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Add new data structures and event handling classes for trading platform. Include base classes, value and bar structs, event arguments, emitters, listeners. Update ruleset for SonarLint.
This commit is contained in:
Miha Kralj
@@ -1,88 +1,88 @@
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using System.Linq;
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namespace QuanTAlib;
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using System;
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using System.Collections.Generic;
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/* <summary>
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ZSCORE: number of standard deviations from SMA
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Z-score describes a value's relationship to the mean of a series, as measured in
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terms of standard deviations from the mean. If a Z-score is 0, it indicates that
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the data point's score is identical to the mean score. A Z-score of 1.0 would
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indicate a value that is one standard deviation from the mean. Z-scores may be
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positive or negative, with a positive value indicating the score is above the
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mean and a negative score indicating it is below the mean.
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Sources:
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https://en.wikipedia.org/wiki/Z-score
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https://www.investopedia.com/terms/z/zscore.asp
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Calculation:
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std = std * STDEV(close, length)
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mean = SMA(close, length)
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ZSCORE = (close - mean) / std
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</summary> */
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public class ZSCORE_Series : TSeries {
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private readonly System.Collections.Generic.List<double> _buffer = new();
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protected readonly int _period;
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protected readonly bool _NaN;
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protected readonly TSeries _data;
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//core constructors
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public ZSCORE_Series(int period, bool useNaN) {
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_period = period;
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_NaN = useNaN;
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Name = $"ZSCORE({period})";
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}
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public ZSCORE_Series(TSeries source, int period, bool useNaN) : this(period, useNaN) {
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_data = source;
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Name = Name.Substring(0, Name.IndexOf(")")) + $", {(string.IsNullOrEmpty(_data.Name) ? "data" : _data.Name)})";
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_data.Pub += Sub;
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Add(_data);
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}
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public ZSCORE_Series() : this(period: 0, useNaN: false) { }
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public ZSCORE_Series(int period) : this(period: period, useNaN: false) { }
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public ZSCORE_Series(TBars source) : this(source.Close, 0, false) { }
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public ZSCORE_Series(TBars source, int period) : this(source.Close, period, false) { }
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public ZSCORE_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN) { }
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public ZSCORE_Series(TSeries source) : this(source, 0, false) { }
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public ZSCORE_Series(TSeries source, int period) : this(source: source, period: period, useNaN: false) { }
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//////////////////
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// core Add() algo
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public override (DateTime t, double v) Add((DateTime t, double v) TValue, bool update = false) {
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BufferTrim(buffer:_buffer, value:TValue.v, period:_period, update: update);
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double _sma = _buffer.Average();
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double _pvar = 0;
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for (int i = 0; i < _buffer.Count; i++) { _pvar += (_buffer[i] - _sma) * (_buffer[i] - _sma); }
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_pvar /= this._buffer.Count;
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double _psdev = Math.Sqrt(_pvar);
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double _zscore = (_psdev == 0) ? 1 : (TValue.v - _sma) / _psdev;
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var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _zscore);
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return base.Add(res, update);
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}
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public override (DateTime t, double v) Add(TSeries data) {
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if (data == null) { return (DateTime.Today, Double.NaN); }
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foreach (var item in data) { Add(item, false); }
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return _data.Last;
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}
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public (DateTime t, double v) Add(bool update) {
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return this.Add(TValue: _data.Last, update: update);
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}
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public (DateTime t, double v) Add() {
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return Add(TValue: _data.Last, update: false);
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}
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private new void Sub(object source, TSeriesEventArgs e) {
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Add(TValue: _data.Last, update: e.update);
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}
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//reset calculation
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public override void Reset() {
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_buffer.Clear();
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}
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using System.Linq;
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namespace QuanTAlib;
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using System;
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using System.Collections.Generic;
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/* <summary>
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ZSCORE: number of standard deviations from SMA
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Z-score describes a value's relationship to the mean of a series, as measured in
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terms of standard deviations from the mean. If a Z-score is 0, it indicates that
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the data point's score is identical to the mean score. A Z-score of 1.0 would
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indicate a value that is one standard deviation from the mean. Z-scores may be
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positive or negative, with a positive value indicating the score is above the
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mean and a negative score indicating it is below the mean.
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Sources:
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https://en.wikipedia.org/wiki/Z-score
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https://www.investopedia.com/terms/z/zscore.asp
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Calculation:
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std = std * STDEV(close, length)
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mean = SMA(close, length)
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ZSCORE = (close - mean) / std
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</summary> */
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public class ZSCORE_Series : TSeries {
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private readonly System.Collections.Generic.List<double> _buffer = new();
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protected readonly int _period;
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protected readonly bool _NaN;
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protected readonly TSeries _data;
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//core constructors
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public ZSCORE_Series(int period, bool useNaN) {
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_period = period;
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_NaN = useNaN;
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Name = $"ZSCORE({period})";
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}
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public ZSCORE_Series(TSeries source, int period, bool useNaN) : this(period, useNaN) {
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_data = source;
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Name = Name.Substring(0, Name.IndexOf(")")) + $", {(string.IsNullOrEmpty(_data.Name) ? "data" : _data.Name)})";
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_data.Pub += Sub;
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Add(_data);
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}
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public ZSCORE_Series() : this(period: 0, useNaN: false) { }
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public ZSCORE_Series(int period) : this(period: period, useNaN: false) { }
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public ZSCORE_Series(TBars source) : this(source.Close, 0, false) { }
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public ZSCORE_Series(TBars source, int period) : this(source.Close, period, false) { }
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public ZSCORE_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN) { }
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public ZSCORE_Series(TSeries source) : this(source, 0, false) { }
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public ZSCORE_Series(TSeries source, int period) : this(source: source, period: period, useNaN: false) { }
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//////////////////
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// core Add() algo
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public override (DateTime t, double v) Add((DateTime t, double v) TValue, bool update = false) {
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BufferTrim(buffer:_buffer, value:TValue.v, period:_period, update: update);
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double _sma = _buffer.Average();
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double _pvar = 0;
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for (int i = 0; i < _buffer.Count; i++) { _pvar += (_buffer[i] - _sma) * (_buffer[i] - _sma); }
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_pvar /= this._buffer.Count;
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double _psdev = Math.Sqrt(_pvar);
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double _zscore = (_psdev == 0) ? 1 : (TValue.v - _sma) / _psdev;
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var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _zscore);
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return base.Add(res, update);
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}
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public override (DateTime t, double v) Add(TSeries data) {
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if (data == null) { return (DateTime.Today, Double.NaN); }
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foreach (var item in data) { Add(item, false); }
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return _data.Last;
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}
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public (DateTime t, double v) Add(bool update) {
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return this.Add(TValue: _data.Last, update: update);
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}
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public (DateTime t, double v) Add() {
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return Add(TValue: _data.Last, update: false);
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}
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private new void Sub(object source, TSeriesEventArgs e) {
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Add(TValue: _data.Last, update: e.update);
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}
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//reset calculation
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public override void Reset() {
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_buffer.Clear();
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}
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}
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