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Miha Kralj
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@@ -1,159 +1,159 @@
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namespace QuanTAlib;
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using System;
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/* <summary>
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JMA: Jurik Moving Average
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Mark Jurik's Moving Average (JMA) attempts to eliminate noise to see the
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underlying activity. It has extremely low lag, is very smooth and is responsive
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to market gaps.
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Sources:
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https://c.mql5.com/forextsd/forum/164/jurik_1.pdf
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https://www.prorealcode.com/prorealtime-indicators/jurik-volatility-bands/
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Issues:
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Real JMA algorithm is not published and this formula is derived through
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deduction and reverse analysis of JMA behavior. It is really close, but not
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exact - published JMA tests against JMA.CSV fail with small deviation. The
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original algo is slightly different, yet this approximation is close enough.
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</summary> */
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public class JMA_Series : Single_TSeries_Indicator
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{
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private readonly System.Collections.Generic.List<double> vbuffer10;
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private readonly System.Collections.Generic.List<double> vsum65;
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private double prev_ma1, prev_det0, prev_det1, prev_jma, bsmax, bsmin;
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private double o_prev_ma1, o_prev_det0, o_prev_det1, o_prev_jma, o_bsmax, o_bsmin;
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private readonly double pr, pow1, len2, beta, rvolty;
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public JMA_Series(TSeries source, int period, double phase = 0.0, bool useNaN = false) : base(source, period, useNaN)
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{
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this.vbuffer10 = new();
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this.vsum65 = new();
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// constants
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this.pr = (phase < -100) ? 0.5 : (phase > 100) ? 2.5 : (phase * 0.01) + 1.5;
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double len1 = Math.Max((Math.Log(Math.Sqrt(0.5 * (_p - 1))) / Math.Log(2.0)) + 2.0, 0);
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this.pow1 = Math.Max(len1 - 2, 0.5);
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this.rvolty = Math.Exp((1 / this.pow1) * Math.Log(len1));
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this.len2 = Math.Sqrt(0.5 * (_p - 1)) * len1;
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this.beta = 0.45 * (_p - 1) / (0.45 * (_p - 1) + 2);
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if (base._data.Count > 0) { base.Add(base._data); }
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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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if (this.Count == 0)
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{
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this.prev_ma1 = this.prev_jma = TValue.v;
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this.bsmax = this.bsmin = this.prev_det0 = this.prev_det1 = 0;
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}
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if (update)
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{
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this.prev_jma = this.o_prev_jma;
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this.prev_ma1 = this.o_prev_ma1;
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this.prev_det0 = this.o_prev_det0;
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this.prev_det1 = this.o_prev_det1;
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this.bsmax = this.o_bsmax;
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this.bsmin = this.o_bsmin;
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}
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else
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{
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this.o_prev_jma = this.prev_jma;
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this.o_prev_ma1 = this.prev_ma1;
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this.o_prev_det0 = this.prev_det0;
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this.o_prev_det1 = this.prev_det1;
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this.o_bsmax = this.bsmax;
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this.o_bsmin = this.bsmin;
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}
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double hprice = TValue.v;
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double lprice = TValue.v;
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for (int i = 0; i <= Math.Min(9, this._data.Count - 1); i++)
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{
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var _item = this._data[this._data.Count - 1 - i].v;
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hprice = (_item > hprice) ? _item : hprice;
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lprice = (_item < lprice) ? _item : lprice;
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}
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double del1 = hprice - this.bsmax;
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double del2 = lprice - this.bsmin;
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double volty = (Math.Abs(del1) != Math.Abs(del2))
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? Math.Max(Math.Abs(del1), Math.Abs(del2))
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: 0;
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if (update)
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{
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this.vbuffer10[this.vbuffer10.Count - 1] = volty;
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}
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else
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{
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this.vbuffer10.Add(volty);
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}
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if (this.vbuffer10.Count > 10)
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{
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this.vbuffer10.RemoveAt(0);
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}
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double prevvsum =
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(this.vsum65.Count > 0) ? this.vsum65[this.vsum65.Count - 1] : 0;
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double vsumitem = prevvsum + 0.1 * (volty - this.vbuffer10[0]);
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if (update)
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{
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this.vsum65[this.vsum65.Count - 1] = vsumitem;
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}
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else
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{
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this.vsum65.Add(vsumitem);
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}
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if (this.vsum65.Count > 65)
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{
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this.vsum65.RemoveAt(0);
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}
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double avolty = 0;
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for (int i = 0; i < this.vsum65.Count; i++)
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{
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avolty += this.vsum65[i];
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}
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avolty /= this.vsum65.Count;
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double dvolty = (avolty > 0) ? volty / avolty : 0;
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dvolty = Math.Max((dvolty > this.rvolty) ? this.rvolty : dvolty, 1.0);
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double pow2 = Math.Exp(this.pow1 * Math.Log(dvolty));
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double kv =
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Math.Exp(Math.Sqrt(pow2) * Math.Log(this.len2 / (this.len2 + 1)));
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this.bsmax = (del1 > 0) ? hprice : hprice - (kv * del1);
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this.bsmin = (del2 < 0) ? lprice : lprice - (kv * del2);
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// adaptive EMA dynamic factor
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double pow = Math.Pow(dvolty, this.pow1);
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double alpha = Math.Pow(this.beta, pow);
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// 1st stage - preliminary smoothing by adaptive EMA
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double ma1 = TValue.v * (1 - alpha) + this.prev_ma1 * alpha;
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this.prev_ma1 = ma1;
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// 2nd stage - one more preliminary smoothing by Kalman filter
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double det0 = (TValue.v - ma1) * (1 - this.beta) + this.prev_det0 * this.beta;
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this.prev_det0 = det0;
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double ma2 = ma1 + (this.pr * det0);
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// 3rd stage - final smoothing by Jurik adaptive filter
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double det1 = ((ma2 - this.prev_jma) * (1 - alpha) * (1 - alpha)) +
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(this.prev_det1 * alpha * alpha);
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this.prev_det1 = det1;
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var jma = this.prev_jma + det1;
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this.prev_jma = jma;
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(System.DateTime t, double v) result =
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(TValue.t, (this.Count < this._p - 1 && this._NaN) ? double.NaN : jma);
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base.Add(result, update);
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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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JMA: Jurik Moving Average
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Mark Jurik's Moving Average (JMA) attempts to eliminate noise to see the
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underlying activity. It has extremely low lag, is very smooth and is responsive
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to market gaps.
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Sources:
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https://c.mql5.com/forextsd/forum/164/jurik_1.pdf
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https://www.prorealcode.com/prorealtime-indicators/jurik-volatility-bands/
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Issues:
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Real JMA algorithm is not published and this formula is derived through
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deduction and reverse analysis of JMA behavior. It is really close, but not
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exact - published JMA tests against JMA.CSV fail with small deviation. The
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original algo is slightly different, yet this approximation is close enough.
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</summary> */
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public class JMA_Series : Single_TSeries_Indicator
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{
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private readonly System.Collections.Generic.List<double> vbuffer10;
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private readonly System.Collections.Generic.List<double> vsum65;
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private double prev_ma1, prev_det0, prev_det1, prev_jma, bsmax, bsmin;
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private double o_prev_ma1, o_prev_det0, o_prev_det1, o_prev_jma, o_bsmax, o_bsmin;
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private readonly double pr, pow1, len2, beta, rvolty;
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public JMA_Series(TSeries source, int period, double phase = 0.0, bool useNaN = false) : base(source, period, useNaN)
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{
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this.vbuffer10 = new();
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this.vsum65 = new();
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// constants
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this.pr = (phase < -100) ? 0.5 : (phase > 100) ? 2.5 : (phase * 0.01) + 1.5;
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double len1 = Math.Max((Math.Log(Math.Sqrt(0.5 * (_p - 1))) / Math.Log(2.0)) + 2.0, 0);
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this.pow1 = Math.Max(len1 - 2, 0.5);
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this.rvolty = Math.Exp((1 / this.pow1) * Math.Log(len1));
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this.len2 = Math.Sqrt(0.5 * (_p - 1)) * len1;
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this.beta = 0.45 * (_p - 1) / (0.45 * (_p - 1) + 2);
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if (base._data.Count > 0) { base.Add(base._data); }
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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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if (this.Count == 0)
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{
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this.prev_ma1 = this.prev_jma = TValue.v;
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this.bsmax = this.bsmin = this.prev_det0 = this.prev_det1 = 0;
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}
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if (update)
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{
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this.prev_jma = this.o_prev_jma;
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this.prev_ma1 = this.o_prev_ma1;
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this.prev_det0 = this.o_prev_det0;
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this.prev_det1 = this.o_prev_det1;
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this.bsmax = this.o_bsmax;
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this.bsmin = this.o_bsmin;
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}
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else
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{
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this.o_prev_jma = this.prev_jma;
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this.o_prev_ma1 = this.prev_ma1;
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this.o_prev_det0 = this.prev_det0;
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this.o_prev_det1 = this.prev_det1;
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this.o_bsmax = this.bsmax;
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this.o_bsmin = this.bsmin;
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}
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double hprice = TValue.v;
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double lprice = TValue.v;
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for (int i = 0; i <= Math.Min(9, this._data.Count - 1); i++)
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{
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var _item = this._data[this._data.Count - 1 - i].v;
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hprice = (_item > hprice) ? _item : hprice;
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lprice = (_item < lprice) ? _item : lprice;
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}
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double del1 = hprice - this.bsmax;
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double del2 = lprice - this.bsmin;
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double volty = (Math.Abs(del1) != Math.Abs(del2))
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? Math.Max(Math.Abs(del1), Math.Abs(del2))
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: 0;
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if (update)
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{
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this.vbuffer10[this.vbuffer10.Count - 1] = volty;
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}
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else
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{
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this.vbuffer10.Add(volty);
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}
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if (this.vbuffer10.Count > 10)
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{
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this.vbuffer10.RemoveAt(0);
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}
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double prevvsum =
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(this.vsum65.Count > 0) ? this.vsum65[this.vsum65.Count - 1] : 0;
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double vsumitem = prevvsum + 0.1 * (volty - this.vbuffer10[0]);
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if (update)
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{
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this.vsum65[this.vsum65.Count - 1] = vsumitem;
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}
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else
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{
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this.vsum65.Add(vsumitem);
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}
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if (this.vsum65.Count > 65)
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{
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this.vsum65.RemoveAt(0);
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}
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double avolty = 0;
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for (int i = 0; i < this.vsum65.Count; i++)
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{
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avolty += this.vsum65[i];
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}
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avolty /= this.vsum65.Count;
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double dvolty = (avolty > 0) ? volty / avolty : 0;
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dvolty = Math.Max((dvolty > this.rvolty) ? this.rvolty : dvolty, 1.0);
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double pow2 = Math.Exp(this.pow1 * Math.Log(dvolty));
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double kv =
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Math.Exp(Math.Sqrt(pow2) * Math.Log(this.len2 / (this.len2 + 1)));
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this.bsmax = (del1 > 0) ? hprice : hprice - (kv * del1);
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this.bsmin = (del2 < 0) ? lprice : lprice - (kv * del2);
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// adaptive EMA dynamic factor
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double pow = Math.Pow(dvolty, this.pow1);
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double alpha = Math.Pow(this.beta, pow);
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// 1st stage - preliminary smoothing by adaptive EMA
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double ma1 = TValue.v * (1 - alpha) + this.prev_ma1 * alpha;
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this.prev_ma1 = ma1;
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// 2nd stage - one more preliminary smoothing by Kalman filter
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double det0 = (TValue.v - ma1) * (1 - this.beta) + this.prev_det0 * this.beta;
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this.prev_det0 = det0;
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double ma2 = ma1 + (this.pr * det0);
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// 3rd stage - final smoothing by Jurik adaptive filter
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double det1 = ((ma2 - this.prev_jma) * (1 - alpha) * (1 - alpha)) +
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(this.prev_det1 * alpha * alpha);
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this.prev_det1 = det1;
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var jma = this.prev_jma + det1;
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this.prev_jma = jma;
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(System.DateTime t, double v) result =
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(TValue.t, (this.Count < this._p - 1 && this._NaN) ? double.NaN : jma);
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base.Add(result, update);
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}
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}
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