COVAR

semver fix VAR test fix new: COVAR, ZSCORE, CORR, LINREG versioning refactoring
2026-08-23 21:18:04 +00:00 · 2022-11-17 11:05:20 -08:00
parent fd2a686ba5
commit 73e3420379
59 changed files with 1225 additions and 1285 deletions
@@ -0,0 +1,57 @@
+namespace QuanTAlib;
+using System;
+using System.Linq;
+
+/* <summary>
+KURT: Kurtosis of population
+  Kurtosis characterizes the relative peakedness or flatness of a distribution
+  compared with the normal distribution. Positive kurtosis indicates a relatively
+  peaked distribution. Negative kurtosis indicates a relatively flat distribution.
+
+  The normal curve is called Mesokurtic curve. If the curve of a distribution is
+  more outlier prone (or heavier-tailed) than a normal or mesokurtic curve then
+  it is referred to as a Leptokurtic curve. If a curve is less outlier prone (or
+  lighter-tailed) than a normal curve, it is called as a platykurtic curve.
+
+Calculation:
+    sum4 = Σ(close-SMA)^4
+    sum2 = (Σ(close-SMA)^2)^2
+    KURT = length * (sum4/sum2)
+
+Sources:
+  https://en.wikipedia.org/wiki/Kurtosis
+  https://stats.oarc.ucla.edu/other/mult-pkg/faq/general/faq-whats-with-the-different-formulas-for-kurtosis/
+
+</summary> */
+
+public class KURTOSIS_Series : Single_TSeries_Indicator
+{
+    public KURTOSIS_Series(TSeries source, int period, double logbase = 2.0, bool useNaN = false) : base(source, period, useNaN)
+    {
+        this._logbase = logbase;
+        if (base._data.Count > 0) { base.Add(base._data); }
+    }
+    protected double _logbase;
+    private readonly System.Collections.Generic.List<double> _buffer = new();
+
+    public override void Add((System.DateTime t, double v) TValue, bool update)
+    {
+        Add_Replace_Trim(_buffer, TValue.v, _p, update);
+        double _n = this._buffer.Count;
+        double _avg = _buffer.Average();
+
+        double _s2 = 0;
+        double _s4 = 0;
+        for (int i = 0; i < this._buffer.Count; i++)
+        {
+            _s2 += (_buffer[i] - _avg) * (_buffer[i] - _avg);
+            _s4 += (_buffer[i] - _avg) * (_buffer[i] - _avg) * (_buffer[i] - _avg) * (_buffer[i] - _avg);
+        }
+
+        double _Vx = _s2 / (_n - 1);
+        double _kurt = (_n > 3) ? ((((_n * (_n + 1)) / (((_n - 1) * (_n - 2)) * (_n - 3))) * (_s4 / (_Vx * _Vx))) - (3 * (((_n - 1) * (_n - 1)) / ((_n - 2) * (_n - 3))))) : Double.NaN;
+
+        var result = (TValue.t, (this.Count < this._p - 1 && this._NaN) ? Double.NaN : _kurt);
+        base.Add(result, update);
+    }
+}