namespace QuanTAlib; using System; /* ZSCORE: number of standard deviations from SMA Z-score describes a value's relationship to the mean of a series, as measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. A Z-score of 1.0 would indicate a value that is one standard deviation from the mean. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean. Sources: https://en.wikipedia.org/wiki/Z-score https://www.investopedia.com/terms/z/zscore.asp Calculation: std = std * STDEV(close, length) mean = SMA(close, length) ZSCORE = (close - mean) / std */ public class ZSCORE_Series : Single_TSeries_Indicator { public ZSCORE_Series(TSeries source, int period, bool useNaN = false) : base(source, period, useNaN) { if (base._data.Count > 0) { base.Add(base._data); } } private readonly System.Collections.Generic.List _buffer = new(); public override void Add((System.DateTime t, double v) TValue, bool update) { if (update) { _buffer[_buffer.Count - 1] = TValue.v; } else { _buffer.Add(TValue.v); } if (_buffer.Count > this._p && this._p != 0) { _buffer.RemoveAt(0); } double _sma = 0; for (int i = 0; i < _buffer.Count; i++) { _sma += _buffer[i]; } _sma /= this._buffer.Count; double _pvar = 0; for (int i = 0; i < _buffer.Count; i++) { _pvar += (_buffer[i] - _sma) * (_buffer[i] - _sma); } _pvar /= this._buffer.Count; double _psdev = Math.Sqrt(_pvar); double _zscore = (_psdev == 0) ? double.NaN : (TValue.v - _sma) / _psdev; var result = (TValue.t, (this.Count < this._p - 1 && this._NaN) ? double.NaN : _zscore); base.Add(result, update); } }