attempt to update fsharp.stats

nhirschey · Nov 23, 2023 · 12483fe · 12483fe
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Showing 40 changed files with 98 additions and 92 deletions.
diff --git a/.gitignore b/.gitignore
@@ -9,4 +9,5 @@ data-cache
 */*FootballPlayers.csv
 docs/*.csv
 docs/data
-docs/project/data
+docs/project/data
+*/*shiller_data.xls
diff --git a/docs/.debugMVE.fsx b/docs/.debugMVE.fsx
@@ -1,5 +1,5 @@
-#r "nuget: NovaSBE.Finance"
-#r "nuget: FSharp.Stats"
+#r "nuget: NovaSBE.Finance, 0.4.0"
+#r "nuget: FSharp.Stats, 0.5.0"
 
 open System
 open FSharp.Stats

diff --git a/docs/.sgd.fsx b/docs/.sgd.fsx
@@ -11,8 +11,8 @@ index: 1000
 [![Notebook](img/badge-notebook.svg)]({{root}}/{{fsdocs-source-basename}}.ipynb)
 *)
 
-#r "nuget: FSharp.Stats"
-#r "nuget: FSharp.Data"
+#r "nuget: FSharp.Stats, 0.5.0"
+#r "nuget: FSharp.Data, 5.0.2"
 #r "nuget: DiffSharp-lite"
 #r "nuget: Quotes.YahooFinance, 0.0.5"
 

diff --git a/docs/.sp500.fsx b/docs/.sp500.fsx
@@ -1,4 +1,4 @@
-#r "nuget: FSharp.Data"
+#r "nuget: FSharp.Data, 5.0.2"
 
 open System
 open FSharp.Data

diff --git a/docs/Common.fsx b/docs/Common.fsx
@@ -1,7 +1,7 @@
 (**
 [![Script](img/badge-script.svg)]({{root}}/{{fsdocs-source-basename}}.fsx)&emsp;
 *)
-#r "nuget: FSharp.Data"
+#r "nuget: FSharp.Data, 5.0.2"
 
 open System
 open System.IO

diff --git a/docs/Momentum-Class.fsx b/docs/Momentum-Class.fsx
@@ -15,11 +15,11 @@ index: 9
 
 #time "on"
 
-#r "nuget: FSharp.Data"
-#r "nuget: FSharp.Stats"
+#r "nuget: FSharp.Data, 5.0.2"
+#r "nuget: FSharp.Stats, 0.5.0"
 #r "nuget: Plotly.NET, 3.*"
 #r "nuget: Plotly.NET.Interactive, 3.*"
-#r "nuget: NovaSBE.Finance,0.1.0"
+#r "nuget: NovaSBE.Finance, 0.4.0"
 
 open System
 open FSharp.Data

diff --git a/docs/PortfolioFormation-SimpleExample.fsx b/docs/PortfolioFormation-SimpleExample.fsx
@@ -26,7 +26,7 @@ samplePeriod
 Now let's dig in. This is a *relatively* basic version of a strategy to build intuition with what we're doing. It is simpler than working with real data. But we will next move to real data.
 *)
 
-#r "nuget: FSharp.Stats"
+#r "nuget: FSharp.Stats, 0.5.0"
 open FSharp.Stats
 
 (**

diff --git a/docs/VolAndReturnPred.fsx b/docs/VolAndReturnPred.fsx
@@ -19,9 +19,9 @@ index: 7
 *)
 
 
-#r "nuget: FSharp.Data"
-#r "nuget: NovaSBE.Finance"
-#r "nuget: FSharp.Stats"
+#r "nuget: FSharp.Data, 5.0.2"
+#r "nuget: NovaSBE.Finance, 0.4.0"
+#r "nuget: FSharp.Stats, 0.5.0"
 #r "nuget: Plotly.NET, 3.*"
 #r "nuget: Plotly.NET.Interactive, 3.*"
 
@@ -309,16 +309,16 @@ let varBuyHold = buyHoldPeriod |> varBy (fun x -> x.Return)
 
 (** Now our managed portfolio. *)
 
-let avgReturn = result |> List.averageBy (fun x -> x.Return)
-let varResult = result |> varBy (fun x -> x.Return)
+let avgManagedReturn = result |> List.averageBy (fun x -> x.Return)
+let varManagedResult = result |> varBy (fun x -> x.Return)
 
-(avgReturn - (3.0/2.0) * varResult)*252.0
+(avgManagedReturn - (3.0/2.0) * varManagedResult)*252.0
 
 (** Why the difference? *)
 
 (** Try scaling managed to full sample variance. *)
-let c = sqrt varBuyHold / sqrt varResult
-(c * avgReturn - (3.0/2.0) * c ** 2.0 * varResult)*252.0
+let c = sqrt varBuyHold / sqrt varManagedResult
+(c * avgManagedReturn - (3.0/2.0) * c ** 2.0 * varManagedResult)*252.0
 
 (** Another way of seeing it.*)
 

diff --git a/docs/VolatilityManagedTypes.fsx b/docs/VolatilityManagedTypes.fsx
@@ -19,9 +19,9 @@ Last time we looked at volatility managed portfolios, but we hard coded the vola
 *)
 
 
-#r "nuget: FSharp.Data"
-#r "nuget: NovaSBE.Finance"
-#r "nuget: FSharp.Stats"
+#r "nuget: FSharp.Data, 5.0.2"
+#r "nuget: NovaSBE.Finance, 0.4.0"
+#r "nuget: FSharp.Stats, 0.5.0"
 #r "nuget: Plotly.NET, 3.*"
 #r "nuget: Plotly.NET.Interactive, 3.*"
 

diff --git a/docs/VolatilityTiming.fsx b/docs/VolatilityTiming.fsx
@@ -24,8 +24,8 @@ As a start, let's acquire a long daily time series on aggregate US market return
 
 *)
 
-#r "nuget: FSharp.Data"
-#r "nuget: NovaSBE.Finance"
+#r "nuget: FSharp.Data, 5.0.2"
+#r "nuget: NovaSBE.Finance, 0.4.0"
 open System
 open FSharp.Data
 open NovaSBE.Finance.French
@@ -47,7 +47,7 @@ ff3 |> List.take 5
 One thing that can help us manage volatility is the fact that volatility tends to be somewhat persistent. By this we mean that if our risky asset is volatile today, then it is likely to be volatile tomorrow. We can observe this by plotting monthly volatility as we do below. It also means that we can use recent past volatility to form estimates of future volatility.
 *)
 
-#r "nuget: FSharp.Stats"
+#r "nuget: FSharp.Stats, 0.5.0"
 #r "nuget: Plotly.NET, 3.*"
 #r "nuget: Plotly.NET.Interactive, 3.*"
 
@@ -76,9 +76,11 @@ testMonth
 let testMonthGroup, testMonthObs = testMonth
 (** testMonthGroup *)
 testMonthGroup
+(***include-it***)
 
 (** testMonthXS *)
-testMonthObs
+testMonthObs |> List.take 3
+(***include-it***)
 
 (** Test month return standard deviation. *)
 testMonthObs

diff --git a/docs/YahooFinance.fsx b/docs/YahooFinance.fsx
@@ -4,7 +4,7 @@
 Based on code from https://github.com/aexsalomao/YahooFinance/
 *)
 
-#r "nuget: FSharp.Data"
+#r "nuget: FSharp.Data, 5.0.2"
 
 open System
 open FSharp.Data

diff --git a/docs/assignment-risky-weights.fsx b/docs/assignment-risky-weights.fsx
@@ -27,8 +27,8 @@ All work that you submit should be your own. Make use of the course resources an
 
 *)
 
-#r "nuget:FSharp.Data"
-#r "nuget: FSharp.Stats"
+#r "nuget: FSharp.Data, 5.0.2"
+#r "nuget: FSharp.Stats, 0.5.0"
 #r "nuget: Quotes.YahooFinance"
 #r "nuget: Plotly.NET, 3.*"
 (*** condition: ipynb ***)

diff --git a/docs/assignment-volatility-timing.fsx b/docs/assignment-volatility-timing.fsx
@@ -28,8 +28,8 @@ All work that you submit should be your own. Make use of the course resources an
 
 *)
 
-#r "nuget:FSharp.Data"
-#r "nuget: FSharp.Stats"
+#r "nuget: FSharp.Data, 5.0.2"
+#r "nuget: FSharp.Stats, 0.5.0"
 #r "nuget: Plotly.NET, 3.*"
 (*** condition: ipynb ***)
 #r "nuget: Plotly.NET.Interactive, 3.*"
@@ -73,7 +73,7 @@ Formatter.SetPreferredMimeTypesFor(typeof<GenericChart.GenericChart>,"text/html"
 We get the Fama-French 3-Factor asset pricing model data.
 *)
 
-#r "nuget: NovaSBE.Finance"
+#r "nuget: NovaSBE.Finance, 0.4.0"
 
 open NovaSBE.Finance
 open NovaSBE.Finance.French
@@ -453,4 +453,4 @@ let hmlAnnualizedReturn =
         hmlVolManaged
         |> List.averageBy (fun x -> x.Return)
     252.0 * dailyRet
-hmlAnnualizedReturn |> should (equalWithin 0.02) 8.18
+hmlAnnualizedReturn |> should (equalWithin 0.02) 8.15
diff --git a/docs/assignments/assignment-performance-evaluation.fsx b/docs/assignments/assignment-performance-evaluation.fsx
@@ -39,9 +39,9 @@ open FsUnitTyped
 For the assignment
 *)
 
-#r "nuget:FSharp.Data"
-#r "nuget: FSharp.Stats"
-#r "nuget: NovaSBE.Finance, 0.2.0-beta1"
+#r "nuget: FSharp.Data, 5.0.2"
+#r "nuget: FSharp.Stats, 0.5.0"
+#r "nuget: NovaSBE.Finance, 0.4.0"
 #r "nuget: MathNet.Numerics"
 #r "nuget: MathNet.Numerics.FSharp"
 #r "nuget: Plotly.NET, 3.*"

diff --git a/docs/assignments/assignment-signal-portfolio.fsx b/docs/assignments/assignment-signal-portfolio.fsx
@@ -40,9 +40,9 @@ open FsUnitTyped
 For the assignment
 *)
 
-#r "nuget:FSharp.Data"
-#r "nuget: FSharp.Stats"
-#r "nuget: NovaSBE.Finance, 0.2.0-beta1"
+#r "nuget: FSharp.Data, 5.0.2"
+#r "nuget: FSharp.Stats, 0.5.0"
+#r "nuget: NovaSBE.Finance, 0.4.0"
 #r "nuget: MathNet.Numerics"
 #r "nuget: MathNet.Numerics.FSharp"
 #r "nuget: Plotly.NET, 3.*"

diff --git a/docs/assignments/signal-exploration.fsx b/docs/assignments/signal-exploration.fsx
@@ -32,8 +32,8 @@ All work that you submit should be your own. Make use of the course resources an
 Load libraries.
 *)
 
-#r "nuget: FSharp.Data"
-#r "nuget: FSharp.Stats"
+#r "nuget: FSharp.Data, 5.0.2"
+#r "nuget: FSharp.Stats, 0.5.0"
 #r "nuget: Plotly.NET, 3.*"
 #r "nuget: Plotly.NET.Interactive, 3.*"
 #r "nuget: MathNet.Numerics"

diff --git a/docs/calls-nn.fsx b/docs/calls-nn.fsx
@@ -19,7 +19,8 @@ index: 100
 // !bash <(curl -Ls https://raw.githubusercontent.com/gbaydin/scripts/main/colab_dotnet6.sh)
 #endif // IPYNB
 
-(***do-not-eval***)
+(***do-not-eval-file***)
+
 #r "nuget:FSharp.Stats"
 // Use lite if you're on Apple Silicon
 //#r "nuget:DiffSharp-lite,1.0.7"

diff --git a/docs/football-1-download-data.fsx b/docs/football-1-download-data.fsx
@@ -31,7 +31,7 @@ For the **Football Players' Exercises** we are trying to scrape data from [Sport
 Both type providers are located in `FSharp.Data` assembly. To use it we need to load and open `FSharp.Data`.
 *)
 
-#r "nuget: FSharp.Data"
+#r "nuget: FSharp.Data, 5.0.2"
 open FSharp.Data
 
 (**

diff --git a/docs/football-collection-functions.fsx b/docs/football-collection-functions.fsx
@@ -62,8 +62,8 @@ let H3 = makeNumberedHeading "h3"
 ### Reference needed nuget packages and open namespaces
 *)
 
-#r "nuget:FSharp.Data"
-#r "nuget: FSharp.Stats"
+#r "nuget: FSharp.Data, 5.0.2"
+#r "nuget: FSharp.Stats, 0.5.0"
 
 open FSharp.Data
 open FSharp.Stats
@@ -799,7 +799,7 @@ playerStatsTable
 (**
 ### 9 Seq.stDev
 
-For `Seq.stDev` to work, we loaded the `FSharp.Stats nuget` (`#r "nuget: FSharp.Stats"`).
+For `Seq.stDev` to work, we loaded the `FSharp.Stats nuget` (`#r "nuget: FSharp.Stats, 0.5.0"`).
 This nuget contains the standard deviation function.
 Besides this we also opened the module `FSharp.Stats` (`open FSharp.Stats`).
 [FSharp.Stats documentation](https://fslab.org/FSharp.Stats/)

diff --git a/docs/football-plotting.fsx b/docs/football-plotting.fsx
@@ -50,8 +50,8 @@ let H3 = makeNumberedHeading "h3"
 ### Reference needed nuget packages and open namespaces
 *)
 
-#r "nuget:FSharp.Data"
-#r "nuget: FSharp.Stats"
+#r "nuget: FSharp.Data, 5.0.2"
+#r "nuget: FSharp.Stats, 0.5.0"
 #r "nuget: Plotly.NET, 3.*"
 #r "nuget: Plotly.NET.Interactive, 3.*"
 

diff --git a/docs/football-tuples-and-records.fsx b/docs/football-tuples-and-records.fsx
@@ -62,7 +62,7 @@ let H3 = makeNumberedHeading "h3"
 ## Import the Football Players Data from the Csv File
 *)
 
-#r "nuget:FSharp.Data"
+#r "nuget: FSharp.Data, 5.0.2"
 open FSharp.Data
 
 (**

diff --git a/docs/fundamentals.fsx b/docs/fundamentals.fsx
@@ -495,7 +495,7 @@ let stddev xs =
 But it is also convenient to use the [FSharp.Stats](https://fslab.org/FSharp.Stats/)
 *)
 
-#r "nuget: FSharp.Stats"
+#r "nuget: FSharp.Stats, 0.5.0"
 
 open FSharp.Stats
 

diff --git a/docs/mveComparisons.fsx b/docs/mveComparisons.fsx
@@ -18,16 +18,15 @@ index: 8
 ## Loading Fama and French data
 *)
 
-#r "nuget: FSharp.Data"
-#r "nuget: NovaSBE.Finance"
-#r "nuget: FSharp.Stats"
+#r "nuget: FSharp.Data, 5.0.2"
+#r "nuget: NovaSBE.Finance, 0.4.0"
+#r "nuget: FSharp.Stats, 0.5.0"
 #r "nuget: Plotly.NET, 3.*"
 #r "nuget: Plotly.NET.Interactive, 3.*"
 
 open System
 open FSharp.Data
 open FSharp.Stats
-open FSharp.Stats.Distributions.ContinuousDistribution
 open Plotly.NET
 open NovaSBE.Finance.French
 
@@ -55,7 +54,7 @@ let seed = 99
 Random.SetSampleGenerator(Random.RandThreadSafe(seed))
 
 // Let's start with this sample of returns
-let rnorm =  normal 0.01 1.0
+let rnorm =  Distributions.Continuous.Normal.Init 0.01 1.0
 let testData = 
     [| for i=1 to 100 do 
         { Date = DateTime(2010, 1, 1).AddDays(float i); 

diff --git a/docs/optimization.fsx b/docs/optimization.fsx
@@ -11,13 +11,13 @@ index: 12
 [![Notebook](img/badge-notebook.svg)]({{root}}/{{fsdocs-source-basename}}.ipynb)
 *)
 
-#r "nuget: FSharp.Stats"
-#r "nuget: FSharp.Data,5.*"
+#r "nuget: FSharp.Stats, 0.5.0"
+#r "nuget: FSharp.Data, 5.0.2"
 #r "nuget: DiffSharp-lite"
 #r "nuget: Plotly.NET, 3.*"
 #r "nuget: Plotly.NET.Interactive, 3.*"
 #r "nuget: Quotes.YahooFinance, 0.0.5"
-#r "nuget: NovaSBE.Finance"
+#r "nuget: NovaSBE.Finance, 0.4.0"
 
 open System
 open FSharp.Data

diff --git a/docs/performance-evaluation.fsx b/docs/performance-evaluation.fsx
@@ -34,11 +34,11 @@ The APT way of thinking is less restrictive than economically motivated equilibr
 
 *)
 
-#r "nuget: FSharp.Stats"
-#r "nuget: FSharp.Data"
+#r "nuget: FSharp.Stats, 0.5.0"
+#r "nuget: FSharp.Data, 5.0.2"
 #r "nuget: Plotly.NET, 3.*"
 #r "nuget: Plotly.NET.Interactive, 3.*"
-#r "nuget: NovaSBE.Finance"
+#r "nuget: NovaSBE.Finance, 0.4.0"
 
 (** *)
 #r "nuget: Quotes.YahooFinance, 0.0.5"

diff --git a/docs/portfolio-statistics.fsx b/docs/portfolio-statistics.fsx
@@ -654,7 +654,7 @@ For next time: Portfolio Variance and Leverage
 ## Leverage
 *)
 
-#r "nuget: FSharp.Stats"
+#r "nuget: FSharp.Stats, 0.5.0"
 
 open FSharp.Stats
 open FSharp.Stats.Correlation

diff --git a/docs/premiums.fsx b/docs/premiums.fsx
@@ -14,9 +14,9 @@ index: 14
 
 *)
 
-#r "nuget: NovaSBE.Finance,0.3.*-*"
-#r "nuget: FSharp.Stats,0.4.*"
-#r "nuget: FSharp.Data,5.*-*"
+#r "nuget: NovaSBE.Finance, 0.4.0"
+#r "nuget: FSharp.Stats, 0.5.0"
+#r "nuget: FSharp.Data, 5.0.2"
 #r "nuget: Plotly.NET, 3.*"
 #r "nuget: Plotly.NET.Interactive, 3.*"
 #r "nuget: ExcelProvider,2.*"

diff --git a/docs/project/.assign-project-signals.fsx b/docs/project/.assign-project-signals.fsx
@@ -1,4 +1,4 @@
-#r "nuget:FSharp.Data"
+#r "nuget: FSharp.Data, 5.0.2"
 open System
 open System.IO
 

diff --git a/docs/project/.prep-project-data.fsx b/docs/project/.prep-project-data.fsx
@@ -1,4 +1,4 @@
-#r "nuget: FSharp.Data"
+#r "nuget: FSharp.Data, 5.0.2"
 #r "nuget: FSharp.Collections.ParallelSeq"
 
 #time "on"