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