd241017d3d449e7e2980b370a9d06f3f45d5b41 GIT binary patch literal 4900 zcmaJ_Ppc(I757hk&RkG2;6fL}q}7e&-Q0U;-Xs%5$b->AXN+h9LI_25cXi+LRadoD z)$h$sn5={>vU4Fp5Ok4^F8lzl1qHu=_#qTrxeo2!ff4;T)GPkXJ#fvANB~|C2 z+`94k7hibsGdDhc{_9)suWsKi%;5XMvs&8X_1nez6)W7JyenP~%u8XzTWlfLaOFf0 zs15Vv0=``k#U)puc{^me-ilgQej!O>%t3<}?SbAGy{Y!`?IbUaX399nj8-HvJ<|)z zYH=wm5p7^4_tl;``JRB>_Fgb>CKMifo=n>h$F%4{sjP=&o>h`XTFYxmDdJT%bc5oa zY>{)CZJOdHz~XC2MaLziL|(na3g$sdgV zo<>8IWv<$bdQixgKlEgNp`?aKG0h8siz_Nwh`j$ay2oud^yIcQpl*@@kRtN<)Y&G5 z$+S$NOQ`aSo;xQmMS5i9Fe`c`D^3#7LP4D*kS)PcLE6-0W-eZ3+Lof9djy2kAR}vD z!_ll@|Hy8nb!bAA0`yK5JhDeew%L#Hp5~fK-B8P;|K}Dtekm4xGkY`fV%3eI2}Ex^ z+D*w$QWxfeiy!btMC_sPXV(MoT3jak6IUHrhmcX&CmwLb8!K4Fl`4640drBjjy2YF z3>8sb^hW9>9B9L;p{C?adIkp_{qPK}>s{*p1m(oHrsm(Len21Fw^^~_}<*cs@ikaFaTL49bo~*L1?nC;Da|&hV-)rIP`<;3j81qfD~fD6v|vto7%A_( zn6zkgnacoUV`1kvC?V-Hvf;|u3t`EMWb(vD)KHP=#)elYq`9GJZI8yN zL!uJS*g-SRy8tiOhFC2fFEKRz&uc=l$t5c~gFYHG@?IkzYUuQ$`V}vQ3ThXDA_oAj zFd~#aaPC8E1=_(f=?JD{d*>+07KkfYtlkT`1dYbkL`Zp{zgQ>X zJi^&?%eyI>fma#bNJ=G5d(8XevS2(>i^hu-7Ia)vsb%NpoG>2H$~pIVBtm!i5R+Xy z1fhec7-;ynQjU3p1%{Io*<*}EfeFEpX(VE4u>)fJINU?Q&J96s`!MyxTwl~P%%qKJ z_Th+X;83R%E`-8xyzB8e?3qbu>Q{8t1&xTM_s0i)o?YZr4nr*f#C-&%>}{+o*BRsY zG+1(pj{^>1BB@pj8rfF}m>svGz+q`hW`z*TI&yf5)*4L7@&H`Yt>4eRC?Y8peeRqj z7&;u2(pZnT@!dPIc4o_I0ZKvw6kvmH9Q!B~A!bQv>ug~FqXF>eF%eL)CA2P?7F|_Q zXO~0MT>pB83#j!DjcaK=8uL}ma0MHmlK>tpViUYfL2>A(qyWDH+RYVFVJOk^>OifD^oF!zoQOZs*g7wh9^!<3n$ah_$4 z8QXF#-wXQYxtPmLG5^uqKY56tv+J?%`Ut#Z%@;8xG~r`oEN+e|4q@ik^c65!y5(#N zEngon(kPd?N-RfBR3@#_G;`xLMh^lp1g++I^v)S*Skjzq zBm$o#=J7h-=8N3yWnE*UVj%;$XoVUQ`b7G3o=sn+yZqIA@wk-rE{s8FN}I`sls3mJJxKe{g%SfW_C0B< z=GDjyX6ynQCrd^n(pri)BZaI9q0AJrWtVM;D-K=DEFJygbQ>R`Te>$6HqtfKm7=bJ zvs930qXeB$`9!A5h{2^sm=e4fyr!?xN5o9=4Uf-QJ(kqaYAm=G7wl(E$S?BJVFSkh zF9bxHZElWX6w&>HXN$Y*yW4fTZs?q6mpDAiF{aU1nxPdA>BSMfkh`-v+wE3QS5u#T J^Iu=Q`X7aSA|n6* literal 0 HcmV?d00001 diff --git a/The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589418.Shawn.25944.1 b/The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589418.Shawn.25944.1 new file mode 100644 index 0000000000000000000000000000000000000000..c1d4c78829f2111f2a3b634725d5039186d76d38 GIT binary patch literal 4900 zcmaJ_Ppc(I6;~6UlM5mSTyzkzPuh`&=+UETHOj&CuKch2ck=kM>FGY`KM ze*XK*hrfR5-}nCb_?w^pj!($ySL7Mv|hdHL~pezH8=Izj$OyiVSQz! z6J{+)iZxOR7AW8S{ogsyFTVVhTVKBT?Di+CJ9i2_x?yyzmZo^?PO*N?2swdshn4(9Y@7h~nqMc&;_A58w9 z21Ar#w%Un$RLGV)3}k+xWDk!*nlpjRD=JxteDXB7$4xg5J~DBb5rdKyCkbewpw1G=mf)zMUe{!1Dqf}AmZG0}1ccZi6Kh$+ z!7Ok8#BQXqXhM_%^v)GLu_s5i$q)Zt&wD2OhFTu|zqH8my~z4z@n+ESQ~G z$STci!eFBZrnt>>>0xXt?DPgDBz{IVTxoMD3|SFPp4o^RDiYn;@Ct>rG!(7v&=|E( zRKyuG_N?cfhnE{etd^FS7@F?qHKEw-k`bLoAB{coULziA?E0+w6)%PIYO_F*0{~YT z;me+J$3j+T)gg|o(PkmI^r1BZ?O>R+1k<6tQv+Vjk!()=4;z za1Pw?ZjPqsRl08^rIMyS=KXP5Fs@bBc!9#ajy;uHa&F1-;{mOla*sy>bo&o6*?Ws1 zbnp}d4gXfkGN-Y?aB?DfjFBiXAviLPMC2A*Ahrv`-52cA5af37Q{T_^te#;eZA^;~ zCsYH6I-PLA7l!5CfX89aLZYXBMOR(Yh{(M^KIqfzBBxRqY5^b~0w^VKLtWWUYqz7p zl1h9UZ~zlYwOY`~zCysvv=w;{i&HWwgjmv%!c(+HV@j3>;8NeZ-O`I9kYdrN&WVD) z!!aqfad;cweH?0Mv78p5L?l1~Ht5Ewk9-kgmiV?#7J4um0e=n?0To+9YtA(2s){6qxkrf=iK)@W+yOW=&}D#g!pCUH-OcNP>CHIv zXdEq>jEHL~-V7A7#)mRd$dT4wR+7pL3s2;I_ywy=?|sjd`t4V9I+MG*IX^pFJzdRx_Rm*-_V|C= CWhHk2 literal 0 HcmV?d00001 diff --git a/The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589834.Shawn.25944.2 b/The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589834.Shawn.25944.2 new file mode 100644 index 0000000000000000000000000000000000000000..7ae7f7bf22bbc4d171c41e46a2466cb926cfedf5 GIT binary patch literal 4900 zcmaJ_&8sCx755`NCl@3baA6k1q?aM@=H5H=CLf592NMRJ7|{fTAVqa|b>H$;cePd3 z_svb1f5Jrwfq+?L<DrC>J5|-yU2pE>E#~pgIeqGU{?0k`@N41c zf4_eC`Sbs@zyHT~KmFI+FMYc-T=we+2hqE?c0XOOUUj0k+LW4`dTqz9MD}TMc`t$A8cerWoYfe0NEULQv^7gH7 zz4+XV-?;Vl%g=6qyt;Fz(4!kh$7*Scx9$|{*Nm{Ea<+KYGY`V}w^%0DaAk!Ts5Nus z0=~_N;=mPX&WuTJFrt=~%OpvRS!i&gJ<|JP(A7S?9p$C&nbOuW-76BApBaQHjJCDRV$DJ}h|RMJB-Pb*0xt>Lw#6!EGWyHRmRwp%9# zOZIp*{_~Ukq{fTXLUHnTs$pFO=-zQAl$paCJ>33z3hX1oyb<#(~_H8q`fR08&Jrp1Rn?FzJ>l zbO}{nF>q_;LBvNU4l`mW8F)*)mR_L&D9aoPx0aivOLUBO%wuVszV9YaM_ zSA&*)4hOwv)mT$*ZftmkLRuP%)^=!&+9xXF zj2U~@^UlM|jUiS`%S#MR_p6#vY<9_rPNR>;9(k`34>fjuR{e^XLV2}WpvVD$D~#}E z&$weDtF!75N7iVw5M27u8i95&Oj?5J(B3IZvIXJ_7OMA3=AhBong}ru^cU+SoJTkZ zZg@9G)AK6bHt(8$$iy(CH z6ax+aR?0G`vA}S0B6*CFC@>*7GL1y!7F!^;3&Y(P?9veAcJNc*&-JXHVJ2-%iw`GM z1BW`DaKRUb<=ueCVb4OMr+!6OUD1fhy+1wZ)9fOrQW$ChARYoJC2vDr*-mS>r@@j+ zd>U{76G^pN(8#_u(viYbv_@k}mPg=H-@5(Miz1L>(WlOdg1*Bs zDYbEU8{d5xYG<*W7NA5VKmj)B#;K2d5n`73woVp$Fd6}W4if2+!t(1s9`U_Z6UX?%b43Kle@!OZs-47VFbz!^c65!+I%+omamT( zX_U)UC5EFWDjnBonz>;bqX&T)0#_QOw{OIS*egMty8%aImiCNua!Vk{nLhP_T$=F} zuv^@O>ty>>9zLQdMN9)LPz2Nlb5tfNnrFU{Le*P>>-@~@MdQX^U|pAJTCRpY4Y2fF zKuQOw1m<8+;{wU1c*u$`#v4_-dh)|ttFzT}bUDB9hcB9+e>2?JpZ@VTU(Pr7-_KTm zJ6nA(tN>wV<+t`1XX)1dy*ooN#{$uNpc;%WvAtm7%zVA3S0kuNQNg z&euo_D>Z1ej6~XwVi5KXw2+fr;rKVS2Deo27^mS5z@dRI1Dq2+MnmpyUJp!f#?GU0 zv}7_OuBCW0P{y{A05(hY}mO3I&ySsO1{SY8|q=gZzF#=n%WT8}6RaSK}S(Qa* zR?oK0{s|6XAt9NAPaOCGT(}^CQ3GTR@y>c~2TjKV(ifFn*D!78p)$*XIai{iDcF}h=@ zi0XRKvd`h5*Q^?AO3tijw9qk(&(ONT#_rEpR)`ve2Rk4Cnmf)SDf#AbzZm$Q%Q zEjfrM8L@1(4>LkDoFFhgxViY=-iE5$bJZ{aStTuD0mVV|WM9EYr-KaXXAN-XS$pWE z=dfIJpSn0Xr8EMKM(M9X4P{iY^bobxbI-v3F8 ztkS$D3^saTirYMw9>%7^PH#{`;%8*TjW*Z9kQLG7nT@ESBGHWvuTV%!L($p}jZynV zMVv8X&wAc@c)2yiYH4|iq3M2B6N=3)8PRF<(byyJHR7ShuFtAp@lq(SHVYIv0C0s7 zzU&!yEM#?79pcCuZ5Dz{A6g^O4u(lfFdf=EMM<_mT){&1UdtRb8e0<~=7IiVorLoU z=fDl`=4g6erTa!wDrwqd-k+8Qce#CBo0`+{8>g4_;%>ifB#)icbbjcM`W zglgbWrxPyt!mzv>@Hp&QNc7aN=&EZP5xMuL2Ys4d~9GSJ#_S}gRLoWG>FCuJ68Uz`AxkaFM&5_ZBjiUtLIgRmwkBVtdHeg1e(>#?I~aKYrqGH*Ih&25C%L-eN6X0WjF)P89?7=~9%U5w+DwFH_3kT1 z_LUlIjL;qz1tvXud5-XGPFQd;>UCcMI_J(!+4OVo;=|!iKgXh*wX+@ z&jqA(fJ$Hv1~o2_Y>J1h_+q?OrK_jkyR$l5y+D_9`{_S^{@&-qjs4LdKK^9Bu|GXq z{pD=+)vyADnU&w#zdcL0_Ak%;t?h9ZRfl@|55sXO>zyBi&=fb54Jm#6=H;WuY~%G} zPSg1sXK)@W+yOW=&}D#g!pCUH{mrX^>CM=A zG>(=`M#QxgZw3lk<3pJ!WXmqu5LO(zmRUUd#rZZoLbvpwEo`J~sw+iZ181oqFD3~( zq0)&=l@WqVjW8#8FL+H~#gB*?80e|+_1cbI$IWqlZKM-s zEl7$rQVA9)|NhRWzk2`cLGOS5^xs!rSj(XI+kd;g`s?l0H@Io-Yfe0NEULQv{PwM{ zzWDr$U%vI+HjJCDRV$DJ}h|RMJB-Pb*0xt>Lw#6!EGWyHRmRwp%9# zOZIp*{_~Ukq{fTXLUHnTs$pFO=-zQAl$paCJ>33z3hX1oyb<#(~_H8q`fR08&Jrp1Rn?FzJ>l zbO}{nF>q_;LBvNU4l`mW8F)*)mR_L&D9aoPx0aivOLUBO%wuVszV9YaM_ zSA&*)4hOwv)mT$*ZftmkLRuP%)^=!&+9xXF zj2U~@^UlM|jUiS`%S#MR_sg14Y<9_rPNR>;9(k`34>fjuR{e^XLV2}WpvVD$D~#}E z&$weDtF!75N7iVw5M27u8i95&Oj?5J(B3IZvIXJ_7OMA3=AhBong}ru^cU+SoJTkZ zZg@9G)AK6bHt(8$$iy(CH z6ax+aR?0G`vA}S0B6*CFC@>*7GL1y!7F!^;3&Y(P?9veAcJNc*&-JXHVJ2-%iw`GM z1BW`DaKRUb<=ueCVb4OMr+!6OUD1fhy+1wZ)9fOrQW$ChARYoJC2vDr*-mS>r@@j+ zd>U{76G^pN(8#_u(viYbv_@k}mPg=H-@5(Miz1L>(WlOdg1*Bs zDYbEU8{d5xYG<*W7NA5VKmj)B#;K2d5n`73woVp$Fd6}W4if2+!t(1s9`U_Z6UX?%b43Kle@!OZs-47VFbz!^c65!+I%+omamT( zX_U)UC5EFWDjnBonz>;bqX&T)0#_QOw{OIS*egMty8%aImiCNua!Vk{nLhP_T$=F( zuv^@O>ty>>9zLQdMN9)LPz2Nlb5tfNnrFU{Le*P>>-@~@MdQX^U|pAJTCRpY4Y2fF zKuQOw1m<8+;{wU1c*u$`#v4_-dh&x?tFzVfbUDBM$u}>5_LXpBfA;4;d_LdU|2SLy z{cQDeSOLP!%5UvIo~2v+w`cy=_Be~GL%n!7E=pnCdC9FfAJGfgLSpG4_Bi<~H-;50 z!tW)dzpu@^++K$ z&9mI>WnE*UVj%;$XoVUh`ULtjo{e9{yZrV0;kcCb&W}N8ikr!Xls_* z>3of}uu_9Y%Sfc{CIOM=JmkzX6!r~ zM@uFn;#!I~1BI;dp-dFAWtVISD-K=DEFS&hd>bC2TYAtIHqtfKm7=bJvs925lLVbm z=|rZ=2*IUBm=nAgyr!?>N5qWr^^Y%D1C~_ZYRtP97VM`@NH6lzVgttiFL*>*Y;Kle z6w&>HXN!C5d)sxqZs?q62OJ*d6w}}<&Cm*mbaq5%a(6cuyWQ%^YVI@n_H)1fKNbri A_y7O^ literal 0 HcmV?d00001 diff --git a/The Effect of Economic News on Gold Prices Analysis/Model/project_folder.ipynb b/The Effect of Economic News on Gold Prices Analysis/Model/project_folder.ipynb new file mode 100644 index 000000000..5ae6164a4 --- /dev/null +++ b/The Effect of Economic News on Gold Prices Analysis/Model/project_folder.ipynb @@ -0,0 +1,2762 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import numpy as np\n", + "import pandas as pd\n", + "import seaborn as sns\n", + "from matplotlib import pyplot as plt\n", + "from matplotlib import colors" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "

\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
DayDateHourCountryEventActualPreviousConsensusForecast
0Tuesday01/01/1920:45CNCaixin Manufacturing PMI DEC49.750.250.150.1
1Friday01/04/198:30USNon Farm Payrolls DEC312K176K177K165K
2Sunday01/06/19NaNCNUS-China Trade TalksNaNNaNNaNNaN
3Monday01/07/1910:00CAIvey PMI s.a DEC59.757.256.856.7
4Monday01/07/19NaNCNUS-China Trade TalksNaNNaNNaNNaN
..............................
1871Thursday11/30/238:30USPersonal Income MoM OCT0.0020.40%0.0020.003
1872Thursday11/30/238:30USPersonal Spending MoM OCT0.0020.70%0.0020.004
1873Thursday11/30/2320:45CNCaixin Manufacturing PMI NOV50.749.549.849.8
1874Friday12/01/238:30CAUnemployment Rate NOV0.0585.70%0.0580.058
1875Friday12/01/2310:00USISM Manufacturing PMI NOV46.746.747.647.2
\n", + "

1876 rows × 9 columns

\n", + "
" + ], + "text/plain": [ + " Day Date Hour Country Event Actual \\\n", + "0 Tuesday 01/01/19 20:45 CN Caixin Manufacturing PMI DEC 49.7 \n", + "1 Friday 01/04/19 8:30 US Non Farm Payrolls DEC 312K \n", + "2 Sunday 01/06/19 NaN CN US-China Trade Talks NaN \n", + "3 Monday 01/07/19 10:00 CA Ivey PMI s.a DEC 59.7 \n", + "4 Monday 01/07/19 NaN CN US-China Trade Talks NaN \n", + "... ... ... ... ... ... ... \n", + "1871 Thursday 11/30/23 8:30 US Personal Income MoM OCT 0.002 \n", + "1872 Thursday 11/30/23 8:30 US Personal Spending MoM OCT 0.002 \n", + "1873 Thursday 11/30/23 20:45 CN Caixin Manufacturing PMI NOV 50.7 \n", + "1874 Friday 12/01/23 8:30 CA Unemployment Rate NOV 0.058 \n", + "1875 Friday 12/01/23 10:00 US ISM Manufacturing PMI NOV 46.7 \n", + "\n", + " Previous Consensus Forecast \n", + "0 50.2 50.1 50.1 \n", + "1 176K 177K 165K \n", + "2 NaN NaN NaN \n", + "3 57.2 56.8 56.7 \n", + "4 NaN NaN NaN \n", + "... ... ... ... \n", + "1871 0.40% 0.002 0.003 \n", + "1872 0.70% 0.002 0.004 \n", + "1873 49.5 49.8 49.8 \n", + "1874 5.70% 0.058 0.058 \n", + "1875 46.7 47.6 47.2 \n", + "\n", + "[1876 rows x 9 columns]" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "path = \"C:/Users/shawn/OneDrive/Documents/GitHub/ML-Crate/Dataset/\"\n", + "news = pd.read_csv(path + \"economic_calendar_19_24.csv\")\n", + "gold_price = pd.read_csv(path + \"gold_price_19_24.csv\")\n", + "news" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
DatePriceOpenHighLowVol_KChange_percent
012/01/20232089.72056.52095.72052.6241.621.58
111/30/20232057.22065.42067.42051.2151.92-0.48
211/29/20232067.12062.02072.72055.9197.790.81
311/28/20232050.52025.02054.42022.91.861.35
411/27/20232023.12012.92027.52012.71.060.47
........................
127401/08/20191285.91287.41288.41280.2221.92-0.31
127501/07/20191289.91290.21297.01287.3204.680.32
127601/04/20191285.81298.91300.01278.1316.06-0.70
127701/03/20191294.81290.41296.91286.4244.540.83
127801/02/20191284.11285.01291.01280.6235.330.22
\n", + "

1279 rows × 7 columns

\n", + "
" + ], + "text/plain": [ + " Date Price Open High Low Vol_K Change_percent\n", + "0 12/01/2023 2089.7 2056.5 2095.7 2052.6 241.62 1.58\n", + "1 11/30/2023 2057.2 2065.4 2067.4 2051.2 151.92 -0.48\n", + "2 11/29/2023 2067.1 2062.0 2072.7 2055.9 197.79 0.81\n", + "3 11/28/2023 2050.5 2025.0 2054.4 2022.9 1.86 1.35\n", + "4 11/27/2023 2023.1 2012.9 2027.5 2012.7 1.06 0.47\n", + "... ... ... ... ... ... ... ...\n", + "1274 01/08/2019 1285.9 1287.4 1288.4 1280.2 221.92 -0.31\n", + "1275 01/07/2019 1289.9 1290.2 1297.0 1287.3 204.68 0.32\n", + "1276 01/04/2019 1285.8 1298.9 1300.0 1278.1 316.06 -0.70\n", + "1277 01/03/2019 1294.8 1290.4 1296.9 1286.4 244.54 0.83\n", + "1278 01/02/2019 1284.1 1285.0 1291.0 1280.6 235.33 0.22\n", + "\n", + "[1279 rows x 7 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "gold_price" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "def outlier_thresholds(dataframe, variable):\n", + " quartile1 = dataframe[variable].quantile(0.01)\n", + " quartile3 = dataframe[variable].quantile(0.75)\n", + " interquantile_range = quartile3 - quartile1\n", + " up_limit = quartile3 + 1.5 * interquantile_range\n", + " low_limit = quartile1 - 1.5 * interquantile_range\n", + " return low_limit, up_limit" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "def summary(df):\n", + " missing_info = pd.DataFrame(df.isnull().sum(), columns=['Missing Values']) \n", + " data_types = pd.DataFrame(df.dtypes, columns=['Data Type'])\n", + " summary_df = pd.concat([missing_info, data_types], axis=1)\n", + " for column in df.columns: \n", + " if pd.api.types.is_object_dtype(df[column]):\n", + " num_unique_choices = df[column].nunique()\n", + " summary_df.loc[column, 'Unique Choices'] = num_unique_choices\n", + " if pd.api.types.is_numeric_dtype(df[column]):\n", + " low_limit, up_limit = outlier_thresholds(df, column) \n", + " summary_df.loc[column, 'min'] = df[column].min()\n", + " summary_df.loc[column, 'max'] = df[column].max() \n", + " summary_df.loc[column, 'Mean'] = df[column].mean()\n", + " summary_df.loc[column, 'Median'] = df[column].median()\n", + " summary_df.loc[column, 'Variance'] = df[column].var()\n", + " summary_df.loc[column, 'deviation'] = df[column].std() \n", + " num_outliers = len(df[(df[column] < low_limit) | (df[column] > up_limit)])\n", + " summary_df.loc[column, 'Num Outliers'] = num_outliers \n", + " return summary_df" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Missing ValuesData TypeUnique ChoicesminmaxMeanMedianVariancedeviationNum Outliers
Date0object1279.0NaNNaNNaNNaNNaNNaNNaN
Price0float64NaN1272.002089.701743.1490621797.70042242.879221205.5307260.0
Open0float64NaN1272.302076.401743.3426111796.90042309.244310205.6921100.0
High0float64NaN1277.102095.701755.4506651810.20043006.633210207.3804070.0
Low0float64NaN1267.302055.901730.4485141784.60041454.022138203.6026080.0
Vol_K15float64NaN0.00813.41216.213473200.51512971.563973113.8927745.0
Change_percent0float64NaN-4.995.950.0432060.0400.9660900.9828992.0
\n", + "
" + ], + "text/plain": [ + " Missing Values Data Type Unique Choices min max \\\n", + "Date 0 object 1279.0 NaN NaN \n", + "Price 0 float64 NaN 1272.00 2089.70 \n", + "Open 0 float64 NaN 1272.30 2076.40 \n", + "High 0 float64 NaN 1277.10 2095.70 \n", + "Low 0 float64 NaN 1267.30 2055.90 \n", + "Vol_K 15 float64 NaN 0.00 813.41 \n", + "Change_percent 0 float64 NaN -4.99 5.95 \n", + "\n", + " Mean Median Variance deviation Num Outliers \n", + "Date NaN NaN NaN NaN NaN \n", + "Price 1743.149062 1797.700 42242.879221 205.530726 0.0 \n", + "Open 1743.342611 1796.900 42309.244310 205.692110 0.0 \n", + "High 1755.450665 1810.200 43006.633210 207.380407 0.0 \n", + "Low 1730.448514 1784.600 41454.022138 203.602608 0.0 \n", + "Vol_K 216.213473 200.515 12971.563973 113.892774 5.0 \n", + "Change_percent 0.043206 0.040 0.966090 0.982899 2.0 " + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "summary(gold_price)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Note\n", + "* Vol_K: 05 outliers, and 15 missing Values.\n", + "* Change_percent: 02 outliers.\n", + "* Date: Type Object ." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "gold_price.index = pd.to_datetime(gold_price['Date'])\n", + "gold_price.set_index(gold_price.index, inplace=True)\n", + "gold_price.drop(columns=['Date'], inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "weekly_gold_prices = gold_price.resample('W').last() \n", + "plt.figure(figsize=(16, 6))\n", + "plt.plot(weekly_gold_prices.index, weekly_gold_prices['Price'], label='Weekly Gold Prices', color='#ffd700', marker='+')\n", + "plt.title('Weekly Gold Prices (2019-2023)', fontsize=16, fontweight='bold')\n", + "plt.xlabel('Date', fontsize=12)\n", + "plt.ylabel('Gold Price', fontsize=12)\n", + "plt.grid(True, linestyle='--', alpha=0.7)\n", + "plt.legend(loc='upper left')" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
DayDateHourCountryEventActualPreviousConsensusForecast
0Tuesday01/01/1920:45CNCaixin Manufacturing PMI DEC49.750.250.150.1
1Friday01/04/198:30USNon Farm Payrolls DEC312K176K177K165K
2Sunday01/06/19NaNCNUS-China Trade TalksNaNNaNNaNNaN
3Monday01/07/1910:00CAIvey PMI s.a DEC59.757.256.856.7
4Monday01/07/19NaNCNUS-China Trade TalksNaNNaNNaNNaN
\n", + "
" + ], + "text/plain": [ + " Day Date Hour Country Event Actual \\\n", + "0 Tuesday 01/01/19 20:45 CN Caixin Manufacturing PMI DEC 49.7 \n", + "1 Friday 01/04/19 8:30 US Non Farm Payrolls DEC 312K \n", + "2 Sunday 01/06/19 NaN CN US-China Trade Talks NaN \n", + "3 Monday 01/07/19 10:00 CA Ivey PMI s.a DEC 59.7 \n", + "4 Monday 01/07/19 NaN CN US-China Trade Talks NaN \n", + "\n", + " Previous Consensus Forecast \n", + "0 50.2 50.1 50.1 \n", + "1 176K 177K 165K \n", + "2 NaN NaN NaN \n", + "3 57.2 56.8 56.7 \n", + "4 NaN NaN NaN " + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "news.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(1876, 9)\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Missing ValuesData TypeUnique Choices
Day0object7.0
Date0object888.0
Hour41object55.0
Country0object7.0
Event0object479.0
Actual153object768.0
Previous154object787.0
Consensus356object592.0
Forecast157object671.0
\n", + "
" + ], + "text/plain": [ + " Missing Values Data Type Unique Choices\n", + "Day 0 object 7.0\n", + "Date 0 object 888.0\n", + "Hour 41 object 55.0\n", + "Country 0 object 7.0\n", + "Event 0 object 479.0\n", + "Actual 153 object 768.0\n", + "Previous 154 object 787.0\n", + "Consensus 356 object 592.0\n", + "Forecast 157 object 671.0" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "print(news.shape)\n", + "summary(news)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Notes -\n", + "* All data types is object\n", + "* 888 unique dates from 1876 Dates i.e (each date can have many rows (Events))\n", + "* Missing values in ( Actual, Previous, Consensus, Forecast ) columns\n", + "* There is 479 in Event (Deduplication. example (Consumer Confidence DEC and Consumer Confidence JAN)\n", + "* The columns( Actual, Previous, Consensus, Forecast ) (Contain chars (%, M, B, K). example (Consumer Confidence DEC and Consumer Confidence JAN)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['\\xa0DEC', 'alks', '\\xa0NOV', '\\xa0JAN', '\\xa0FEB', 'ress',\n", + " '\\xa0MAR', 'x\\xa0Q1', '\\xa0APR', 'e\\xa005', 'I\\xa005', 'a\\xa005',\n", + " 's\\xa005', 'Y\\xa005', 'M\\xa005', '\\xa0JUN', 'x\\xa0Q2', '\\xa0JUL',\n", + " '\\xa0AUG', 'e 1Y', '\\xa0SEP', 'x\\xa0Q3', '\\xa0OCT', 'x\\xa0Q4',\n", + " 'utes', 'ture', 'line', '2019', 'ting', 'ech\\xa0', 'ence', '2020',\n", + " 'irus', 'kage', 'l\\xa005', 'dget', 'Plan', 'tion', 'ring',\n", + " 'age\\xa0', 'ions', 'mony', 'sing', 'port', '-FEB', 'asts',\n", + " 'h\\xa005', 'kets', 'king', 'arty', 'ment', 'sion', 'Rate',\n", + " 'Y\\xa0Q4', 'v\\xa0Q4', 'h\\xa0Q4', 'l\\xa0Q4', 'Q\\xa0Q4', 'tem\\xa0',\n", + " 'Y\\xa0Q1', 'v\\xa0Q1', 'h\\xa0Q1', 'l\\xa0Q1', 'Q\\xa0Q1', 'Y\\xa0Q2',\n", + " 'v\\xa0Q2', 'h\\xa0Q2', 'l\\xa0Q2', 't\\xa0Q2', 'Q\\xa0Q2', 'Y\\xa0Q3',\n", + " 'v\\xa0Q3', 'h\\xa0Q3', 'l\\xa0Q3', 't\\xa0Q3', 'Q\\xa0Q3'],\n", + " dtype=object)" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "news['Event'].apply(lambda x: x[-4:]).unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Down to 144 Unique values for Event columns\n" + ] + } + ], + "source": [ + "def remove_suffix(event):\n", + " if event.endswith(('\\xa0JAN','\\xa0FEB','\\xa0MAR','\\xa0APR','\\xa005',\n", + " '\\xa0JUN','\\xa0JUL','\\xa0AUG','\\xa0SEP','\\xa0OCT','\\xa0NOV',\n", + " '\\xa0DEC','\\xa0Q1','\\xa0Q2','\\xa0Q3','\\xa0Q4')):\n", + " return event[:-3]\n", + " else:\n", + " return event\n", + "news['Event'] = news['Event'].apply(remove_suffix)\n", + "print(f\"Down to {len(news['Event'].unique())} Unique values for Event columns\")" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\shawn\\AppData\\Local\\Temp\\ipykernel_3588\\1052689142.py:2: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " percentage_mask.fillna(False, inplace=True)\n" + ] + } + ], + "source": [ + "percentage_mask = news['Previous'].str.endswith('%')\n", + "percentage_mask.fillna(False, inplace=True)\n", + "news['Previous'] = news['Previous'].str.rstrip('%')\n", + "news.loc[percentage_mask, 'Previous'] = pd.to_numeric(news.loc[percentage_mask, 'Previous'], errors='coerce') / 100.0" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "# Create a new column 'Multiplier' based on 'Previous' values\n", + "news['Multiplier'] = news['Previous'].str.extract(r'([BKM])', expand=False)\n", + "\n", + "news['Previous'] = news['Previous'].str.replace(r'[BKM]', '', regex=True).astype(float)\n", + "news['Actual'] = news['Actual'].str.replace(r'[BKM]', '', regex=True).astype(float)\n", + "news['Consensus'] = news['Consensus'].str.replace(r'[BKM]', '', regex=True).astype(float)\n", + "news['Forecast'] = news['Forecast'].str.replace(r'[BKM]', '', regex=True).astype(float)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\shawn\\AppData\\Local\\Temp\\ipykernel_3588\\3036244955.py:9: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n", + " news['Date'] = pd.to_datetime(news['Date'])\n" + ] + } + ], + "source": [ + "# Function to calculate percentage difference\n", + "def calculate_percentage_difference(row, value_column, actual_column):\n", + " return abs((row[value_column] - row[actual_column]) / ((row[value_column] + row[actual_column] + 1) / 2)) * 100\n", + "\n", + "# Apply the function to each row and create new columns 'D_Consensus' and 'D_Forecast'\n", + "news['D_Consensus'] = news.apply(lambda row: calculate_percentage_difference(row, 'Consensus', 'Actual'), axis=1)\n", + "news['D_Forecast'] = news.apply(lambda row: calculate_percentage_difference(row, 'Forecast', 'Actual'), axis=1)\n", + "\n", + "news['Date'] = pd.to_datetime(news['Date'])" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Missing ValuesData TypeUnique ChoicesminmaxMeanMedianVariancedeviationNum Outliers
Day0object7.0NaNNaNNaNNaNNaNNaNNaN
Date0datetime64[ns]NaNNaNNaNNaNNaNNaNNaNNaN
Hour41object55.0NaNNaNNaNNaNNaNNaNNaN
Country0object7.0NaNNaNNaNNaNNaNNaNNaN
Event0object144.0NaNNaNNaNNaNNaNNaNNaN
Actual153float64NaN-20500.04800.000000-4.7057830.035000310961.105749557.6388677.0
Previous1055float64NaN-20687.04800.000000-9.16414034.100000666068.985029816.1304953.0
Consensus356float64NaN-22000.03000.000000-15.2083120.031000418879.382158647.2089174.0
Forecast157float64NaN-21780.02900.000000-11.2543960.032000365741.781013604.7658896.0
Multiplier1486object3.0NaNNaNNaNNaNNaNNaNNaN
D_Consensus356float64NaN0.017600.00000032.5077950.830565248035.454155498.031579238.0
D_Forecast157float64NaN0.07733.88429834.7728471.18110266839.635570258.533626282.0
\n", + "
" + ], + "text/plain": [ + " Missing Values Data Type Unique Choices min \\\n", + "Day 0 object 7.0 NaN \n", + "Date 0 datetime64[ns] NaN NaN \n", + "Hour 41 object 55.0 NaN \n", + "Country 0 object 7.0 NaN \n", + "Event 0 object 144.0 NaN \n", + "Actual 153 float64 NaN -20500.0 \n", + "Previous 1055 float64 NaN -20687.0 \n", + "Consensus 356 float64 NaN -22000.0 \n", + "Forecast 157 float64 NaN -21780.0 \n", + "Multiplier 1486 object 3.0 NaN \n", + "D_Consensus 356 float64 NaN 0.0 \n", + "D_Forecast 157 float64 NaN 0.0 \n", + "\n", + " max Mean Median Variance deviation \\\n", + "Day NaN NaN NaN NaN NaN \n", + "Date NaN NaN NaN NaN NaN \n", + "Hour NaN NaN NaN NaN NaN \n", + "Country NaN NaN NaN NaN NaN \n", + "Event NaN NaN NaN NaN NaN \n", + "Actual 4800.000000 -4.705783 0.035000 310961.105749 557.638867 \n", + "Previous 4800.000000 -9.164140 34.100000 666068.985029 816.130495 \n", + "Consensus 3000.000000 -15.208312 0.031000 418879.382158 647.208917 \n", + "Forecast 2900.000000 -11.254396 0.032000 365741.781013 604.765889 \n", + "Multiplier NaN NaN NaN NaN NaN \n", + "D_Consensus 17600.000000 32.507795 0.830565 248035.454155 498.031579 \n", + "D_Forecast 7733.884298 34.772847 1.181102 66839.635570 258.533626 \n", + "\n", + " Num Outliers \n", + "Day NaN \n", + "Date NaN \n", + "Hour NaN \n", + "Country NaN \n", + "Event NaN \n", + "Actual 7.0 \n", + "Previous 3.0 \n", + "Consensus 4.0 \n", + "Forecast 6.0 \n", + "Multiplier NaN \n", + "D_Consensus 238.0 \n", + "D_Forecast 282.0 " + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "summary(news)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "There are 394 dates with one event.\n" + ] + } + ], + "source": [ + "\n", + "# Define a custom color palette with copper tones\n", + "custom_palette = [\"#FFD700\", \"#B87333\", \"#CD7F32\", \"#D2691E\", \"#BC8F8F\", \"#A52A2A\", \"#8B4513\"]\n", + "\n", + "date_event_counts = news.groupby('Date')['Event'].nunique()\n", + "# Count the occurrences of each event count\n", + "event_count_distribution = date_event_counts.value_counts().sort_index()\n", + "\n", + "# Plot the bar chart with the copper tone color palette\n", + "plt.figure(figsize=(15, 3))\n", + "event_count_distribution.plot(kind='bar', color=custom_palette, edgecolor='black')\n", + "plt.title('Distribution of Events per Date')\n", + "plt.xlabel('Number of Events')\n", + "plt.ylabel('Count of Dates')\n", + "plt.show()\n", + "\n", + "print(f\"There are {event_count_distribution[1]} dates with one event.\")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Associate one Date with One Event" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\shawn\\AppData\\Local\\Temp\\ipykernel_3588\\2166861275.py:8: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " news.drop(columns=['Country_Priority'], inplace=True)\n" + ] + } + ], + "source": [ + "country_priority = {'US': 1, 'EA': 2, 'GB': 3, 'JP': 4, 'CA': 5, 'CN': 6, 'RU': 7}\n", + "news['Country_Priority'] = news['Country'].map(country_priority)\n", + "# Sort by 'Country_Priority' and 'Date'\n", + "news.sort_values(by=['Country_Priority', 'Date'], inplace=True)\n", + "# Drop duplicates based on 'Date', keeping the first occurrence\n", + "news = news.drop_duplicates(subset='Date', keep='first')\n", + "# Drop the 'Country_Priority' column if you don't need it in the final result\n", + "news.drop(columns=['Country_Priority'], inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(1279, 18)\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
DatePriceVol_KChange_percentCountryEventD_ConsensusD_Forecast
02023-12-012089.7241.621.58USISM Manufacturing PMI1.8887721.053741
12023-11-302057.2151.92-0.48USCore PCE Price Index MoM0.0000000.199005
22023-11-292067.1197.790.81USGDP Growth Rate QoQ 2nd Est0.3629760.544959
32023-11-282050.51.861.35NaNNaNNaNNaN
42023-11-272023.11.060.47NaNNaNNaNNaN
\n", + "
" + ], + "text/plain": [ + " Date Price Vol_K Change_percent Country \\\n", + "0 2023-12-01 2089.7 241.62 1.58 US \n", + "1 2023-11-30 2057.2 151.92 -0.48 US \n", + "2 2023-11-29 2067.1 197.79 0.81 US \n", + "3 2023-11-28 2050.5 1.86 1.35 NaN \n", + "4 2023-11-27 2023.1 1.06 0.47 NaN \n", + "\n", + " Event D_Consensus D_Forecast \n", + "0 ISM Manufacturing PMI  1.888772 1.053741 \n", + "1 Core PCE Price Index MoM  0.000000 0.199005 \n", + "2 GDP Growth Rate QoQ 2nd Est 0.362976 0.544959 \n", + "3 NaN NaN NaN \n", + "4 NaN NaN NaN " + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Merge based on the 'Date' column\n", + "data = pd.merge(gold_price, news, on='Date', how='left')\n", + "print(data.shape)\n", + "data = data[[\"Date\", \"Price\", \"Vol_K\", \"Change_percent\", \"Country\", \"Event\", \"D_Consensus\", \"D_Forecast\"]]\n", + "data.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
DatePriceVol_KChange_percentCountryEventD_ConsensusD_Forecast
02023-12-012089.70241.621.58USISM Manufacturing PMI1.8887721.053741
12023-11-302057.20151.92-0.48USCore PCE Price Index MoM0.0000000.199005
22023-11-292067.10197.790.81USGDP Growth Rate QoQ 2nd Est0.3629760.544959
32023-11-282050.501.861.35NaNNaNNaNNaN
42023-11-272023.101.060.47NaNNaNNaNNaN
52023-11-242013.700.520.95NaNNaNNaNNaN
62023-11-231994.75NaN-0.43JPInflation Rate YoYNaN0.187793
72023-11-222003.400.67-0.43USDurable Goods Orders MoM5.0273225.664488
82023-11-212012.000.671.07USFOMC MinutesNaNNaN
92023-11-201990.700.310.30NaNNaNNaNNaN
102023-11-171984.70133.12-0.13USBuilding Permits Prel1.8796041.879604
112023-11-161987.30186.811.17NaNNaNNaNNaN
122023-11-151964.30142.92-0.11USPPI MoM1.2048191.204819
132023-11-141966.50180.740.84USCore Inflation Rate MoM0.1990050.199005
142023-11-131950.20183.700.65NaNNaNNaNNaN
152023-11-101937.70229.64-1.63USMichigan Consumer Sentiment Prel5.2757796.050955
162023-11-091969.80214.080.61USFed Chair Powell SpeechNaNNaN
172023-11-081957.80189.36-0.80USFed Chair Powell SpeechNaNNaN
182023-11-071973.50218.95-0.76NaNNaNNaNNaN
192023-11-061988.60146.28-0.53CAIvey PMI s.a1.1070112.441315
202023-11-031999.20222.190.29USNon Farm Payrolls18.12688823.460411
212023-11-021993.50158.650.30GBBoE Interest Rate Decision0.0000000.000000
222023-11-011987.50197.63-0.34USISM Manufacturing PMI4.7569805.761317
232023-10-311994.30214.78-0.56EAGDP Growth Rate QoQ Flash0.2002000.200200
242023-10-302005.60181.340.83JPBoJ Interest Rate Decision0.0000000.000000
252023-10-271989.000.370.06USCore PCE Price Index MoM0.0000000.199005
262023-10-261987.900.200.12USDurable Goods Orders MoM5.6390986.805293
272023-10-251985.500.160.44USFed Chair Powell SpeechNaNNaN
282023-10-241976.801.23-0.07GBUnemployment Rate - AdjustedNaNNaN
292023-10-231978.200.45-0.81NaNNaNNaNNaN
\n", + "
" + ], + "text/plain": [ + " Date Price Vol_K Change_percent Country \\\n", + "0 2023-12-01 2089.70 241.62 1.58 US \n", + "1 2023-11-30 2057.20 151.92 -0.48 US \n", + "2 2023-11-29 2067.10 197.79 0.81 US \n", + "3 2023-11-28 2050.50 1.86 1.35 NaN \n", + "4 2023-11-27 2023.10 1.06 0.47 NaN \n", + "5 2023-11-24 2013.70 0.52 0.95 NaN \n", + "6 2023-11-23 1994.75 NaN -0.43 JP \n", + "7 2023-11-22 2003.40 0.67 -0.43 US \n", + "8 2023-11-21 2012.00 0.67 1.07 US \n", + "9 2023-11-20 1990.70 0.31 0.30 NaN \n", + "10 2023-11-17 1984.70 133.12 -0.13 US \n", + "11 2023-11-16 1987.30 186.81 1.17 NaN \n", + "12 2023-11-15 1964.30 142.92 -0.11 US \n", + "13 2023-11-14 1966.50 180.74 0.84 US \n", + "14 2023-11-13 1950.20 183.70 0.65 NaN \n", + "15 2023-11-10 1937.70 229.64 -1.63 US \n", + "16 2023-11-09 1969.80 214.08 0.61 US \n", + "17 2023-11-08 1957.80 189.36 -0.80 US \n", + "18 2023-11-07 1973.50 218.95 -0.76 NaN \n", + "19 2023-11-06 1988.60 146.28 -0.53 CA \n", + "20 2023-11-03 1999.20 222.19 0.29 US \n", + "21 2023-11-02 1993.50 158.65 0.30 GB \n", + "22 2023-11-01 1987.50 197.63 -0.34 US \n", + "23 2023-10-31 1994.30 214.78 -0.56 EA \n", + "24 2023-10-30 2005.60 181.34 0.83 JP \n", + "25 2023-10-27 1989.00 0.37 0.06 US \n", + "26 2023-10-26 1987.90 0.20 0.12 US \n", + "27 2023-10-25 1985.50 0.16 0.44 US \n", + "28 2023-10-24 1976.80 1.23 -0.07 GB \n", + "29 2023-10-23 1978.20 0.45 -0.81 NaN \n", + "\n", + " Event D_Consensus D_Forecast \n", + "0 ISM Manufacturing PMI  1.888772 1.053741 \n", + "1 Core PCE Price Index MoM  0.000000 0.199005 \n", + "2 GDP Growth Rate QoQ 2nd Est 0.362976 0.544959 \n", + "3 NaN NaN NaN \n", + "4 NaN NaN NaN \n", + "5 NaN NaN NaN \n", + "6 Inflation Rate YoY  NaN 0.187793 \n", + "7 Durable Goods Orders MoM  5.027322 5.664488 \n", + "8 FOMC Minutes NaN NaN \n", + "9 NaN NaN NaN \n", + "10 Building Permits Prel  1.879604 1.879604 \n", + "11 NaN NaN NaN \n", + "12 PPI MoM  1.204819 1.204819 \n", + "13 Core Inflation Rate MoM  0.199005 0.199005 \n", + "14 NaN NaN NaN \n", + "15 Michigan Consumer Sentiment Prel  5.275779 6.050955 \n", + "16 Fed Chair Powell Speech  NaN NaN \n", + "17 Fed Chair Powell Speech  NaN NaN \n", + "18 NaN NaN NaN \n", + "19 Ivey PMI s.a  1.107011 2.441315 \n", + "20 Non Farm Payrolls  18.126888 23.460411 \n", + "21 BoE Interest Rate Decision 0.000000 0.000000 \n", + "22 ISM Manufacturing PMI  4.756980 5.761317 \n", + "23 GDP Growth Rate QoQ Flash 0.200200 0.200200 \n", + "24 BoJ Interest Rate Decision 0.000000 0.000000 \n", + "25 Core PCE Price Index MoM  0.000000 0.199005 \n", + "26 Durable Goods Orders MoM  5.639098 6.805293 \n", + "27 Fed Chair Powell Speech  NaN NaN \n", + "28 Unemployment Rate - Adjusted  NaN NaN \n", + "29 NaN NaN NaN " + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.head(30)" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Missing ValuesData TypeminmaxMeanMedianVariancedeviationNum OutliersUnique Choices
Date0datetime64[ns]NaNNaNNaNNaNNaNNaNNaNNaN
Price0float641272.002089.7000001743.1490621797.70000042242.879221205.5307260.0NaN
Vol_K15float640.00813.410000216.213473200.51500012971.563973113.8927745.0NaN
Change_percent0float64-4.995.9500000.0432060.0400000.9660900.9828992.0NaN
Country472objectNaNNaNNaNNaNNaNNaNNaN7.0
Event472objectNaNNaNNaNNaNNaNNaNNaN98.0
D_Consensus599float640.00752.83018911.3081941.0979192253.84994647.47473094.0NaN
D_Forecast537float640.007733.88429833.9553821.48358696522.160809310.680158105.0NaN
\n", + "
" + ], + "text/plain": [ + " Missing Values Data Type min max \\\n", + "Date 0 datetime64[ns] NaN NaN \n", + "Price 0 float64 1272.00 2089.700000 \n", + "Vol_K 15 float64 0.00 813.410000 \n", + "Change_percent 0 float64 -4.99 5.950000 \n", + "Country 472 object NaN NaN \n", + "Event 472 object NaN NaN \n", + "D_Consensus 599 float64 0.00 752.830189 \n", + "D_Forecast 537 float64 0.00 7733.884298 \n", + "\n", + " Mean Median Variance deviation \\\n", + "Date NaN NaN NaN NaN \n", + "Price 1743.149062 1797.700000 42242.879221 205.530726 \n", + "Vol_K 216.213473 200.515000 12971.563973 113.892774 \n", + "Change_percent 0.043206 0.040000 0.966090 0.982899 \n", + "Country NaN NaN NaN NaN \n", + "Event NaN NaN NaN NaN \n", + "D_Consensus 11.308194 1.097919 2253.849946 47.474730 \n", + "D_Forecast 33.955382 1.483586 96522.160809 310.680158 \n", + "\n", + " Num Outliers Unique Choices \n", + "Date NaN NaN \n", + "Price 0.0 NaN \n", + "Vol_K 5.0 NaN \n", + "Change_percent 2.0 NaN \n", + "Country NaN 7.0 \n", + "Event NaN 98.0 \n", + "D_Consensus 94.0 NaN \n", + "D_Forecast 105.0 NaN " + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "summary(data)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\shawn\\AppData\\Local\\Temp\\ipykernel_3588\\1062981010.py:2: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n", + "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n", + "\n", + "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n", + "\n", + "\n", + " data['Vol_K'].fillna(data['Vol_K'].median(), inplace=True)\n", + "C:\\Users\\shawn\\AppData\\Local\\Temp\\ipykernel_3588\\1062981010.py:3: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n", + "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n", + "\n", + "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n", + "\n", + "\n", + " data['D_Consensus'].fillna(data['D_Consensus'].median(), inplace=True)\n", + "C:\\Users\\shawn\\AppData\\Local\\Temp\\ipykernel_3588\\1062981010.py:4: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n", + "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n", + "\n", + "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n", + "\n", + "\n", + " data['D_Forecast'].fillna(data['D_Forecast'].median(), inplace=True)\n" + ] + } + ], + "source": [ + "# Handle missing values (example: filling with median)\n", + "data['Vol_K'].fillna(data['Vol_K'].median(), inplace=True)\n", + "data['D_Consensus'].fillna(data['D_Consensus'].median(), inplace=True)\n", + "data['D_Forecast'].fillna(data['D_Forecast'].median(), inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Aggregate data by country\n", + "country_avg_prices = data.groupby('Country')['Price'].mean().reset_index()\n", + "# Sort countries by average price\n", + "country_avg_prices = country_avg_prices.sort_values(by='Price', ascending=False)\n", + "# Bar Plot of Average Gold Prices by Country\n", + "plt.figure(figsize=(12, 8))\n", + "sns.barplot(x='Price', y='Country', data=country_avg_prices, palette='copper')\n", + "plt.title('Average Gold Prices by Country')\n", + "plt.xlabel('Average Gold Price')\n", + "plt.ylabel('Country')\n", + "plt.show()\n", + "# Box Plot of Gold Prices by Country\n", + "plt.figure(figsize=(14, 8))\n", + "sns.boxplot(x='Price', y='Country', data=data, palette='copper')\n", + "plt.title('Distribution of Gold Prices by Country')\n", + "plt.xlabel('Gold Price')\n", + "plt.ylabel('Country')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "# Exclude non-numeric columns (assuming 'Country' is non-numeric)\n", + "numeric_data = data.drop(columns=['Country', 'Event'])\n", + "\n", + "# Calculate correlation matrix\n", + "correlation_matrix = numeric_data.corr()\n", + "\n", + "# Define custom color palette with copper and gold tones\n", + "custom_palette = [\"#FFD700\", \"#B87333\", \"#CD7F32\", \"#D2691E\", \"#BC8F8F\", \"#A52A2A\", \"#8B4513\"]\n", + "\n", + "# Plot heatmap with custom color palette\n", + "plt.figure(figsize=(12, 8))\n", + "sns.heatmap(correlation_matrix, annot=True, cmap=sns.color_palette(custom_palette), fmt=\".2f\", linewidths=.5)\n", + "plt.title('Correlation Heatmap of Variables')\n", + "plt.show()\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\shawn\\AppData\\Local\\Temp\\ipykernel_3588\\847878419.py:2: FutureWarning: 'Q' is deprecated and will be removed in a future version, please use 'QE' instead.\n", + " quarterly_data = data.set_index('Date').resample('Q').agg({'Price': 'mean', 'Vol_K': 'mean'})\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "# Resample data by quarter and calculate the average price and volume for each quarter\n", + "quarterly_data = data.set_index('Date').resample('Q').agg({'Price': 'mean', 'Vol_K': 'mean'})\n", + "\n", + "fig, ax1 = plt.subplots(figsize=(12, 6))\n", + "\n", + "# Plot Price trend\n", + "ax1.plot(quarterly_data.index, quarterly_data['Price'], marker='o', linestyle='-', color='#FFD700', label='Price') # Gold color\n", + "ax1.set_xlabel('Quarter')\n", + "ax1.set_ylabel('Price', color='Black') # Gold color\n", + "ax1.tick_params('y', colors='Black') # Gold color\n", + "\n", + "# Create a secondary y-axis for Volume\n", + "ax2 = ax1.twinx()\n", + "ax2.plot(quarterly_data.index, quarterly_data['Vol_K'], marker='s', linestyle='-', color='#DAA520', label='Volume') # Dark gold color\n", + "ax2.set_ylabel('Volume (Vol K)', color='Black') # Dark gold color\n", + "ax2.tick_params('y', colors='Black') # Dark gold color\n", + "\n", + "# Add legend\n", + "lines, labels = ax1.get_legend_handles_labels()\n", + "lines2, labels2 = ax2.get_legend_handles_labels()\n", + "ax2.legend(lines + lines2, labels + labels2, loc='upper left')\n", + "\n", + "plt.title('Price and Volume Trend Over Quarters')\n", + "plt.grid(True)\n", + "\n", + "plt.tight_layout() # Adjust layout to prevent clipping of labels\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Date Price Vol_K Change_percent Country \\\n", + "0 2023-12-01 2089.7 241.62 1.58 US \n", + "1 2023-11-30 2057.2 151.92 -0.48 US \n", + "2 2023-11-29 2067.1 197.79 0.81 US \n", + "3 2023-11-28 2050.5 1.86 1.35 NaN \n", + "4 2023-11-27 2023.1 1.06 0.47 NaN \n", + "... ... ... ... ... ... \n", + "1274 2019-01-08 1285.9 221.92 -0.31 EA \n", + "1275 2019-01-07 1289.9 204.68 0.32 CA \n", + "1276 2019-01-04 1285.8 316.06 -0.70 US \n", + "1277 2019-01-03 1294.8 244.54 0.83 NaN \n", + "1278 2019-01-02 1284.1 235.33 0.22 NaN \n", + "\n", + " Event D_Consensus D_Forecast Sentiment \n", + "0 ISM Manufacturing PMI  1.888772 1.053741 Positive \n", + "1 Core PCE Price Index MoM  0.000000 0.199005 Negative \n", + "2 GDP Growth Rate QoQ 2nd Est 0.362976 0.544959 Positive \n", + "3 NaN 1.097919 1.483586 Neutral \n", + "4 NaN 1.097919 1.483586 Neutral \n", + "... ... ... ... ... \n", + "1274 Business Confidence  12.099644 19.178082 Negative \n", + "1275 Ivey PMI s.a  4.936170 5.110733 Positive \n", + "1276 Non Farm Payrolls  55.102041 61.506276 Negative \n", + "1277 NaN 1.097919 1.483586 Neutral \n", + "1278 NaN 1.097919 1.483586 Neutral \n", + "\n", + "[1279 rows x 9 columns]\n" + ] + } + ], + "source": [ + "def assign_sentiment(change_percent, event):\n", + " \"\"\"Assigns sentiment based on the change percent value, considering empty events.\n", + "\n", + " Args:\n", + " change_percent (float): The percent change in price.\n", + " event (str): The event associated with the price change (may be empty).\n", + "\n", + " Returns:\n", + " str: \"Positive\" if change_percent is positive, \"Negative\" if negative, \n", + " \"Neutral\" otherwise, or \"Neutral\" if event is empty.\n", + " \"\"\"\n", + " # Check if event is None (missing value) or an empty string after stripping\n", + " if pd.isna(event) or (isinstance(event, str) and event.strip() == ''):\n", + " return \"Neutral\"\n", + " elif change_percent > 0:\n", + " return \"Positive\"\n", + " elif change_percent < 0:\n", + " return \"Negative\"\n", + " else:\n", + " return \"Neutral\"\n", + "\n", + "# Add a new 'Sentiment' column with sentiment values based on 'Change_percent'\n", + "data['Sentiment'] = data.apply(lambda row: assign_sentiment(row['Change_percent'], row['Event']), axis=1)\n", + "\n", + "# Save the data to a CSV file\n", + "# data.to_csv('sentiment_labeled_data.csv', index=False)\n", + "\n", + "print(data)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## SENTIMENT ANALYSIS FOR EVENTS" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.preprocessing import LabelEncoder, StandardScaler\n", + "from sklearn.metrics import classification_report, accuracy_score\n", + "\n", + "# Load the dataset\n", + "data = pd.read_csv('C:/Users/shawn/OneDrive/Documents/GitHub/ML-Crate/Dataset/sentiment_labeled_data.csv')\n", + "\n", + "\n", + "# Encode categorical features\n", + "label_encoder = LabelEncoder()\n", + "data['Country'] = label_encoder.fit_transform(data['Country'].fillna('Unknown'))\n", + "data['Event'] = label_encoder.fit_transform(data['Event'])\n", + "\n", + "# Define features and target\n", + "features = ['Price', 'Vol_K', 'Change_percent', 'D_Consensus', 'D_Forecast', 'Country', 'Event']\n", + "X = data[features]\n", + "y = data['Sentiment']\n", + "\n", + "# Encode target labels\n", + "y = label_encoder.fit_transform(y)\n", + "\n", + "# Split the data into training and testing sets\n", + "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n", + "\n", + "# Standardize the features\n", + "scaler = StandardScaler()\n", + "X_train = scaler.fit_transform(X_train)\n", + "X_test = scaler.transform(X_test)\n", + "\n", + "model_name=[]\n", + "model_accu = []" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## RANDOM FOREST" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 0.99609375\n", + " precision recall f1-score support\n", + "\n", + " Negative 0.99 1.00 0.99 85\n", + " Neutral 1.00 0.99 0.99 93\n", + " Positive 1.00 1.00 1.00 78\n", + "\n", + " accuracy 1.00 256\n", + " macro avg 1.00 1.00 1.00 256\n", + "weighted avg 1.00 1.00 1.00 256\n", + "\n" + ] + } + ], + "source": [ + "from sklearn.ensemble import RandomForestClassifier\n", + "\n", + "\n", + "# Train a Random Forest Classifier\n", + "model = RandomForestClassifier(n_estimators=100, random_state=42)\n", + "model.fit(X_train, y_train)\n", + "\n", + "# Make predictions\n", + "y_pred = model.predict(X_test)\n", + "\n", + "# Evaluate the model\n", + "print('Accuracy:', accuracy_score(y_test, y_pred))\n", + "print(classification_report(y_test, y_pred, target_names=label_encoder.classes_))\n", + "\n", + "model_name.append('Random Forest')\n", + "model_accu.append(accuracy_score(y_test, y_pred))\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## SVM" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 0.9765625\n", + " precision recall f1-score support\n", + "\n", + " Negative 0.99 0.96 0.98 85\n", + " Neutral 1.00 0.97 0.98 93\n", + " Positive 0.94 1.00 0.97 78\n", + "\n", + " accuracy 0.98 256\n", + " macro avg 0.98 0.98 0.98 256\n", + "weighted avg 0.98 0.98 0.98 256\n", + "\n" + ] + } + ], + "source": [ + "from sklearn.svm import SVC\n", + "\n", + "# Train a Support Vector Classifier\n", + "model = SVC(kernel='linear', random_state=42)\n", + "model.fit(X_train, y_train)\n", + "\n", + "# Make predictions\n", + "y_pred = model.predict(X_test)\n", + "\n", + "# Evaluate the model\n", + "print('Accuracy:', accuracy_score(y_test, y_pred))\n", + "print(classification_report(y_test, y_pred, target_names=label_encoder.classes_))\n", + "\n", + "model_name.append('SVM')\n", + "model_accu.append(accuracy_score(y_test, y_pred))\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## LOGISTIC REGRESSION" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 0.97265625\n", + " precision recall f1-score support\n", + "\n", + " Negative 0.97 0.98 0.97 85\n", + " Neutral 0.98 0.96 0.97 93\n", + " Positive 0.97 0.99 0.98 78\n", + "\n", + " accuracy 0.97 256\n", + " macro avg 0.97 0.97 0.97 256\n", + "weighted avg 0.97 0.97 0.97 256\n", + "\n" + ] + } + ], + "source": [ + "from sklearn.linear_model import LogisticRegression\n", + "\n", + "# Train a Logistic Regression model\n", + "model = LogisticRegression(random_state=42, max_iter=1000)\n", + "model.fit(X_train, y_train)\n", + "\n", + "# Make predictions\n", + "y_pred = model.predict(X_test)\n", + "\n", + "# Evaluate the model\n", + "print('Accuracy:', accuracy_score(y_test, y_pred))\n", + "print(classification_report(y_test, y_pred, target_names=label_encoder.classes_))\n", + "\n", + "model_name.append('Logistic Regression')\n", + "model_accu.append(accuracy_score(y_test, y_pred))\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## GRADIENT BOOSTER " + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 1.0\n", + " precision recall f1-score support\n", + "\n", + " Negative 1.00 1.00 1.00 85\n", + " Neutral 1.00 1.00 1.00 93\n", + " Positive 1.00 1.00 1.00 78\n", + "\n", + " accuracy 1.00 256\n", + " macro avg 1.00 1.00 1.00 256\n", + "weighted avg 1.00 1.00 1.00 256\n", + "\n" + ] + } + ], + "source": [ + "from sklearn.ensemble import GradientBoostingClassifier\n", + "\n", + "# Train a Gradient Boosting Classifier\n", + "model = GradientBoostingClassifier(random_state=42)\n", + "model.fit(X_train, y_train)\n", + "\n", + "# Make predictions\n", + "y_pred = model.predict(X_test)\n", + "\n", + "# Evaluate the model\n", + "print('Accuracy:', accuracy_score(y_test, y_pred))\n", + "print(classification_report(y_test, y_pred, target_names=label_encoder.classes_))\n", + "\n", + "model_name.append('Gradient Boosting')\n", + "model_accu.append(accuracy_score(y_test, y_pred))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
ModelsAccuracies
0Random Forest0.996094
1SVM0.976562
2Logistic Regression0.972656
3Gradient Boosting1.000000
\n", + "
" + ], + "text/plain": [ + " Models Accuracies\n", + "0 Random Forest 0.996094\n", + "1 SVM 0.976562\n", + "2 Logistic Regression 0.972656\n", + "3 Gradient Boosting 1.000000" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_comp=pd.DataFrame({'Models':model_name, 'Accuracies':model_accu})\n", + "model_comp" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "model_comp.plot(x='Models',y='Accuracies')" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/The Effect of Economic News on Gold Prices Analysis/requirements.txt b/The Effect of Economic News on Gold Prices Analysis/requirements.txt new file mode 100644 index 000000000..dc601bdca --- /dev/null +++ b/The Effect of Economic News on Gold Prices Analysis/requirements.txt @@ -0,0 +1,5 @@ +Pandas +Seaborn +Numpy +Matplotlib +Sklearn \ No newline at end of file From 4612645eee6e41274c65eeec15ddb9542bb15410 Mon Sep 17 00:00:00 2001 From: fspzar123 <111989473+fspzar123@users.noreply.github.com> Date: Sat, 8 Jun 2024 08:03:37 +0530 Subject: [PATCH 2/2] logs directory deleted --- .../events.out.tfevents.1717589276.Shawn.25944.0 | Bin 4900 -> 0 bytes .../events.out.tfevents.1717589418.Shawn.25944.1 | Bin 4900 -> 0 bytes .../events.out.tfevents.1717589834.Shawn.25944.2 | Bin 4900 -> 0 bytes .../events.out.tfevents.1717589993.Shawn.25944.3 | Bin 4900 -> 0 bytes .../events.out.tfevents.1717590151.Shawn.25944.4 | Bin 4900 -> 0 bytes 5 files changed, 0 insertions(+), 0 deletions(-) delete mode 100644 The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589276.Shawn.25944.0 delete mode 100644 The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589418.Shawn.25944.1 delete mode 100644 The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589834.Shawn.25944.2 delete mode 100644 The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589993.Shawn.25944.3 delete mode 100644 The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717590151.Shawn.25944.4 diff --git a/The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589276.Shawn.25944.0 b/The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589276.Shawn.25944.0 deleted file mode 100644 index fd241017d3d449e7e2980b370a9d06f3f45d5b41..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 4900 zcmaJ_Ppc(I757hk&RkG2;6fL}q}7e&-Q0U;-Xs%5$b->AXN+h9LI_25cXi+LRadoD z)$h$sn5={>vU4Fp5Ok4^F8lzl1qHu=_#qTrxeo2!ff4;T)GPkXJ#fvANB~|C2 z+`94k7hibsGdDhc{_9)suWsKi%;5XMvs&8X_1nez6)W7JyenP~%u8XzTWlfLaOFf0 zs15Vv0=``k#U)puc{^me-ilgQej!O>%t3<}?SbAGy{Y!`?IbUaX399nj8-HvJ<|)z zYH=wm5p7^4_tl;``JRB>_Fgb>CKMifo=n>h$F%4{sjP=&o>h`XTFYxmDdJT%bc5oa zY>{)CZJOdHz~XC2MaLziL|(na3g$sdgV zo<>8IWv<$bdQixgKlEgNp`?aKG0h8siz_Nwh`j$ay2oud^yIcQpl*@@kRtN<)Y&G5 z$+S$NOQ`aSo;xQmMS5i9Fe`c`D^3#7LP4D*kS)PcLE6-0W-eZ3+Lof9djy2kAR}vD z!_ll@|Hy8nb!bAA0`yK5JhDeew%L#Hp5~fK-B8P;|K}Dtekm4xGkY`fV%3eI2}Ex^ z+D*w$QWxfeiy!btMC_sPXV(MoT3jak6IUHrhmcX&CmwLb8!K4Fl`4640drBjjy2YF z3>8sb^hW9>9B9L;p{C?adIkp_{qPK}>s{*p1m(oHrsm(Len21Fw^^~_}<*cs@ikaFaTL49bo~*L1?nC;Da|&hV-)rIP`<;3j81qfD~fD6v|vto7%A_( zn6zkgnacoUV`1kvC?V-Hvf;|u3t`EMWb(vD)KHP=#)elYq`9GJZI8yN zL!uJS*g-SRy8tiOhFC2fFEKRz&uc=l$t5c~gFYHG@?IkzYUuQ$`V}vQ3ThXDA_oAj zFd~#aaPC8E1=_(f=?JD{d*>+07KkfYtlkT`1dYbkL`Zp{zgQ>X zJi^&?%eyI>fma#bNJ=G5d(8XevS2(>i^hu-7Ia)vsb%NpoG>2H$~pIVBtm!i5R+Xy z1fhec7-;ynQjU3p1%{Io*<*}EfeFEpX(VE4u>)fJINU?Q&J96s`!MyxTwl~P%%qKJ z_Th+X;83R%E`-8xyzB8e?3qbu>Q{8t1&xTM_s0i)o?YZr4nr*f#C-&%>}{+o*BRsY zG+1(pj{^>1BB@pj8rfF}m>svGz+q`hW`z*TI&yf5)*4L7@&H`Yt>4eRC?Y8peeRqj z7&;u2(pZnT@!dPIc4o_I0ZKvw6kvmH9Q!B~A!bQv>ug~FqXF>eF%eL)CA2P?7F|_Q zXO~0MT>pB83#j!DjcaK=8uL}ma0MHmlK>tpViUYfL2>A(qyWDH+RYVFVJOk^>OifD^oF!zoQOZs*g7wh9^!<3n$ah_$4 z8QXF#-wXQYxtPmLG5^uqKY56tv+J?%`Ut#Z%@;8xG~r`oEN+e|4q@ik^c65!y5(#N zEngon(kPd?N-RfBR3@#_G;`xLMh^lp1g++I^v)S*Skjzq zBm$o#=J7h-=8N3yWnE*UVj%;$XoVUQ`b7G3o=sn+yZqIA@wk-rE{s8FN}I`sls3mJJxKe{g%SfW_C0B< z=GDjyX6ynQCrd^n(pri)BZaI9q0AJrWtVM;D-K=DEFJygbQ>R`Te>$6HqtfKm7=bJ zvs930qXeB$`9!A5h{2^sm=e4fyr!?xN5o9=4Uf-QJ(kqaYAm=G7wl(E$S?BJVFSkh zF9bxHZElWX6w&>HXN$Y*yW4fTZs?q6mpDAiF{aU1nxPdA>BSMfkh`-v+wE3QS5u#T J^Iu=Q`X7aSA|n6* diff --git a/The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589418.Shawn.25944.1 b/The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589418.Shawn.25944.1 deleted file mode 100644 index c1d4c78829f2111f2a3b634725d5039186d76d38..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 4900 zcmaJ_Ppc(I6;~6UlM5mSTyzkzPuh`&=+UETHOj&CuKch2ck=kM>FGY`KM ze*XK*hrfR5-}nCb_?w^pj!($ySL7Mv|hdHL~pezH8=Izj$OyiVSQz! z6J{+)iZxOR7AW8S{ogsyFTVVhTVKBT?Di+CJ9i2_x?yyzmZo^?PO*N?2swdshn4(9Y@7h~nqMc&;_A58w9 z21Ar#w%Un$RLGV)3}k+xWDk!*nlpjRD=JxteDXB7$4xg5J~DBb5rdKyCkbewpw1G=mf)zMUe{!1Dqf}AmZG0}1ccZi6Kh$+ z!7Ok8#BQXqXhM_%^v)GLu_s5i$q)Zt&wD2OhFTu|zqH8my~z4z@n+ESQ~G z$STci!eFBZrnt>>>0xXt?DPgDBz{IVTxoMD3|SFPp4o^RDiYn;@Ct>rG!(7v&=|E( zRKyuG_N?cfhnE{etd^FS7@F?qHKEw-k`bLoAB{coULziA?E0+w6)%PIYO_F*0{~YT z;me+J$3j+T)gg|o(PkmI^r1BZ?O>R+1k<6tQv+Vjk!()=4;z za1Pw?ZjPqsRl08^rIMyS=KXP5Fs@bBc!9#ajy;uHa&F1-;{mOla*sy>bo&o6*?Ws1 zbnp}d4gXfkGN-Y?aB?DfjFBiXAviLPMC2A*Ahrv`-52cA5af37Q{T_^te#;eZA^;~ zCsYH6I-PLA7l!5CfX89aLZYXBMOR(Yh{(M^KIqfzBBxRqY5^b~0w^VKLtWWUYqz7p zl1h9UZ~zlYwOY`~zCysvv=w;{i&HWwgjmv%!c(+HV@j3>;8NeZ-O`I9kYdrN&WVD) z!!aqfad;cweH?0Mv78p5L?l1~Ht5Ewk9-kgmiV?#7J4um0e=n?0To+9YtA(2s){6qxkrf=iK)@W+yOW=&}D#g!pCUH-OcNP>CHIv zXdEq>jEHL~-V7A7#)mRd$dT4wR+7pL3s2;I_ywy=?|sjd`t4V9I+MG*IX^pFJzdRx_Rm*-_V|C= CWhHk2 diff --git a/The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589834.Shawn.25944.2 b/The Effect of Economic News on Gold Prices Analysis/Model/logs/events.out.tfevents.1717589834.Shawn.25944.2 deleted file mode 100644 index 7ae7f7bf22bbc4d171c41e46a2466cb926cfedf5..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 4900 zcmaJ_&8sCx755`NCl@3baA6k1q?aM@=H5H=CLf592NMRJ7|{fTAVqa|b>H$;cePd3 z_svb1f5Jrwfq+?L<DrC>J5|-yU2pE>E#~pgIeqGU{?0k`@N41c zf4_eC`Sbs@zyHT~KmFI+FMYc-T=we+2hqE?c0XOOUUj0k+LW4`dTqz9MD}TMc`t$A8cerWoYfe0NEULQv^7gH7 zz4+XV-?;Vl%g=6qyt;Fz(4!kh$7*Scx9$|{*Nm{Ea<+KYGY`V}w^%0DaAk!Ts5Nus z0=~_N;=mPX&WuTJFrt=~%OpvRS!i&gJ<|JP(A7S?9p$C&nbOuW-76BApBaQHjJCDRV$DJ}h|RMJB-Pb*0xt>Lw#6!EGWyHRmRwp%9# zOZIp*{_~Ukq{fTXLUHnTs$pFO=-zQAl$paCJ>33z3hX1oyb<#(~_H8q`fR08&Jrp1Rn?FzJ>l zbO}{nF>q_;LBvNU4l`mW8F)*)mR_L&D9aoPx0aivOLUBO%wuVszV9YaM_ zSA&*)4hOwv)mT$*ZftmkLRuP%)^=!&+9xXF zj2U~@^UlM|jUiS`%S#MR_p6#vY<9_rPNR>;9(k`34>fjuR{e^XLV2}WpvVD$D~#}E z&$weDtF!75N7iVw5M27u8i95&Oj?5J(B3IZvIXJ_7OMA3=AhBong}ru^cU+SoJTkZ zZg@9G)AK6bHt(8$$iy(CH z6ax+aR?0G`vA}S0B6*CFC@>*7GL1y!7F!^;3&Y(P?9veAcJNc*&-JXHVJ2-%iw`GM z1BW`DaKRUb<=ueCVb4OMr+!6OUD1fhy+1wZ)9fOrQW$ChARYoJC2vDr*-mS>r@@j+ zd>U{76G^pN(8#_u(viYbv_@k}mPg=H-@5(Miz1L>(WlOdg1*Bs zDYbEU8{d5xYG<*W7NA5VKmj)B#;K2d5n`73woVp$Fd6}W4if2+!t(1s9`U_Z6UX?%b43Kle@!OZs-47VFbz!^c65!+I%+omamT( zX_U)UC5EFWDjnBonz>;bqX&T)0#_QOw{OIS*egMty8%aImiCNua!Vk{nLhP_T$=F} zuv^@O>ty>>9zLQdMN9)LPz2Nlb5tfNnrFU{Le*P>>-@~@MdQX^U|pAJTCRpY4Y2fF zKuQOw1m<8+;{wU1c*u$`#v4_-dh)|ttFzT}bUDB9hcB9+e>2?JpZ@VTU(Pr7-_KTm zJ6nA(tN>wV<+t`1XX)1dy*ooN#{$uNpc;%WvAtm7%zVA3S0kuNQNg z&euo_D>Z1ej6~XwVi5KXw2+fr;rKVS2Deo27^mS5z@dRI1Dq2+MnmpyUJp!f#?GU0 zv}7_OuBCW0P{y{A05(hY}mO3I&ySsO1{SY8|q=gZzF#=n%WT8}6RaSK}S(Qa* zR?oK0{s|6XAt9NAPaOCGT(}^CQ3GTR@y>c~2TjKV(ifFn*D!78p)$*XIai{iDcF}h=@ zi0XRKvd`h5*Q^?AO3tijw9qk(&(ONT#_rEpR)`ve2Rk4Cnmf)SDf#AbzZm$Q%Q zEjfrM8L@1(4>LkDoFFhgxViY=-iE5$bJZ{aStTuD0mVV|WM9EYr-KaXXAN-XS$pWE z=dfIJpSn0Xr8EMKM(M9X4P{iY^bobxbI-v3F8 ztkS$D3^saTirYMw9>%7^PH#{`;%8*TjW*Z9kQLG7nT@ESBGHWvuTV%!L($p}jZynV zMVv8X&wAc@c)2yiYH4|iq3M2B6N=3)8PRF<(byyJHR7ShuFtAp@lq(SHVYIv0C0s7 zzU&!yEM#?79pcCuZ5Dz{A6g^O4u(lfFdf=EMM<_mT){&1UdtRb8e0<~=7IiVorLoU z=fDl`=4g6erTa!wDrwqd-k+8Qce#CBo0`+{8>g4_;%>ifB#)icbbjcM`W zglgbWrxPyt!mzv>@Hp&QNc7aN=&EZP5xMuL2Ys4d~9GSJ#_S}gRLoWG>FCuJ68Uz`AxkaFM&5_ZBjiUtLIgRmwkBVtdHeg1e(>#?I~aKYrqGH*Ih&25C%L-eN6X0WjF)P89?7=~9%U5w+DwFH_3kT1 z_LUlIjL;qz1tvXud5-XGPFQd;>UCcMI_J(!+4OVo;=|!iKgXh*wX+@ z&jqA(fJ$Hv1~o2_Y>J1h_+q?OrK_jkyR$l5y+D_9`{_S^{@&-qjs4LdKK^9Bu|GXq z{pD=+)vyADnU&w#zdcL0_Ak%;t?h9ZRfl@|55sXO>zyBi&=fb54Jm#6=H;WuY~%G} zPSg1sXK)@W+yOW=&}D#g!pCUH{mrX^>CM=A zG>(=`M#QxgZw3lk<3pJ!WXmqu5LO(zmRUUd#rZZoLbvpwEo`J~sw+iZ181oqFD3~( zq0)&=l@WqVjW8#8FL+H~#gB*?80e|+_1cbI$IWqlZKM-s zEl7$rQVA9)|NhRWzk2`cLGOS5^xs!rSj(XI+kd;g`s?l0H@Io-Yfe0NEULQv{PwM{ zzWDr$U%vI+HjJCDRV$DJ}h|RMJB-Pb*0xt>Lw#6!EGWyHRmRwp%9# zOZIp*{_~Ukq{fTXLUHnTs$pFO=-zQAl$paCJ>33z3hX1oyb<#(~_H8q`fR08&Jrp1Rn?FzJ>l zbO}{nF>q_;LBvNU4l`mW8F)*)mR_L&D9aoPx0aivOLUBO%wuVszV9YaM_ zSA&*)4hOwv)mT$*ZftmkLRuP%)^=!&+9xXF zj2U~@^UlM|jUiS`%S#MR_sg14Y<9_rPNR>;9(k`34>fjuR{e^XLV2}WpvVD$D~#}E z&$weDtF!75N7iVw5M27u8i95&Oj?5J(B3IZvIXJ_7OMA3=AhBong}ru^cU+SoJTkZ zZg@9G)AK6bHt(8$$iy(CH z6ax+aR?0G`vA}S0B6*CFC@>*7GL1y!7F!^;3&Y(P?9veAcJNc*&-JXHVJ2-%iw`GM z1BW`DaKRUb<=ueCVb4OMr+!6OUD1fhy+1wZ)9fOrQW$ChARYoJC2vDr*-mS>r@@j+ zd>U{76G^pN(8#_u(viYbv_@k}mPg=H-@5(Miz1L>(WlOdg1*Bs zDYbEU8{d5xYG<*W7NA5VKmj)B#;K2d5n`73woVp$Fd6}W4if2+!t(1s9`U_Z6UX?%b43Kle@!OZs-47VFbz!^c65!+I%+omamT( zX_U)UC5EFWDjnBonz>;bqX&T)0#_QOw{OIS*egMty8%aImiCNua!Vk{nLhP_T$=F( zuv^@O>ty>>9zLQdMN9)LPz2Nlb5tfNnrFU{Le*P>>-@~@MdQX^U|pAJTCRpY4Y2fF zKuQOw1m<8+;{wU1c*u$`#v4_-dh&x?tFzVfbUDBM$u}>5_LXpBfA;4;d_LdU|2SLy z{cQDeSOLP!%5UvIo~2v+w`cy=_Be~GL%n!7E=pnCdC9FfAJGfgLSpG4_Bi<~H-;50 z!tW)dzpu@^++K$ z&9mI>WnE*UVj%;$XoVUh`ULtjo{e9{yZrV0;kcCb&W}N8ikr!Xls_* z>3of}uu_9Y%Sfc{CIOM=JmkzX6!r~ zM@uFn;#!I~1BI;dp-dFAWtVISD-K=DEFS&hd>bC2TYAtIHqtfKm7=bJvs925lLVbm z=|rZ=2*IUBm=nAgyr!?>N5qWr^^Y%D1C~_ZYRtP97VM`@NH6lzVgttiFL*>*Y;Kle z6w&>HXN!C5d)sxqZs?q62OJ*d6w}}<&Cm*mbaq5%a(6cuyWQ%^YVI@n_H)1fKNbri A_y7O^