mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-07 05:27:43 +00:00
Miha Kralj
99 lines
3.5 KiB
C#
99 lines
3.5 KiB
C#
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();
|
|
}
|
|
} |