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58 lines
2.1 KiB
C#
58 lines
2.1 KiB
C#
namespace QuanTAlib;
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using System;
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/* <summary>
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SMMA: Smoothed Moving Average
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The Smoothed Moving Average (SMMA) is a combination of a SMA and an EMA. It gives the recent prices
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an equal weighting as the historic prices as it takes all available price data into account.
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The main advantage of a smoothed moving average is that it removes short-term fluctuations.
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SMMA(i) = (SMMA-1*(N-1) + CLOSE (i)) / N
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Sources:
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https://blog.earn2trade.com/smoothed-moving-average
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https://guide.traderevolution.com/traderevolution/mobile-applications/phone/android/technical-indicators/moving-averages/smma-smoothed-moving-average
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https://www.chartmill.com/documentation/technical-analysis-indicators/217-MOVING-AVERAGES-%7C-The-Smoothed-Moving-Average-%28SMMA%29
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</summary> */
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public class SMMA_Series : Single_TSeries_Indicator
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{
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private readonly System.Collections.Generic.List<double> _buffer = new();
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private double _lastsmma, _lastlastsmma;
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public SMMA_Series(TSeries source, int period, bool useNaN = false) : base(source, period, useNaN)
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{
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this._lastsmma = this._lastlastsmma = double.NaN;
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if (this._data.Count > 0) { base.Add(this._data); }
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}
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public override void Add((DateTime t, double v) TValue, bool update)
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{
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double _smma = 0;
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if (update) { this._lastsmma = this._lastlastsmma; }
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if (this.Count < this._p)
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{
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if (update) { this._buffer[this._buffer.Count - 1] = TValue.v; }
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else
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{
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this._buffer.Add(TValue.v);
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}
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if (this._buffer.Count > this._p) { this._buffer.RemoveAt(0); }
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for (int i = 0; i < this._buffer.Count; i++) { _smma += this._buffer[i]; }
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_smma /= this._buffer.Count;
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}
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else
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{
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_smma = ((_lastsmma * (_p-1)) + TValue.v) / _p ;
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}
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this._lastlastsmma = this._lastsmma;
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this._lastsmma = _smma;
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var ret = (TValue.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _smma);
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base.Add(ret, update);
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}
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} |