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MACD and RSI
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using System.Drawing;
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using TradingPlatform.BusinessLayer;
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namespace QuanTAlib;
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public class RSI_chart : Indicator
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{
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#region Parameters
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[InputParameter("Smoothing period", 0, 1, 999, 1, 1)]
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private int Period = 10;
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[InputParameter("Data source", 1, variants: new object[]
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{ "Open", 0, "High", 1, "Low", 2, "Close", 3, "HL2", 4, "OC2", 5,
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"OHL3", 6, "HLC3", 7, "OHLC4", 8, "Weighted (HLCC4)", 9 })]
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private int DataSource = 8;
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#endregion Parameters
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private TBars bars;
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///////
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private RSI_Series indicator;
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///////
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public RSI_chart()
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{
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this.SeparateWindow = true;
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this.Name = "RSI - Relative Strength Index";
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this.Description = "RSI description";
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this.AddLineSeries("RSI", Color.RoyalBlue, 3, LineStyle.Solid);
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}
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protected override void OnInit()
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{
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this.bars = new();
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this.ShortName =
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"RSI (" + TBars.SelectStr(this.DataSource) + ", " + this.Period + ")";
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this.indicator = new(source: bars.Select(this.DataSource),
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period: this.Period, useNaN: true);
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}
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protected override void OnUpdate(UpdateArgs args)
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{
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bool update = !(args.Reason == UpdateReason.NewBar ||
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args.Reason == UpdateReason.HistoricalBar);
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this.bars.Add(this.Time(), this.GetPrice(PriceType.Open),
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this.GetPrice(PriceType.High), this.GetPrice(PriceType.Low),
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this.GetPrice(PriceType.Close),
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this.GetPrice(PriceType.Volume), update);
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double result = this.indicator[this.indicator.Count - 1].v;
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this.SetValue(result, 0);
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}
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}
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namespace QuanTAlib;
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using System;
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/* <summary>
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MACD: Moving Average Convergence/Divergence
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Moving average convergence divergence (MACD) is a trend-following momentum
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indicator that shows the relationship between two moving averages of a series.
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The MACD is calculated by subtracting the 26-period exponential moving average (EMA)
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from the 12-period EMA. MACD Signal is 9-day EMA of MACD.
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Sources:
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https://www.investopedia.com/terms/m/macd.asp
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https://www.fidelity.com/learning-center/trading-investing/technical-analysis/technical-indicator-guide/macd
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</summary> */
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public class MACD_Series : Single_TSeries_Indicator
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{
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private EMA_Series _TSslow;
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private EMA_Series _TSfast;
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private SUB_Series _TSmacd;
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public EMA_Series Signal { get; }
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public MACD_Series(TSeries source, int slow = 26, int fast = 12, int signal = 9, bool useNaN = false)
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: base(source, period: 0, useNaN)
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{
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_TSslow = new(source: source, period: slow, useNaN: false);
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_TSfast = new(source: source, period: fast, useNaN: false);
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_TSmacd = new(_TSfast, _TSslow);
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Signal = new(source: _TSmacd, period: signal, useNaN: useNaN);
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if (source.Count > 0) { base.Add(_TSmacd); }
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}
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public override void Add((System.DateTime t, double v) TValue, bool update)
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{
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double _macd;
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if (update)
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{
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_TSslow.Add(TValue, true);
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_TSfast.Add(TValue, true);
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}
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_macd = this._TSmacd[(this.Count < this._TSmacd.Count) ? this.Count : this._TSmacd.Count - 1].v;
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var result = (TValue.t, _macd);
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base.Add(result, update);
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}
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}
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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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double _avgGain = 0;
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double _avgLoss = 0;
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double _lastValue = 0;
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double _lastlastValue = 0;
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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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{ if (source.Count > 0) { base.Add(source); } }
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public override void Add((System.DateTime t, double v) TValue, bool update)
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{
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int i = this.Count;
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double _rsi = 0;
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if (update) { _lastValue = _lastlastValue; }
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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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if (update) { _gain[_gain.Count - 1] = _gainval; } else { _gain.Add(_gainval); }
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if (_gain.Count > this._p) { _gain.RemoveAt(0); }
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double _lossval = (TValue.v < _lastValue) ? _lastValue - TValue.v : 0;
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if (update) { _loss[_loss.Count - 1] = _lossval; } else { _loss.Add(_lossval); }
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if (_loss.Count > this._p) { _loss.RemoveAt(0); }
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_lastlastValue = _lastValue;
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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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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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}
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