doc headers

lib/statistics/hurst/Hurst.Validation.Tests.cs

@@ -1,6 +1,4 @@
 
-using OoplesFinance.StockIndicators;
-using OoplesFinance.StockIndicators.Models;
 // HURST Validation Tests - Hurst Exponent via Rescaled Range (R/S) Analysis
 // Validated against self-consistency and known mathematical properties
 // No external library provides a direct R/S-based Hurst exponent equivalent
@@ -183,23 +181,4 @@ public sealed class HurstValidationTests
         Assert.Equal(h1.Last.Value, h2.Last.Value, 1e-15);
     }
 
-    [Fact(Skip = "CalculateEhlersHurstCoefficient produces 0 finite values on 500-bar dataset — requires an extremely long warmup (1000+ bars). Not comparable with synthetic GBM input.")]
-    public void Hurst_MatchesOoples_Structural()
-    {
-        var gbm = new GBM(startPrice: 100.0, mu: 0.02, sigma: 0.15, seed: 42);
-        var bars = gbm.Fetch(500, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
-        var ooplesData = bars.Select(b => new TickerData
-        {
-            Date = new DateTime(b.Time, DateTimeKind.Utc),
-            Open = b.Open,
-            High = b.High,
-            Low = b.Low,
-            Close = b.Close,
-            Volume = b.Volume
-        }).ToList();
-        var result = new StockData(ooplesData).CalculateEhlersHurstCoefficient();
-        var values = result.OutputValues.Values.First();
-        int finiteCount = values.Count(v => double.IsFinite(v));
-        Assert.True(finiteCount > 100, $"Expected >100 finite values, got {finiteCount}");
-    }
 }

lib/statistics/hurst/Hurst.md

@@ -1,5 +1,22 @@
 # HURST: Hurst Exponent
 
+| Property         | Value                            |
+| ---------------- | -------------------------------- |
+| **Category**     | Statistic                        |
+| **Inputs**       | Source (close)                          |
+| **Parameters**   | `period`                      |
+| **Outputs**      | Single series (Hurst)                       |
+| **Output range** | Varies (see docs)                     |
+| **Warmup**       | `period + 1` bars                          |
+
+### TL;DR
+
+- The Hurst Exponent ($H$) quantifies long-range dependence in a time series through Rescaled Range (R/S) analysis.
+- Parameterized by `period`.
+- Output range: Varies (see docs).
+- Requires `period + 1` bars of warmup before first valid output (IsHot = true).
+- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
+
 > "The past is not dead. In fact, it's not even past." — William Faulkner, and also every mean-reverting time series that refuses to forget.
 
 ## Introduction