docs: remove C# Implementation Considerations sections, clean up temp scripts, reorganize test files

- Remove 'C# Implementation Considerations' sections from 34 indicator .md files - Delete 29 temp PowerShell scripts (_fix_mojibake.ps1, _hex_scan.ps1, etc.) - Move test files into tests/ subdirectories for consistent project structure - Add trader-focused bullet points to indicator documentation
2026-08-22 20:48:04 +00:00 · 2026-03-12 12:34:16 -07:00
parent 8937b0c0fa
commit 060649192f
1149 changed files with 1780 additions and 3316 deletions
@@ -0,0 +1,171 @@
+using Skender.Stock.Indicators;
+using TALib;
+
+namespace QuanTAlib.Tests;
+
+public sealed class BetaValidationTests : IDisposable
+{
+    private readonly ValidationTestData _data;
+
+    public BetaValidationTests()
+    {
+        _data = new ValidationTestData();
+    }
+
+    public void Dispose()
+    {
+        _data.Dispose();
+    }
+
+    [Fact]
+    public void Validate_Against_Skender()
+    {
+        // Generate Market Data (use existing Data)
+        var marketQuotes = _data.Data;
+
+        // Generate Asset Data correlated to Market
+        // Asset Returns = 1.5 * Market Returns + Noise
+        var assetQuotes = new List<TBar>();
+        double assetPrice = 100;
+        const double targetBeta = 1.5;
+
+        // Use GBM for noise generation (sigma=0.2 gives ~0.0006 per step noise which matches original random noise level)
+        var noiseGbm = new GBM(startPrice: 100, mu: 0, sigma: 0.2, seed: 777);
+
+        assetQuotes.Add(new TBar(marketQuotes[0].Time, assetPrice, assetPrice, assetPrice, assetPrice, 1000));
+
+        for (int i = 1; i < marketQuotes.Count; i++)
+        {
+            double marketReturn = (marketQuotes[i].Value - marketQuotes[i - 1].Value) / marketQuotes[i - 1].Value;
+
+            // Get noise from GBM return
+            var noiseBar = noiseGbm.Next();
+            double noise = (noiseBar.Close - noiseBar.Open) / noiseBar.Open;
+
+            double assetReturn = targetBeta * marketReturn + noise;
+
+            assetPrice *= (1 + assetReturn);
+            assetQuotes.Add(new TBar(marketQuotes[i].Time, assetPrice, assetPrice, assetPrice, assetPrice, 1000));
+        }
+
+        // Skender
+        // Skender expects IEnumerable<Quote>
+        var skenderMarket = marketQuotes.Select(x => new Quote { Date = x.AsDateTime, Close = (decimal)x.Value }).ToList();
+        var skenderAsset = assetQuotes.Select(x => new Quote { Date = x.AsDateTime, Close = (decimal)x.Close }).ToList();
+
+        int period = 20;
+        var skenderBeta = skenderAsset.GetBeta(skenderMarket, period).ToList();
+
+        // QuanTAlib
+        var beta = new Beta(period);
+        var qlBeta = new List<double>();
+
+        for (int i = 0; i < marketQuotes.Count; i++)
+        {
+            var result = beta.Update(assetQuotes[i].Close, marketQuotes[i].Value);
+            qlBeta.Add(result.Value);
+        }
+
+        // Compare
+        // Skip warmup period. Skender Beta needs period returns, so period+1 prices?
+        // Skender results align with input quotes.
+        // First valid value should be at index 'period'.
+
+        // We verify the last 100 values
+        int count = qlBeta.Count;
+        int skip = period + 5; // Safety margin
+
+        for (int i = skip; i < count; i++)
+        {
+            double sk = (skenderBeta[i].Beta ?? 0);
+            double ql = qlBeta[i];
+
+            // Skender might return null/0 for warmup.
+            if (Math.Abs(sk) > 1e-10)
+            {
+                Assert.Equal(sk, ql, ValidationHelper.DefaultTolerance);
+            }
+        }
+    }
+
+    [Fact]
+    public void Validate_Against_Talib()
+    {
+        // TALib Beta takes two price series (e.g. stock vs market returns via price series).
+        // TALib.Functions.Beta(stockPrices, marketPrices, range, output, outRange, period)
+        // Internally computes beta from price returns within each rolling window.
+        //
+        // Note: TALib Beta uses a different return calculation (price[i]/price[i-1] - 1)
+        // and a different beta formula (covariance/variance from returns) than Skender.
+        // QuanTAlib Beta matches Skender (covariance of returns / variance of market returns).
+        // Direct numeric equality with TALib is not expected; we verify structural properties.
+
+        var marketQuotes = _data.Data;
+
+        // Build correlated asset prices
+        var noiseGbm = new GBM(startPrice: 100, mu: 0, sigma: 0.2, seed: 999);
+        double assetPrice = 100;
+        const double targetBeta = 1.2;
+
+        var assetPrices = new double[marketQuotes.Count];
+        var marketPrices = new double[marketQuotes.Count];
+        assetPrices[0] = assetPrice;
+        marketPrices[0] = marketQuotes[0].Value;
+
+        for (int i = 1; i < marketQuotes.Count; i++)
+        {
+            double mktReturn = (marketQuotes[i].Value - marketQuotes[i - 1].Value) / marketQuotes[i - 1].Value;
+            var noiseBar = noiseGbm.Next();
+            double noise = (noiseBar.Close - noiseBar.Open) / noiseBar.Open;
+            double astReturn = targetBeta * mktReturn + noise * 0.1;
+            assetPrice *= (1 + astReturn);
+            assetPrices[i] = assetPrice;
+            marketPrices[i] = marketQuotes[i].Value;
+        }
+
+        const int period = 20;
+
+        // TALib Beta
+        double[] taOut = new double[marketPrices.Length];
+        var retCode = Functions.Beta<double>(
+            assetPrices.AsSpan(), marketPrices.AsSpan(),
+            0..^0, taOut, out var outRange, period);
+        Assert.Equal(TALib.Core.RetCode.Success, retCode);
+
+        (int offset, int length) = outRange.GetOffsetAndLength(taOut.Length);
+
+        // Verify TALib produces finite values
+        Assert.True(length > 0, "TALib Beta produced no output");
+        for (int j = 0; j < length; j++)
+        {
+            Assert.True(double.IsFinite(taOut[j]),
+                $"TALib Beta[{j}] = {taOut[j]} is not finite");
+        }
+
+        // QuanTAlib Beta
+        var beta = new Beta(period);
+        var qlBetaArr = new double[marketQuotes.Count];
+        for (int i = 0; i < marketQuotes.Count; i++)
+        {
+            qlBetaArr[i] = beta.Update(assetPrices[i], marketPrices[i]).Value;
+        }
+
+        // Both should produce finite values after warmup
+        for (int i = period + 5; i < marketQuotes.Count; i++)
+        {
+            Assert.True(double.IsFinite(qlBetaArr[i]), $"QuanTAlib Beta[{i}] is not finite");
+        }
+
+        // Sign agreement: positively correlated asset → >60% positive betas from both
+        int taPositive = 0;
+        int qlPositive = 0;
+        for (int j = 0; j < length; j++)
+        {
+            int qi = j + offset;
+            if (taOut[j] > 0) { taPositive++; }
+            if (qlBetaArr[qi] > 0) { qlPositive++; }
+        }
+        Assert.True(taPositive > length * 0.6, $"TALib Beta positive rate {taPositive}/{length} < 60%");
+        Assert.True(qlPositive > length * 0.6, $"QuanTAlib Beta positive rate {qlPositive}/{length} < 60%");
+    }
+}