Update RSI_Series to check for period != 0 before calculating RSI

2026-08-25 05:48:06 +00:00 · 2023-04-27 22:23:50 -07:00
parent c80f57ddab
commit abdcbf5f20
145 changed files with 4826 additions and 4207 deletions
@@ -0,0 +1,99 @@
+namespace QuanTAlib;
+using System;
+using System.Collections.Generic;
+using System.Linq;
+
+/* <summary>
+KURTOSIS: 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
+    KURTOSIS = 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 : TSeries {
+	protected readonly int _period;
+	protected readonly bool _NaN;
+	protected readonly TSeries _data;
+	private readonly System.Collections.Generic.List<double> _buffer = new();
+
+	//core constructors
+	public KURTOSIS_Series(int period, bool useNaN) : base() {
+		_period = period;
+		_NaN = useNaN;
+		Name = $"KURTOSIS({period})";
+	}
+	public KURTOSIS_Series(TSeries source, int period, bool useNaN) : this(period, useNaN) {
+		_data = source;
+		Name = Name.Substring(0, Name.IndexOf(")")) + $", {(string.IsNullOrEmpty(_data.Name) ? "data" : _data.Name)})";
+		_data.Pub += Sub;
+		Add(_data);
+	}
+	public KURTOSIS_Series() : this(period: 0, useNaN: false) { }
+	public KURTOSIS_Series(int period) : this(period: period, useNaN: false) { }
+	public KURTOSIS_Series(TSeries source) : this(source, period: 0, useNaN: false) { }
+	public KURTOSIS_Series(TSeries source, int period) : this(source: source, period: period, useNaN: false) { }
+
+	//////////////////
+	// core Add() algo
+	public override (DateTime t, double v) Add((DateTime t, double v) TValue, bool update = false) {
+		if (double.IsNaN(TValue.v)) {
+			return base.Add((TValue.t, Double.NaN), update);
+		}
+
+		BufferTrim(buffer: _buffer, value: TValue.v, period: _period, update: update);
+		double _n = _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) * _s4) / (_Vx * _Vx * (_n - 3) * (_n - 1) * (_n - 2)) - (3 * (_n - 1) * (_n - 1) / ((_n - 2) * (_n - 3))) //using Sheskin Algo
+	: (_s2 * _s2) / _n - 3; //using Snedecor and Cochran (1967) algo
+		var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _kurt);
+		return base.Add(res, update);
+	}
+
+	public override (DateTime t, double v) Add(TSeries data) {
+		if (data == null) { return (DateTime.Today, Double.NaN); }
+		foreach (var item in data) { Add(item, false); }
+		return _data.Last;
+	}
+	public new (DateTime t, double v) Add((DateTime t, double v) TValue) {
+		return Add(TValue, false);
+	}
+	public (DateTime t, double v) Add(bool update) {
+		return this.Add(TValue: _data.Last, update: update);
+	}
+	public (DateTime t, double v) Add() {
+		return Add(TValue: _data.Last, update: false);
+	}
+	private new void Sub(object source, TSeriesEventArgs e) {
+		Add(TValue: _data.Last, update: e.update);
+	}
+
+	//reset calculation
+	public override void Reset() {
+		_buffer.Clear();
+	}
+}