Note: As of version 2.00.12/3.00.0 (2024/4/1), this document is no longer maintained. For the latest documentation, please refer to DolphinDB Manual>Trading Calendar.
Trading calendar is a frequently used tool for data analysis, which helps to quickly obtain exchange calendars and perform calculations based on trading calendars. Starting from version 2.00.9/1.30.21, DolphinDB provides built-in trading calendars of more than fifty exchanges. Refer to Release for information on the latest calendars.
This tutorial describes how to use and customize trading calendars in DolphinDB. Specifically: check trading days; perform calculations based on trading calendars; create your own trading calendars; update trading calendars.
The built-in trading calendars can be used for various scenarios.
Note:
-
Starting from version 1.30.23/2.00.11, multiple trading days frequency is supported for functions transFreq, asFreq, and resample with the number specified before the trading calendar identifier in rule.
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Starting from version 2.00.11.1, trading calendar, specified as “integers + identifiers“, can be used and calculated as DURATION data.
You can use function getMarketCalendar(marketName, [startDate], [endDate]) to get trading days of the corresponding exchange in the date range determined by startDate and endDate.
To check the trading days of New York Stock Exchange (XNYS) between 2022.1.1 and 2022.1.10:
getMarketCalendar("XNYS",2022.01.01, 2022.01.10)
// output
[2022.01.03,2022.01.04,2022.01.05,2022.01.06,2022.01.07,2022.01.10]To shift a trading day forward or backward, you can use function temporalAdd(date, duration, exchangeId).
Take XNYS for example, we add two trading days to the dates between 2023.1.1 and 2023.1.6:
dates=[2023.01.01, 2023.01.02, 2023.01.03, 2023.01.04, 2023.01.05, 2023.01.06]
temporalAdd(dates,2,"XNYS")
// output
[2023.01.04,2023.01.04,2023.01.05,2023.01.06,2023.01.09,2023.01.10]Or you can also use the following script if you use version 2.00.11.1 or higher. For detailed usage of trading calendar as DURATION type, refer to section "Use Trading Days as DURATION Type".
dates=[2023.01.01, 2023.01.02, 2023.01.03, 2023.01.04, 2023.01.05, 2023.01.06]
temporalAdd(dates, 2XNYS)
//output
[2023.01.04,2023.01.04,2023.01.05,2023.01.06,2023.01.09,2023.01.10]You can get the closest trading day of a certain day with function transFreq(X,rule).
For example, specify parameter rule as XNYS. We can get the closest trading days of each date between 2023.1.1 and 2023.1.6:
dates=[2023.01.01, 2023.01.02, 2023.01.03, 2023.01.04, 2023.01.05, 2023.01.06]
dates.transFreq("XNYS")
// output
[2022.12.30,2022.12.30,2023.01.03,2023.01.04,2023.01.05,2023.01.06]You can choose functions asFreq(X,rule) or resample(X,rule,func) to sample data on trading days. The only difference of the two lies in whether data can be aggregated.
Function asFreq(X,rule) will return the result by trading days. If there are multiple records in the same trading day, only the first value will be taken. If there is no data in a trading day, it will be filled with NULL.
The following example obtains the stock prices of XNYS in trading days from 2022.12.30 to 2023.1.6:
timestampv = [2022.12.30T23:00:00.000,2023.01.01T00:00:00.000,2023.01.03T00:10:00.000,2023.01.03T00:20:00.000,2023.01.04T00:20:00.000,2023.01.04T00:30:00.000,2023.01.06T00:40:00.000]
close = [100.10, 100.10, 100.10, 78.89, 88.99, 88.67, 78.78]
s=indexedSeries(timestampv, close)
s.asFreq("XNYS")
// output
#0
------
2022.12.30|100.10
2023.01.03|100.10
2023.01.04|88.99
2023.01.05|
2023.01.06|78.78Function resample(X,rule,func) will return the aggregated result of data sampled by trading days.
In the following example, we obtain the closing prices of XNYS stocks in trading days from 2022.12.30 to 2023.1.6:
timestampv = [2022.12.30T23:00:00.000,2023.01.01T00:00:00.000,2023.01.03T00:10:00.000,2023.01.03T00:20:00.000,2023.01.04T00:20:00.000,2023.01.04T00:30:00.000,2023.01.06T00:40:00.000]
close = [100.10, 100.10, 100.10, 78.89, 88.99, 88.67, 78.78]
s=indexedSeries(timestampv, close)
s.resample("XNYS", last)
// output
#0
------
2022.12.30|100.10
2023.01.03|78.89
2023.01.04|88.67
2023.01.05|
2023.01.06|78.78Starting from version 2.00.11.1, trading calendar, specified as “integers + identifiers“, can be used as DURATION data.
Trading days of DURATION type can be specified by converting a string of trading calendar identifier with theduration function.
Take XNYS for example, we can convert string “2XNYS“ to DURATION type and query the average closing price every two trading days with interval specified:
y = duration("2XNYS")
date = [2022.12.30, 2023.01.03, 2023.01.04, 2023.01.05, 2023.01.06]
close = [100.10, 78.89, 88.99, 88.67, 78.78]
t = table(date, close)
select avg(close) from t group by interval(date, y, "prev")
// output
| interval_date | avg_close
---|---------------|-----------
0 | 2022.12.30 | 89.495
1 | 2023.01.04 | 88.83
2 | 2023.01.06 | 78.78
The window parameter of wj now can be specified as trading calendar identifiers.
The following example performs the window join operation on “t1“ and “t2“ and obtain the average closing price over each window [-2XNYS:0XNYS]:
t1 = table(2023.01.03 2023.01.06 as date)
date = [2022.12.30, 2023.01.03, 2023.01.04, 2023.01.05, 2023.01.06]
close = [100.10, 78.89, 88.99, 88.67, 78.78]
t2 = table(date, close)
wj(t1, t2, -2XNYS:0XNYS, <avg(close)>, `date);
// output
| date | avg_close
---|------------|-------------------
0 | 2023.01.03 | 89.495
1 | 2023.01.06 | 85.48
The trading days can be used for measuring sliding windows for the moving, time-based moving, twindow, and tmovingWindowData functions.
Moving Functions
Take msum as an example, we obtain the sum of closing prices of an XNYS stock every two trading days:
date = [2022.12.30, 2023.01.03, 2023.01.04, 2023.01.05, 2023.01.06]
close = [100.10, 78.89, 88.99, 88.67, 78.78]
X1 = indexedSeries(date, close)
msum(X1, window=2XNYS)
// output
#0
------
2022.12.30|100.1
2023.01.03|178.99
2023.01.04|167.88
2023.01.05|177.66
2023.01.06|167.45
Time-based Moving Functions
Take tmavg for example, we obtain the average closing prices of an XNYS stock every two trading days:
date = [2022.12.30, 2023.01.03, 2023.01.04, 2023.01.05, 2023.01.06]
close = [100.10, 78.89, 88.99, 88.67, 78.78]
t = table(date, close)
select tmavg(date, close, 2XNYS) from t
// output
| tmavg_date
---|------------
0 | 100.1
1 | 89.495
2 | 83.94
3 | 88.83
4 | 83.725
Function twindow
The following example calculates the average closing price of an XNYS stock over each window [-1XNYS:2XNYS]:
date = [2022.12.30, 2023.01.03, 2023.01.04, 2023.01.05, 2023.01.06]
close = [100.10, 78.89, 88.99, 88.67, 78.78]
t = table(date, close)
select twindow(avg, close, date, -1XNYS:2XNYS) from t
// output
| twindow_avg
---|-------------------
0 | 89.327
1 | 89.163
2 | 83.833
3 | 85.48
4 | 83.725
Function tmovingWindowData
The following example returns an array vector where each row indicates the closing prices of each window (i.e., two trading days).
date = [2022.12.30, 2023.01.03, 2023.01.04, 2023.01.05, 2023.01.06]
close = [100.10, 78.89, 88.99, 88.67, 78.78]
tmovingWindowData(date, close, 2XNYS)
// output
[[100.1],[100.1, 78.89],[78.89, 88.99],[88.99, 88.67],[88.67, 78.78]]
Use functions move and tmove to shift elements based on trading days.
Function move
The following example shifts the closing prices of an XNYS stock to the right for two trading days:
date = [2022.12.30, 2023.01.03, 2023.01.04, 2023.01.05, 2023.01.06]
close = [100.10, 78.89, 88.99, 88.67, 78.78]
X1 = indexedSeries(date, close)
move(X1, 2XNYS)
// output
#0
------
2022.12.30|
2023.01.03|
2023.01.04|100.1
2023.01.05|78.89
2023.01.06|88.99
Function tmove
The following example obtains the closing prices from two trading days before the current day.
date = [2022.12.30, 2023.01.03, 2023.01.04, 2023.01.05, 2023.01.06]
close = [100.10, 78.89, 88.99, 88.67, 78.78]
t = table(date, close)
select *, tmove(date, close, 2XNYS) from t
// output
| date | close | tmove_date
------|------------|-------|-----------
0 | 2022.12.30 | 100.1 |
1 | 2023.01.03 | 78.89 |
2 | 2023.01.04 | 88.99 | 100.1
3 | 2023.01.05 | 88.67 | 78.89
4 | 2023.01.06 | 78.78 | 88.99
DolphinDB also allows administrators to customize trading calendars with built-in functions.
Note: Since version 1.30.23/2.00.11, naming the trading calendar identifier with digits is no longer permitted. It must consist of four uppercase letters and cannot be the same as the file name in marketHolidayDir.
Suppose there is an exchange named “XDDB“, function addMarketHoliday(marketName, holiday) can be used to add a new XDDB calendar. A XDDB.csv file will be added to the /marketHoliday/ directory. Weekends are recognized as holidays in DolphinDB by default, therefore, only weekday holidays need to be filled in the file.
Once a new trading calendar has been generated, functions such as getMarketCalendar can be used directly based on the new calendar:
//set 2023.01.03 (Tue.) and 2023.01.04 (Wed.) as holidays
holiday = 2023.01.03 2023.01.04
//user login
login(`admin,`123456)
//generate a trading calendar
addMarketHoliday("XDDB",holiday)
//get the trading days of the new calendar in a date range
getMarketCalendar("XDDB",2023.01.01, 2023.01.10)
//output
[2023.01.02,2023.01.05,2023.01.06,2023.01.09,2023.01.10]
temporalAdd(2023.01.01,2,"XDDB")
//output
2023.01.05Note: The newly added trading calendar is only valid on the current node. Execute function addMarketHoliday on other nodes for it to take effect on those nodes.
If you want to update the existing calendar of XDDB exchange, function updateMarketHoliday(marketName, holiday) can be used to reset the holidays.
Note: The file will be overwritten. The original holidays will be replaced with the holidays specified by this function.
The following example resets the dates 2023.03.07 and 2023.03.08 as holidays for the XDDB calendar. Check the next trading day after 2022.01.01 with function temporalAdd:
//set 2023.03.07 (Tue.) and 2023.03.08 (Wed.) as holiday
updateMarketHoliday("XDDB",2023.03.07 2023.03.08)
//the original holidays 2023.01.03 and 2023.01.04 are no longer holidays
getMarketCalendar("XDDB",2023.01.01, 2023.01.10)
//output
[2023.01.02,2023.01.03,2023.01.04,2023.01.05,2023.01.06,2023.01.09,2023.01.10]
//As holidays, 2023.03.07 and 2023.03.08 are not included in the trading calendar
getMarketCalendar("XDDB",2023.03.01, 2023.03.10)
//output
[2023.03.01,2023.03.02,2023.03.03,2023.03.06,2023.03.09,2023.03.10]All exchange calendars supported are listed below.
Note that calendars are updated according to the holidays announced on the official website of each exchange and the local governments. Refer to Release for information on the latest calendars.
- Major Stock Exchanges
| ISO Code | Exchange | Country | Exchange Website | CSV File Path | Starting from |
|---|---|---|---|---|---|
| AIXK | Astana International Exchange | Kazakhstan | https://aix.kz/trading/trading-calendar/ | marketHoliday/AIXK.csv | 2017 |
| ASEX | Athens Stock Exchange | Greece | https://www.athexgroup.gr/market-alternative-holidays | marketHoliday/ASEX.csv | 2004 |
| BVMF | BMF Bovespa | Brazil | https://www.b3.com.br/en_us/solutions/platforms/puma-trading-system/for-members-and-traders/trading-calendar/holidays/ | marketHoliday/BVMF.csv | 2004 |
| CCFX | China Finacial Futures Exchange | China | http://www.cffex.com.cn/jyrl/ | marketHoliday/CCFX.csv | 2007 |
| CMES | Chicago Mercantile Exchange | USA | https://www.cmegroup.com/tools-information/holiday-calendar.html#cmeGlobex | marketHoliday/CMES.csv | 2004 |
| CZCE | Zhengzhou Commodity Exchange | China | http://www.czce.com.cn/cn/jysj/jyyl/H770313index_1.htm | marketHoliday/CZCE.csv | 1991 |
| XDCE | Dalian Commodity Exchange | China | http://big5.dce.com.cn:1980/SuniT/www.dce.com.cn/DCE/TradingClearing/Exchange%20Notice/1516085/index.html | marketHoliday/XDCE.csv | 1994 |
| IEPA | ICE US | US | https://www.theice.com/holiday-hours?utm_source=website&utm_medium=search&utm_campaign=spotlight | marketHoliday/IEPA.csv | 2004 |
| XINE | Shanghai International Energey Exchange | China | https://www.ine.cn/en/news/notice/6598.html | marketHoliday/XINE.csv | 2017 |
| SHFE | Shanghai Futures Exchange | China | https://www.shfe.com.cn/bourseService/businessdata/calendar/ | marketHoliday/SHFE.csv | 1992 |
| XAMS | Euronext Amsterdam | Netherlands | https://www.euronext.com/en/trade/trading-hours-holidays | marketHoliday/XAMS.csv | 2004 |
| XASX | Austrialian Securities Exchange | Australia | https://www2.asx.com.au/markets/market-resources/asx-24-trading-calendar | marketHoliday/XASX.csv | 2004 |
| XBKK | Stock Exchange of Thailand | Thailand | https://www.set.or.th/en/about/event-calendar/holiday?year=2023 | marketHoliday/XBKK.csv | 2004 |
| XBOG | Colombia Securities Exchange | Colombia | https://www.bvc.com.co/non-business-market-days | marketHoliday/XBOG.csv | 2004 |
| XBOM | Bombay Stock Exchange | India | https://www.bseindia.com/static/markets/marketinfo/listholi.aspx | marketHoliday/XBOM.csv | 2004 |
| XBRU | Euronext Brussels | Belgium | https://www.euronext.com/en/trade/trading-hours-holidays#:~:text=Calendar%20of%20business%20days%202023%20%20%20Euronext:%20%20Closed%20%2012%20more%20rows%20 | marketHoliday/XBRU.csv | 2004 |
| XBSE | Bucharest Stock Exchange | Romania | https://www.bvb.ro/TradingAndStatistics/TradingSessionSchedule | marketHoliday/XBSE.csv | 2004 |
| XBUD | Budapest Stock Exchange | Hungary | https://www.bse.hu/Products-and-Services/Trading-information/trading-calendar-2023 | marketHoliday/XBUD.csv | 2004 |
| XBUE | Buenos Aires Stock Exchange | Argentina | marketHoliday/XBUE.csv | 2004 | |
| XCBF | CBOE Futures | USA | https://www.cboe.com/about/hours/us-futures/ | marketHoliday/XCBF.csv | 2004 |
| XCSE | Copenhagen Stock Exchange | Denmark | https://www.nasdaqomxnordic.com/tradinghours/ | marketHoliday/XCSE.csv | 2004 |
| XDUB | Irish Stock Exchange | Ireland | https://www.euronext.com/en/trade/trading-hours-holidays | marketHoliday/XDUB.csv | 2004 |
| XETR | Xetra | Germany | https://www.xetra.com/xetra-en/newsroom/trading-calendar | marketHoliday/XETR.csv | 2004 |
| XFRA | Frankfurt Stock Exchange | Germany | https://www.boerse-frankfurt.de/en/know-how/trading-calendar | marketHoliday/XFRA.csv | 2004 |
| XHEL | Helsinki Stock Exchange | Finland | https://www.nasdaqomxnordic.com/tradinghours/XHEL | marketHoliday/XHEL.csv | 2004 |
| XHKG | Hong Kong Exchanges | Hong Kong, China | https://www.hkex.com.hk/News/HKEX-Calendar?sc_lang=zh-HK&defaultdate=2023-02-01 | marketHoliday/XHKG.csv | 2004 |
| XICE | Iceland Stock Exchange | Iceland | https://www.nasdaqomxnordic.com/tradinghours/ | marketHoliday/XICE.csv | 2004 |
| XIDX | Indonesia Stock Exchange | Indonesia | https://idx.co.id/en/about-idx/trading-holiday/ | marketHoliday/XIDX.csv | 2004 |
| XIST | Istanbul Stock Exchange | Türkiye | https://borsaistanbul.com/en/sayfa/3631/official-holidays | marketHoliday/XIST.csv | 2004 |
| XJSE | Johannesburg Stock Exchange | South Africa | https://www.jse.co.za/ | marketHoliday/XJSE.csv | 2004 |
| XKAR | Pakistan Stock Exchange | Pakistan | https://www.psx.com.pk/psx/exchange/general/calendar-holidays | marketHoliday/XKAR.csv | 2004 |
| XKLS | Malaysia Stock Exchange | Malaysia | https://www.bursamalaysia.com/about_bursa/about_us/calendar | marketHoliday/XKLS.csv | 2004 |
| XKRX | Korea Exchange | Republic of Korea | http://global.krx.co.kr/contents/GLB/05/0501/0501110000/GLB0501110000.jsp | marketHoliday/XKRX.csv | 2004 |
| XLIM | Lima Stock Exchange | Peru | marketHoliday/XLIM.csv | 2004 | |
| XLIS | Euronext Lisbon | Portugal | https://www.euronext.com/en/trade/trading-hours-holidays | marketHoliday/XLIS.csv | 2004 |
| XLON | London Stock Exchange | England | https://www.londonstockexchange.com/securities-trading/trading-access/business-days | marketHoliday/XLON.csv | 2004 |
| XMAD | Euronext Lisbon | Portugal | https://www.euronext.com/en/trade/trading-hours-holidays | marketHoliday/XMAD.csv | 2004 |
| XMEX | Mexican Stock Exchange | Mexico | https://www.bmv.com.mx/en/bmv-group/holiday-schedule | marketHoliday/XMEX.csv | 2004 |
| XMIL | Borsa Italiana | Italy | https://www.borsaitaliana.it/borsaitaliana/calendario-e-orari-di-negoziazione/calendario-borsa-orari-di-negoziazione.en.htm | marketHoliday/XMIL.csv | 2004 |
| XMOS | Moscow Exchange | Russia | https://www.moex.com/en/tradingcalendar/ | marketHoliday/XMOS.csv | 2004 |
| XNYS | New York Stock Exchange | USA | https://www.nyse.com/markets/hours-calendars | marketHoliday/XNYS.csv | 2004 |
| XNZE | New Zealand Exchangen | New Zealand | https://www.nzx.com/services/nzx-trading/hours-boards | marketHoliday/XNZE.csv | 2004 |
| XOSL | Oslo Stock Exchange | Norway | https://www.euronext.com/en/trade/trading-hours-holidays | marketHoliday/XOSL.csv | 2004 |
| XPAR | Euronext Paris | France | https://www.euronext.com/en/trade/trading-hours-holidays | marketHoliday/XPAR.csv | 2004 |
| XPHS | Philippine Stock Exchange | Philippines | https://www.pse.com.ph/investing-at-pse/#investing2 | marketHoliday/XPHS.csv | 2004 |
| XPRA | Prague Stock Exchange | Czech Republic | https://www.pse.cz/en/trading/trading-information/trading-calendar | marketHoliday/XPRA.csv | 2004 |
| XSES | Singapore Exchange | Singapore | https://www.mom.gov.sg/employment-practices/public-holidays | marketHoliday/XSES.csv | 2004 |
| XSGO | Santiago Stock Exchange | Chile | https://www.euronext.com/en/trade/trading-hours-holidays | marketHoliday/XSGO.csv | 2004 |
| XSHE | Shenzhen Stock Exchange | China | http://www.szse.cn/disclosure/index.html | marketHoliday/XSHE.csv | 1992 |
| XSHG | Shanghai Stock Exchange | China | http://www.sse.com.cn/market/view/ | marketHoliday/XSHG.csv | 1991 |
| XSTO | Stockholm Stock Exchange | Sweden | https://www.nasdaqomxnordic.com/tradinghours/ | marketHoliday/XSTO.csv | 2004 |
| XSWX | SIX Swiss Exchange | Switzerland | https://www.six-group.com/en/products-services/the-swiss-stock-exchange/market-data/news-tools/trading-currency-holiday-calendar.html#/ | marketHoliday/XSWX.csv | 2004 |
| XTAI | Taiwan Stock Exchange Corp | Taiwan, China | https://www.twse.com.tw/en/holidaySchedule/holidaySchedule | marketHoliday/XTAI.csv | 2004 |
| XTKS | Tokyo Stock Exchange | Japan | https://www.jpx.co.jp/english/corporate/about-jpx/calendar/ | marketHoliday/XTKS.csv | 2004 |
| XTSE | Toronto Stock Exchange | Canada | https://www.tsx.com/trading/calendars-and-trading-hours/calendar | marketHoliday/XTSE.csv | 2004 |
| XWAR | Poland Stock Exchange | Poland | marketHoliday/XWAR.csv | 2004 | |
| XWBO | Wiener Borse | Austria | https://www.wienerborse.at/en/trading/trading-information/trading-calendar/ | marketHoliday/XWBO.csv | 2004 |