mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-04 04:07:42 +00:00
78 lines
2.7 KiB
C#
78 lines
2.7 KiB
C#
namespace QuanTAlib;
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using System;
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/* <summary>
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RSI: Relative Strength Index
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Created by J. Welles Wilder, the Relative Strength Index measures strength
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of the winning/losing streak over N lookback periods on a scale of 0 to 100,
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to depict overbought and oversold conditions.
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Sources:
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https://www.investopedia.com/terms/r/rsi.asp
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</summary> */
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public class RSI_Series : Single_TSeries_Indicator
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{
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private readonly System.Collections.Generic.List<double> _gain = new();
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private readonly System.Collections.Generic.List<double> _loss = new();
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private double _avgGain, _avgLoss, _lastValue;
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private double _avgGain_o, _avgLoss_o, _lastValue_o;
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private int i;
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public RSI_Series(TSeries source, int period = 10, bool useNaN = false) : base(source, period: period, useNaN: useNaN) {
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i = 0;
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if (source.Count > 0) { base.Add(source); }
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}
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public override void Add((System.DateTime t, double v) TValue, bool update) {
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double _rsi = 0;
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if (update) {
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_lastValue = _lastValue_o;
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_avgGain = _avgGain_o;
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_avgLoss = _avgLoss_o;
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}
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else {
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_lastValue_o = _lastValue;
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_avgGain_o = _avgGain;
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_avgLoss_o = _avgLoss;
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}
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if (i == 0) { _lastValue = TValue.v; }
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double _gainval = (TValue.v > _lastValue) ? TValue.v - _lastValue : 0;
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Add_Replace_Trim(_gain, _gainval, _p, update);
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double _lossval = (TValue.v < _lastValue) ? _lastValue - TValue.v : 0;
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Add_Replace_Trim(_loss, _lossval, _p, update);
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_lastValue = TValue.v;
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// calculate RSI
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if (i > _p)
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{
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_avgGain = ((_avgGain * (_p - 1)) + _gain[_gain.Count - 1]) / _p;
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_avgLoss = ((_avgLoss * (_p - 1)) + _loss[_loss.Count - 1]) / _p;
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if (_avgLoss > 0) {
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double rs = _avgGain / _avgLoss;
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_rsi = 100 - (100 / (1 + rs));
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}
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else { _rsi = 100; }
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}
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// initialize average gain
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else
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{
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double _sumGain = 0;
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for (int p = 0; p < _gain.Count; p++) { _sumGain += _gain[p]; }
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double _sumLoss = 0;
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for (int p = 0; p < _loss.Count; p++) { _sumLoss += _loss[p]; }
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_avgGain = _sumGain / _gain.Count;
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_avgLoss = _sumLoss / _loss.Count;
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_rsi = (_avgLoss > 0) ? 100 - (100 / (1 + (_avgGain / _avgLoss))) : 100;
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}
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if (!update) { i++; }
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var result = (TValue.t, (this.Count < this._p && this._NaN) ? double.NaN : _rsi);
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base.Add(result, update);
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}
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} |