test: setup common stability and robustness properties tracking

lib/statistics/acf/Acf.Quantower.Tests.cs

@@ -294,4 +294,4 @@ public class AcfIndicatorTests
             Assert.True(value >= -1 && value <= 1, $"ACF value at index {i} should be bounded [-1, 1], got {value}");
         }
     }
-}
+}

lib/statistics/acf/Acf.Tests.cs

@@ -539,4 +539,4 @@ public class AcfTests
     }
 
     #endregion
-}
+}

lib/statistics/acf/Acf.Validation.Tests.cs

@@ -114,11 +114,13 @@ public class AcfValidationTests
         // For white noise, ACF at any lag > 0 should be close to zero
         var acf = new Acf(100, 5);
 
-        // Generate pseudo-random values with zero mean via GBM log-returns
-        var random = new GBM(startPrice: 100.0, sigma: 1.0, seed: 42);
-        for (int i = 0; i < 500; i++)
+        // Generate incremental bar-to-bar log-returns: log(close_i / close_{i-1})
+        // These are approximately i.i.d. N(0, σ²·dt) — genuine white noise
+        var gbm = new GBM(startPrice: 100.0, sigma: 0.2, seed: 42);
+        var bars = gbm.Fetch(501, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
+        for (int i = 1; i < 501; i++)
         {
-            double val = Math.Log(random.Next().Close / 100.0); // ~N(0, vol²*dt) centered near 0
+            double val = Math.Log(bars[i].Close / bars[i - 1].Close); // incremental log-return
             acf.Update(new TValue(DateTime.UtcNow.AddSeconds(i), val));
         }
 
@@ -215,12 +217,15 @@ public class AcfValidationTests
 
         double[] ar1Data = new double[n];
         ar1Data[0] = 0;
-        var random = new GBM(startPrice: 100.0, sigma: 1.0, seed: 42);
+
+        // Use incremental bar-to-bar log-returns as i.i.d. noise: log(close_i / close_{i-1})
+        var gbm = new GBM(startPrice: 100.0, sigma: 0.2, seed: 42);
+        var bars = gbm.Fetch(n, DateTime.UtcNow.Ticks, TimeSpan.FromMinutes(1));
 
         // Generate AR(1) process
         for (int i = 1; i < n; i++)
         {
-            double epsilon = Math.Log(random.Next().Close / 100.0) * 0.1; // Small noise
+            double epsilon = Math.Log(bars[i].Close / bars[i - 1].Close) * 0.5; // incremental log-return scaled as noise
             ar1Data[i] = phi * ar1Data[i - 1] + epsilon;
         }
 
@@ -280,4 +285,4 @@ public class AcfValidationTests
     }
 
     #endregion
-}
+}

lib/statistics/acf/Acf.cs

@@ -42,12 +42,10 @@ public sealed class Acf : AbstractBase
     // Running sums for O(1) updates
     private double _sum;
     private double _sumSq;
-    private double _sumLagged;
 
     // Snapshot state for bar correction
     private double _p_sum;
     private double _p_sumSq;
-    private double _p_sumLagged;
 
     private int _updateCount;
     private const int ResyncInterval = 1000;
@@ -110,7 +108,6 @@ public sealed class Acf : AbstractBase
             // Snapshot state for rollback
             _p_sum = _sum;
             _p_sumSq = _sumSq;
-            _p_sumLagged = _sumLagged;
             _buffer.Snapshot();
         }
         else
@@ -118,7 +115,6 @@ public sealed class Acf : AbstractBase
             // Restore state from snapshot
             _sum = _p_sum;
             _sumSq = _p_sumSq;
-            _sumLagged = _p_sumLagged;
             _buffer.Restore();
         }
 
@@ -129,12 +125,6 @@ public sealed class Acf : AbstractBase
             _sum -= oldVal;
             _sumSq = Math.FusedMultiplyAdd(-oldVal, oldVal, _sumSq);
 
-            // Remove contribution to lagged sum
-            if (_buffer.Count > _lag)
-            {
-                double oldLaggedVal = _buffer[_lag]; // value that was _lag positions from oldest
-                _sumLagged -= oldVal * oldLaggedVal;
-            }
         }
 
         // Add new value
@@ -142,14 +132,6 @@ public sealed class Acf : AbstractBase
         _sum += value;
         _sumSq = Math.FusedMultiplyAdd(value, value, _sumSq);
 
-        // Update lagged sum: add product of new value and value at lag positions before
-        if (_buffer.Count > _lag)
-        {
-            int lagIndex = _buffer.Count - 1 - _lag;
-            double laggedVal = _buffer[lagIndex];
-            _sumLagged += value * laggedVal;
-        }
-
         if (isNew)
         {
             _updateCount++;
@@ -257,18 +239,11 @@ public sealed class Acf : AbstractBase
         int n = _buffer.Count;
         _sum = 0;
         _sumSq = 0;
-        _sumLagged = 0;
-
         for (int i = 0; i < n; i++)
         {
             double val = _buffer[i];
             _sum += val;
             _sumSq += val * val;
-
-            if (i >= _lag)
-            {
-                _sumLagged += val * _buffer[i - _lag];
-            }
         }
     }
 
@@ -277,19 +252,18 @@ public sealed class Acf : AbstractBase
         _buffer.Clear();
         _sum = 0;
         _sumSq = 0;
-        _sumLagged = 0;
         _p_sum = 0;
         _p_sumSq = 0;
-        _p_sumLagged = 0;
         _updateCount = 0;
         Last = default;
     }
 
     public override void Prime(ReadOnlySpan<double> source, TimeSpan? step = null)
     {
+        Reset();
         foreach (double value in source)
         {
-            Update(new TValue(DateTime.UtcNow, value));
+            Update(new TValue(DateTime.MinValue, value));
         }
     }
 

lib/statistics/acf/Acf.md

@@ -15,7 +15,7 @@
 - Parameterized by `period`, `lag` (default 1).
 - Output range: Varies (see docs).
 - Requires `period` bars of warmup before first valid output (IsHot = true).
-- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
+- Validated against mathematical properties and theoretical AR-process expectations.
 
 > "The past doesn't predict the future, but it whispers patterns to those who listen."