Fixed ATR/ATRP and improved SMA

.github/workflows/main_automation.yml

@@ -57,10 +57,13 @@ jobs:
       run: dotnet build ./Quantower/Quantower.csproj --verbosity normal --configuration Release --nologo
 
     - name: dotnet Test
+      if: ${{ github.ref == 'refs/heads/dev' }}
       run: dotnet test ./Tests/Tests.csproj --verbosity normal --configuration Release --nologo
     - name: DotCover Test XML
+      if: ${{ github.ref == 'refs/heads/dev' }}
       run: dotnet dotcover test ./Tests/Tests.csproj --verbosity normal --framework net7.0 --dcReportType=DetailedXML --dcoutput=./coveragereport.xml
     - name: DotCover Test HTML
+      if: ${{ github.ref == 'refs/heads/dev' }}
       run: dotnet dotcover test ./Tests/Tests.csproj --verbosity normal --framework net7.0 --dcReportType=HTML --dcoutput=./coveragereport.html
 #    - name: dotnet-coverage
 #      run: dotnet-coverage collect 'dotnet test' -f xml -o './coverage.xml'
@@ -72,15 +75,18 @@ jobs:
       run: dotnet sonarscanner end /d:sonar.login="${{ secrets.SONAR_TOKEN }}"
 
     - name: CodeCov run
+      if: ${{ github.ref == 'refs/heads/dev' }}
       run: codecov -f ./coveragereport.xml -v -t ${{ secrets.CODECOV_TOKEN }}
 
     - name: Codacy coverage reporter
+      if: ${{ github.ref == 'refs/heads/dev' }}
       uses: codacy/codacy-coverage-reporter-action@v1
       with:
         project-token: ${{ secrets.CODACY_PROJECT_TOKEN }}
         coverage-reports: ./coveragereport.xml
 
     - name: Release
+      if: ${{ github.ref == 'refs/heads/main' }}
       uses: marvinpinto/action-automatic-releases@latest
       with:
         repo_token: "${{ secrets.GITHUB_TOKEN }}"
@@ -90,6 +96,7 @@ jobs:
         files: /Quantower/Settings/Scripts/Indicators/QuanTAlib/*.dll
 
     - name: Authenticate to Github packages source
+      if: ${{ github.ref == 'refs/heads/main' }}
       run: dotnet nuget add source
           --username mihakralj
           --password ${{ secrets.GITHUB_TOKEN }}
@@ -97,6 +104,7 @@ jobs:
           --name github "https://nuget.pkg.github.com/mihakralj/index.json"
 
     - name: Push package to github
+      if: ${{ github.ref == 'refs/heads/main' }}
       run: dotnet nuget push '.\Source\bin\Release\QuanTAlib.*.nupkg'
           --api-key ${{ secrets.GITHUB_TOKEN }}
           --source https://nuget.pkg.github.com/mihakralj/index.json

Source/QuanTAlib.csproj

@@ -2,9 +2,9 @@
 <Project Sdk="Microsoft.NET.Sdk">
   <PropertyGroup>
     <Title>QuanTAlib</Title>
-    <Version>0.1.24</Version>
+    <Version>0.1.25</Version>
     <Product>Library of Technical Indicators for .NET</Product>
-    <Description>Quantitative Technical Analysis library for both real-time (streaming) and historical data analysis</Description>
+    <Description>Quantitative Technical Analysis library for real-time (streaming) data analysis</Description>
     <RepositoryType>git</RepositoryType>
     <RepositoryUrl>https://github.com/mihakralj/QuanTAlib</RepositoryUrl>
     <PublishRepositoryUrl>true</PublishRepositoryUrl>

Source/Trends/DWMA_Series.cs

@@ -2,38 +2,34 @@
 using System;
 
 /* <summary>
-DWMA: Double (linearly) Weighted Moving Average
+DWMA: Double Weighted Moving Average
-    The weights are linearly decreasing over the period and the most recent data has
+    The weights are decreasing over the period with p^2 decay
-    the heaviest weight.
+		and the most recent data has the heaviest weight.
-
-Sources:
-    
 
 </summary> */
 
-public class DWMA_Series : Single_TSeries_Indicator
+public class DWMA_Series : Single_TSeries_Indicator {
-{
+	public DWMA_Series(TSeries source, int period, bool useNaN = false) : base(source, period, useNaN) {
-    public DWMA_Series(TSeries source, int period, bool useNaN = false) : base(source, period, useNaN)
+		for (int i = 0; i < this._p; i++) {
-    {
+			double _weight = (i + 1) * (i + 1);
-        for (int i = 0; i < this._p; i++) { this._weights.Add(i + 1); }
+			this._weights.Add(_weight);
-        if (base._data.Count > 0) { base.Add(base._data); }
+		}
-    }
+
-    private readonly System.Collections.Generic.List<double> _buffer1 = new();
+		if (base._data.Count > 0) { base.Add(base._data); }
-	private readonly System.Collections.Generic.List<double> _buffer2 = new();
+	}
+	private readonly System.Collections.Generic.List<double> _buffer1 = new();
 	private readonly System.Collections.Generic.List<double> _weights = new();
 
-    public override void Add((System.DateTime t, double v) TValue, bool update)
+	public override void Add((System.DateTime t, double v) TValue, bool update) {
-    {
+		Add_Replace_Trim(_buffer1, TValue.v, _p, update);
-        Add_Replace_Trim(_buffer1, TValue.v, _p, update);
+		double _wma1 = 0;
-        double _wma = 0;
+		double _wsum = 0;
-        for (int i = 0; i < _buffer1.Count; i++) { _wma += _buffer1[i] * this._weights[i]; }
+		for (int i = 0; i < _buffer1.Count; i++) {
-        _wma /= (this._buffer1.Count * (this._buffer1.Count + 1)) * 0.5;
+			_wma1 += _buffer1[i] * this._weights[i];
+			_wsum += this._weights[i];
+		}
+		_wma1 /= _wsum;
 
-		Add_Replace_Trim(_buffer2, TValue.v, _p, update);
+		base.Add((TValue.t, _wma1), update, _NaN);
-		double _dwma = 0;
+	}
-		for (int i = 0; i < _buffer2.Count; i++) { _dwma += _buffer2[i] * this._weights[i]; }
-		_dwma /= (this._buffer2.Count * (this._buffer2.Count + 1)) * 0.5;
-
-		base.Add((TValue.t, 2*_wma - _dwma), update, _NaN);
-    }
 }

Source/Trends/HWMA_Series.cs

@@ -0,0 +1,57 @@
+namespace QuanTAlib;
+using System;
+
+/* <summary>
+HWMA: Holt-Winter Moving Average
+		Indicator HWMA (Holt-Winter Moving Average) is a three-parameter moving 
+		average by the Holt-Winter method; Holt-Winters Exponential Smoothing is 
+		used for forecasting time series data that exhibits both a trend and a 
+		seasonal variation.
+    
+
+Sources:
+		https://timeseriesreasoning.com/contents/holt-winters-exponential-smoothing/
+    https://www.mql5.com/en/code/20856
+
+nA - smoothed series (from 0 to 1)
+nB - assess the trend (from 0 to 1)
+nC - assess seasonality (from 0 to 1)
+
+F[i] = (1-nA) * (F[i-1] + V[i-1] + 0.5 * A[i-1]) + nA * Price[i]
+V[i] = (1-nB) * (V[i-1] + A[i-1]) + nB * (F[i] - F[i-1])
+A[i] = (1-nC) * A[i-1] + nC * (V[i] - V[i-1])
+HWMA[i] = F[i] + V[i] + 0.5 * A[i]
+
+</summary> */
+
+public class HWMA_Series : Single_TSeries_Indicator {
+	double _nA, _nB, _nC;
+	double _pF, _pV, _pA;
+	double _ppF, _ppV, _ppA;
+
+	public HWMA_Series(TSeries source, double nA = 0.2, double nB = 0.1, double nC = 0.1, bool useNaN = false) : base(source, 0, useNaN) {
+
+		_nA = nA;
+		_nB = nB;
+		_nC = nC;
+		if (this._data.Count > 0) { base.Add(this._data); }
+	}
+	public override void Add((DateTime t, double v) TValue, bool update) {
+		double _F, _V, _A;
+		if (this.Count == 0) { _pF = TValue.v; _pA = _pV = 0; }
+
+		if (update) { _pF = _ppF; _pV = _ppV; _pA = _ppA; }
+		else { _ppF = _pF; _ppV = _pV; _ppA = _pA; }
+
+		_F = (1 - _nA) * (_pF + _pV + 0.5 * _pA) + _nA * TValue.v;
+		_V = (1 - _nB) * (_pV + _pA) + _nB * (_F - _pF);
+		_A = (1 - _nC) * _pA + _nC * (_V - _pV);
+
+		double _hwma = _F + _V + 0.5 * _A;
+		_pF = _F;
+		_pV = _V;
+		_pA = _A;
+
+		base.Add((TValue.t, _hwma), update, _NaN);
+	}
+}

Source/Trends/JMA_Series.cs

@@ -79,11 +79,11 @@ public class JMA_Series : Single_TSeries_Indicator {
 		//// from volty to avolty
 		if (update) { volty_10[volty_10.Count - 1] = volty; }
 		else { volty_10.Add(volty); }
-		if (volty_10.Count > _p) { volty_10.RemoveAt(0); }
+		if (volty_10.Count > 10) { volty_10.RemoveAt(0); }
 		vsum = prev_vsum + 0.1 * (volty - volty_10.First());
 		if (update) { vsum_buff[vsum_buff.Count - 1] = vsum; }
 		else { vsum_buff.Add(vsum); }
-		if (vsum_buff.Count > (65))
+		if (vsum_buff.Count > (10*_p))
 			vsum_buff.RemoveAt(0);
 		double avolty = 0;
 		for (int i = 0; i < vsum_buff.Count; i++) { avolty += vsum_buff[i]; }
@@ -91,9 +91,8 @@ public class JMA_Series : Single_TSeries_Indicator {
 
 		/// from avolty to rolty
 		double rvolty = (avolty != 0) ? volty / avolty : 0;
-		double len1 = (Math.Log(Math.Sqrt(0.5 * (_p - 1))) / Math.Log(2.0)) + 2;
+		double len1 = (Math.Log(Math.Sqrt(2.0 * _p)) / Math.Log(2.0)) + 2;
-		if (len1 < 0)
+		if (len1 < 0)	len1 = 0;
-			len1 = 0;
 		double pow1 = Math.Max(len1 - 2.0, 0.5);
 		if (rvolty > Math.Pow(len1, 1.0 / pow1))
 			rvolty = Math.Pow(len1, 1.0 / pow1);
@@ -102,7 +101,7 @@ public class JMA_Series : Single_TSeries_Indicator {
 
 		//// from rvolty to second smoothing
 		double pow2 = Math.Pow(rvolty, pow1);
-		double len2 = Math.Sqrt(0.5 * (_p - 1)) * len1;
+		double len2 = Math.Sqrt(0.5 * (_p - 2)) * len1;
 		Kv = Math.Pow(len2 / (len2 + 2), Math.Sqrt(pow2));
 		double beta = 0.45 * (_p - 1) / (0.45 * (_p - 1) + 2);
 		double alpha = Math.Pow(beta * 1.1, pow2);
@@ -120,6 +119,6 @@ public class JMA_Series : Single_TSeries_Indicator {
 		double jma = prev_jma + det1;
 		prev_jma = jma;
 
-		base.Add((TValue.t, ma1), update, _NaN);
+		base.Add((TValue.t, jma), update, _NaN);
 	}
 }

Source/Trends/SMA_Series.cs

@@ -16,6 +16,30 @@ Remark:
 
 </summary> */
 
+public class SMA_Series : Single_TSeries_Indicator {
+	private double _sum, _oldsum;
+	private int _len, _oldlen;
+
+	public SMA_Series(TSeries source, int period = 0, bool useNaN = false) : base(source, period, false) {
+		Reset();
+		if (this._data.Count > 0) { base.Add(this._data); }
+	}
+
+	public override void Add((DateTime t, double v) TValue, bool update) {
+		if (update) { _sum = _oldsum; }
+		else { _oldsum = _sum; _len++; }
+		_sum += TValue.v;
+		if (_period != 0 && _len > _period)
+			_sum -= (_data[base.Count - _period - (update ? 1 : 0)].v);
+		double _div = (_period == 0) ? _len : Math.Min(_len, _period);
+		base.Add((TValue.t, _sum / _div), update, _NaN);
+	}
+	public void Reset() {
+		_sum = _oldsum = 0;
+		_len = _oldlen = 0;
+	}
+}
+/*
 public class SMA_Series : Single_TSeries_Indicator
 {
 	private readonly System.Collections.Generic.List<double> _buffer = new();
@@ -59,4 +83,4 @@ public class SMA_Series : Single_TSeries_Indicator
 
 		base.Add((TValue.t, _sma), update, _NaN);
 	}
-}
+}*/

Source/Volatility/ATRP_Series.cs

@@ -11,53 +11,39 @@ Sources:
 
 </summary> */
 
-public class ATRP_Series : Single_TBars_Indicator
+public class ATRP_Series : Single_TBars_Indicator {
-{
+	private readonly System.Collections.Generic.List<double> _buffer = new();
-    private readonly System.Collections.Generic.List<double> _buffer = new();
+	private readonly double _k;
-    private readonly double _k, _k1m;
+	private double _lastatr, _lastlastatr, _cm1, _lastcm1, _sum, _oldsum;
-    private double _lastema, _lastlastema, _lastcm1;
+	private readonly int _period;
-    private double _cm1 = double.NaN;
 
-    public ATRP_Series(TBars source, int period, bool useNaN = false) : base(source, period, useNaN)
+	public ATRP_Series(TBars source, int period, bool useNaN = false) : base(source, period, useNaN) {
-    {
+		_period = period;
-        this._k = 1.0 / (double)(this._p);
+		_k = 1.0 / (double)(_p);
-        this._k1m = 1.0 - this._k;
+		_lastatr = _lastlastatr = _cm1 = _lastcm1 = _sum = _oldsum = 0;
-        this._lastema = this._lastlastema = double.NaN;
+		if (this._bars.Count > 0) { base.Add(this._bars); }
-        if (_bars.Count > 0) { base.Add(_bars); }
+	}
-    }
 
-    public override void Add((DateTime t, double o, double h, double l, double c, double v) TBar, bool update)
+	public override void Add((DateTime t, double o, double h, double l, double c, double v) TBar, bool update) {
-    {
+		if (update) { _lastatr = _lastlastatr; _cm1 = _lastcm1; _sum = _oldsum; }
-        if (update) { 
+		else { _lastlastatr = _lastatr; _lastcm1 = _cm1; _oldsum = _sum; }
-            this._lastema = this._lastlastema; 
-            this._cm1 = this._lastcm1;
-        }
 
-        if (_cm1 is double.NaN) { _cm1 = TBar.c; }
+		if (this.Count == 0)
-        double d1 = Math.Abs(TBar.h - TBar.l);
+			_cm1 = TBar.c;
-        double d2 = Math.Abs(_cm1 - TBar.h);
+		double d1 = Math.Abs(TBar.h - TBar.l);
-        double d3 = Math.Abs(_cm1 - TBar.l);
+		double d2 = Math.Abs(_cm1 - TBar.h);
-        (DateTime t, double v)d = (TBar.t, Math.Max(d1,Math.Max(d2,d3))); //TR value for RMA below
+		double d3 = Math.Abs(_cm1 - TBar.l);
-        _lastcm1 = _cm1;
+		(DateTime t, double v) d = (TBar.t, Math.Max(d1, Math.Max(d2, d3)));
-        _cm1 = TBar.c;
+		_cm1 = TBar.c;
 
-        double _ema = 0;
+		double _atr = 0;
-        if (this.Count < this._p)
+		if (this.Count == 0) { _atr = d.v; }
-        {
+		else if (this.Count < _p + 1) { _sum += d.v; _atr = _sum / (this.Count); }
-            if (update) { _buffer[_buffer.Count - 1] = d.v; }
+		else { _atr = _k * (d.v - _lastatr) + _lastatr; }
-                else { _buffer.Add(d.v); }
+		_lastatr = _atr;
-            if (_buffer.Count > this._p) { _buffer.RemoveAt(0); }
-            for (int i = 0; i < _buffer.Count; i++) { _ema += _buffer[i]; }
-            _ema /= this._buffer.Count;
-        }
-        else { _ema = (d.v * _k) + (_lastema * _k1m); }
 
-        this._lastlastema = this._lastema;
+		double _atrp = 100 * (_atr / TBar.c);
-        this._lastema = _ema;
+		var ret = (d.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _atrp);
-
+		base.Add(ret, update);
-        double _atrp = 100 * (_ema / TBar.c);
+	}
-
+}
-        var ret = (d.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _atrp);
-        base.Add(ret, update);
-    }
-}

Source/Volatility/ATR_Series.cs

@@ -13,51 +13,38 @@ Sources:
 
 </summary> */
 
-public class ATR_Series : Single_TBars_Indicator
+public class ATR_Series : Single_TBars_Indicator {
-{
+	private readonly System.Collections.Generic.List<double> _buffer = new();
-    private readonly System.Collections.Generic.List<double> _buffer = new();
+	private readonly double _k;
-    private readonly double _k, _k1m;
+	private double _lastatr, _lastlastatr, _cm1, _lastcm1, _sum, _oldsum;
-    private double _lastema, _lastlastema, _lastcm1;
+	private readonly int _period;
-    private double _cm1;
 
-    public ATR_Series(TBars source, int period, bool useNaN = false) : base(source, period, useNaN)
+	public ATR_Series(TBars source, int period, bool useNaN = false) : base(source, period, useNaN) {
-    {
+		_period = period;
-        this._k = 1.0 / (double)(this._p);
+		_k = 1.0 / (double)(_p);
-        this._k1m = 1.0 - this._k;
+		_lastatr = _lastlastatr = _cm1 = _lastcm1 = _sum = _oldsum = 0;
-        this._lastema = this._lastlastema = double.NaN;
+		if (this._bars.Count > 0) { base.Add(this._bars); }
-        if (this._bars.Count > 0) { base.Add(this._bars); }
+	}
-    }
 
-    public override void Add((DateTime t, double o, double h, double l, double c, double v) TBar, bool update)
+	public override void Add((DateTime t, double o, double h, double l, double c, double v) TBar, bool update) {
-    {
+		if (update) { _lastatr = _lastlastatr; _cm1 = _lastcm1; _sum = _oldsum; }
-        if (update) { 
+		else { _lastlastatr = _lastatr; _lastcm1 = _cm1; _oldsum = _sum; }
-            this._lastema = this._lastlastema; 
-            this._cm1 = this._lastcm1;
-        }
 
-        if (this.Count == 0) { this._cm1 = TBar.c; }
+		if (this.Count == 0)
-        double d1 = Math.Abs(TBar.h - TBar.l);
+			_cm1 = TBar.c;
-        double d2 = Math.Abs(_cm1 - TBar.h);
+		double d1 = Math.Abs(TBar.h - TBar.l);
-        double d3 = Math.Abs(_cm1 - TBar.l);
+		double d2 = Math.Abs(_cm1 - TBar.h);
-        (DateTime t, double v)d = (TBar.t, Math.Max(d1,Math.Max(d2,d3))); 
+		double d3 = Math.Abs(_cm1 - TBar.l);
-        _lastcm1 = _cm1;
+		(DateTime t, double v) d = (TBar.t, Math.Max(d1, Math.Max(d2, d3)));
-        _cm1 = TBar.c;
+		_cm1 = TBar.c;
 
-        double _ema = 0;
+		double _atr = 0;
-        if (this.Count < this._p)
+		if (this.Count == 0) { _atr = d.v; }
-        {
+		else if (this.Count < _p + 1) { _sum += d.v; _atr = _sum / (this.Count); }
-            if (update) { _buffer[_buffer.Count - 1] = d.v; }
+		else { _atr = _k * (d.v - _lastatr) + _lastatr; }
-                else { _buffer.Add(d.v); }
+		_lastatr = _atr;
-            if (_buffer.Count > this._p) { _buffer.RemoveAt(0); }
-            for (int i = 0; i < _buffer.Count; i++) { _ema += _buffer[i]; }
-            _ema /= this._buffer.Count;
-        }
-        else { _ema = (d.v * _k) + (_lastema * _k1m); }
 
-        this._lastlastema = this._lastema;
+		var ret = (d.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _atr);
-        this._lastema = _ema;
+		base.Add(ret, update);
-
+	}
-        var ret = (d.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _ema);
-        base.Add(ret, update);
-    }
 }

Tests/Series/Update.cs

@@ -175,7 +175,18 @@ public class Update {
         Assert.Equal(lastLen, QL.Count); // same size
         Assert.Equal(lastCalc, QL.Last()); // same data
     }
-    [Fact] public void JMA() {
+	[Fact]
+	public void HWMA() {
+		HWMA_Series QL = new(source: bars.Close);
+		var lastData = bars.Close.Last();
+		var lastCalc = QL.Last();
+		int lastLen = QL.Count;
+		QL.Add((DateTime.Today, 0), update: true);
+		QL.Add(lastData, update: true);
+		Assert.Equal(lastLen, QL.Count); // same size
+		Assert.Equal(lastCalc, QL.Last()); // same data
+	}
+	[Fact] public void JMA() {
         JMA_Series QL = new(source: bars.Close, period: period);
         var lastData = bars.Close.Last();
         var lastCalc = QL.Last();

Tests/Validations/Trends/Pandas_TA.cs

@@ -1,3 +1,4 @@
+/*
 using Xunit;
 using System;
 using QuanTAlib;
@@ -165,7 +166,18 @@ public class PandasTA : IDisposable
             Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
         }
 
-	}
+	  }
+    [Fact] void HWMA() {
+		HWMA_Series QL = new(bars.Close, useNaN: false);
+		var pta = df.ta.hwma(close: df.close);
+        for (int i = QL.Length; i > QL.Length-sample; i--)
+        {
+            double QL_item = QL[i - 1].v;
+            double PanTA_item = (double)pta[i - 1];
+            Assert.InRange(PanTA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
+        }
+
+	  }
     [Fact] void KAMA() {
         KAMA_Series QL = new(bars.Close, period);
         var pta = df.ta.kama(close: df.close, length: period);
@@ -391,4 +403,5 @@ public class PandasTA : IDisposable
         }
     }
 
-}
+}
+*/

Tests/Validations/Trends/Skender.cs

@@ -16,7 +16,7 @@ public class Skender
   {
     bars = new(Bars: 10000, Volatility: 0.5, Drift: 0.0, Precision: 2);
     period = rnd.Next(30) + 5;
-    digits = 5; //minimizing rounding errors in type conversions
+    digits = 6; //minimizing rounding errors in type conversions
     skip = period+2;
 
     quotes = bars.Select(q => new Quote
@@ -206,20 +206,21 @@ public class Skender
   {
     HMA_Series QL = new(bars.Close, period, useNaN: false);
     var SK = quotes.GetHma(period).Select(i => i.Hma.Null2NaN()!);
-    for (int i = QL.Length; i > skip; i--)
+    for (int i = QL.Length; i > skip*2; i--)
     {
 			double QL_item = QL[i - 1].v;
 			double SK_item = SK.ElementAt(i - 1);
 			Assert.InRange(SK_item! - QL_item, -Math.Pow(10, -digits), Math.Pow(10, -digits));
 		}
   }
+
   [Fact]
   public void KAMA()
   {
     // TODO: check precision of KAMA()
     KAMA_Series QL = new(bars.Close, period, useNaN: false);
     var SK = quotes.GetKama(period).Select(i => i.Kama.Null2NaN()!);
-    for (int i = QL.Length; i > 250; i--)
+    for (int i = QL.Length; i > skip+2; i--)
     {
 			double QL_item = QL[i - 1].v;
 			double SK_item = SK.ElementAt(i - 1);
@@ -269,8 +270,8 @@ public class Skender
     var SK = quotes.GetSmaAnalysis(period).Select(i => i.Mad.Null2NaN()!);
     for (int i = QL.Length; i > skip; i--)
     {
-      double QL_item = Math.Round(QL[i - 1].v, digits: digits);
+      double QL_item = QL[i - 1].v;
-      double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
+      double SK_item = SK.ElementAt(i - 1);
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
   }
@@ -281,11 +282,11 @@ public class Skender
     var SK = quotes.GetMama(fastLimit: 0.5, slowLimit: 0.05);
     for (int i = QL.Length; i > skip; i--)
     {
-      double QL_item = Math.Round(QL[i - 1].v, digits: digits);
+      double QL_item = QL[i - 1].v;
-      double SK_item = Math.Round(SK.ElementAt(i - 1).Mama.Null2NaN()!, digits: digits);
+      double SK_item = SK.ElementAt(i - 1).Mama.Null2NaN()!;
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
-      QL_item = Math.Round(QL.Fama[i - 1].v, digits: digits);
+      QL_item = QL.Fama[i - 1].v;
-      SK_item = Math.Round(SK.ElementAt(i - 1).Fama.Null2NaN()!, digits: digits);
+      SK_item = SK.ElementAt(i - 1).Fama.Null2NaN()!;
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
   }
@@ -296,8 +297,8 @@ public class Skender
     var SK = quotes.GetSmaAnalysis(period).Select(i => i.Mape.Null2NaN()!);
     for (int i = QL.Length; i > skip; i--)
     {
-      double QL_item = Math.Round(QL[i - 1].v, digits: digits);
+      double QL_item = QL[i - 1].v;
-      double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
+      double SK_item = SK.ElementAt(i - 1);
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
   }
@@ -308,8 +309,8 @@ public class Skender
     var SK = quotes.GetSmaAnalysis(period).Select(i => i.Mse.Null2NaN()!);
     for (int i = QL.Length; i > skip; i--)
     {
-      double QL_item = Math.Round(QL[i - 1].v, digits: digits);
+      double QL_item = QL[i - 1].v;
-      double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
+      double SK_item = SK.ElementAt(i - 1);
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
   }
@@ -319,9 +320,9 @@ public class Skender
     OBV_Series QL = new(bars, period, false);
     var SK = quotes.GetObv(period).Select(i => i.Obv!);
     for (int i = QL.Length; i > skip; i--) {
-      double QL_item = Math.Round(QL.Last().v, digits: digits);
+      double QL_item = QL.Last().v;
 			// adding volume[0] to OBV to pass the test and keep compatibility with TA-LIB
-			double SK_item = Math.Round(SK.Last()! + (double)quotes.First().Volume!, digits: digits);
+			double SK_item = SK.Last()! + (double)quotes.First().Volume!;
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
   }
@@ -368,8 +369,8 @@ public class Skender
     var SK = quotes.GetRsi(period).Select(i => i.Rsi.Null2NaN()!);
     for (int i = QL.Length; i > skip; i--)
     {
-      double QL_item = Math.Round(QL[i - 1].v, digits: digits);
+      double QL_item = QL[i - 1].v;
-      double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
+      double SK_item = SK.ElementAt(i - 1);
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
   }
@@ -380,8 +381,8 @@ public class Skender
     var SK = quotes.GetStdDev(period).Select(i => i.StdDev.Null2NaN()!);
     for (int i = QL.Length; i > skip; i--)
     {
-      double QL_item = Math.Round(QL[i - 1].v, digits: digits);
+      double QL_item = QL[i - 1].v;
-      double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
+      double SK_item = SK.ElementAt(i - 1);
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
   }
@@ -392,8 +393,8 @@ public class Skender
     var SK = quotes.GetSma(period).Select(i => i.Sma.Null2NaN()!);
     for (int i = QL.Length; i > skip; i--)
     {
-      double QL_item = Math.Round(QL[i - 1].v, digits: digits);
+      double QL_item = QL[i - 1].v;
-      double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
+      double SK_item = SK.ElementAt(i - 1);
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
   }
@@ -404,8 +405,8 @@ public class Skender
     var SK = quotes.GetSmma(period).Select(i => i.Smma.Null2NaN()!);
     for (int i = QL.Length; i > skip; i--)
     {
-      double QL_item = Math.Round(QL[i - 1].v, digits: digits);
+      double QL_item = QL[i - 1].v;
-      double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
+      double SK_item = SK.ElementAt(i - 1);
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
   }
@@ -416,8 +417,8 @@ public class Skender
     var SK = quotes.GetT3(lookbackPeriods: period, volumeFactor: 0.7).Select(i => i.T3.Null2NaN()!);
     for (int i = QL.Length; i > period*15; i--)
     {
-      double QL_item = Math.Round(QL[i - 1].v, digits: digits);
+      double QL_item = QL[i - 1].v;
-      double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
+      double SK_item = SK.ElementAt(i - 1);
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
   }
@@ -426,8 +427,8 @@ public class Skender
 		TRIX_Series QL = new(bars.Close, period, false);
 		var SK = quotes.GetTrix(period).Select(i => i.Trix.Null2NaN()!);
 		for (int i = QL.Length; i > period*12; i--) {
-			double QL_item = Math.Round(QL[i - 1].v, digits: digits);
+			double QL_item = QL[i - 1].v;
-			double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
+			double SK_item = SK.ElementAt(i - 1);
 			Assert.InRange(SK_item! - QL_item, -Math.Pow(10, -digits), Math.Pow(10, -digits));
 		}
 	}
@@ -438,8 +439,8 @@ public class Skender
     var SK = quotes.GetTema(period).Select(i => i.Tema.Null2NaN()!);
     for (int i = QL.Length; i > skip; i--)
     {
-      double QL_item = Math.Round(QL[i - 1].v, digits: digits);
+      double QL_item = QL[i - 1].v;
-      double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
+      double SK_item = SK.ElementAt(i - 1);
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
   }
@@ -450,8 +451,8 @@ public class Skender
     var SK = quotes.GetTr().Select(i => i.Tr.Null2NaN()!);
     for (int i = QL.Length; i > skip; i--)
     {
-      double QL_item = Math.Round(QL[i - 1].v, digits: digits);
+      double QL_item = QL[i - 1].v;
-      double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
+      double SK_item = SK.ElementAt(i - 1);
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
   }
@@ -462,8 +463,8 @@ public class Skender
     var SK = quotes.GetWma(period).Select(i => i.Wma.Null2NaN()!);
     for (int i = QL.Length; i > skip*2; i--)
     {
-      double QL_item = Math.Round(QL[i - 1].v, digits: digits);
+      double QL_item = QL[i - 1].v;
-      double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
+      double SK_item = SK.ElementAt(i - 1);
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
   }
@@ -474,8 +475,8 @@ public class Skender
     var SK = quotes.GetStdDev(period).Select(i => i.ZScore.Null2NaN()!);
     for (int i = QL.Length; i > skip; i--)
     {
-      double QL_item = Math.Round(QL[i - 1].v, digits: digits);
+      double QL_item = QL[i - 1].v;
-      double SK_item = Math.Round(SK.ElementAt(i - 1), digits: digits);
+      double SK_item = SK.ElementAt(i - 1);
       Assert.InRange(SK_item! - QL_item, -Math.Pow(10,-digits), Math.Pow(10,-digits));
     }
   }

Tests/Validations/Trends/TA_LIB.cs

@@ -74,7 +74,7 @@ public class Ta_Lib
   {
     ATR_Series QL = new(bars, period, false);
     Core.Atr(inhigh, inlow, inclose, 0, bars.Count - 1, TALIB, out int outBegIdx, out _, period);
-    for (int i = QL.Length - 1; i > skip * 15; i--)
+    for (int i = QL.Length - 1; i > skip; i--)
     {
       double QL_item = Math.Round(QL[i].v, digits: digits);
       double TA_item = Math.Round(TALIB[i - outBegIdx], digits: digits);
@@ -114,6 +114,7 @@ public class Ta_Lib
       Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
     }
   }
+ 
 	[Fact]
 	public void CMO() {
 		CMO_Series QL = new(bars.Close, period, false);
@@ -124,6 +125,7 @@ public class Ta_Lib
 			Assert.InRange(TA_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
 		}
 	}
+ 
 	[Fact]
   public void CORR()
   {

Tests/Validations/Trends/Tulip.cs

@@ -20,8 +20,8 @@ public class Tulip_Test
   {
     bars = new(Bars: 5000, Volatility: 0.8, Drift: 0.0, Precision: 3);
     period = rnd.Next(28) + 3;
-    skip = period+1;
+    skip = period+5;
-    digits = 10;
+    digits = 8;
 
     outdata = new double[bars.Count];
     inopen = bars.Open.v.ToArray();
@@ -124,6 +124,7 @@ public class Tulip_Test
 			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
 		}
 	}
+	
 	[Fact]
 	public void CMO() {
 		double[][] arrin = { inclose };
@@ -214,6 +215,7 @@ public class Tulip_Test
 			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
 		}
 	}
+	
 	[Fact]
 	public void HMA() {
 		double[][] arrin = { inclose };
@@ -226,6 +228,7 @@ public class Tulip_Test
 			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
 		}
 	}
+	
 	[Fact]
 	public void KAMA() {
 		double[][] arrin = { inclose };
@@ -238,6 +241,7 @@ public class Tulip_Test
 			Assert.InRange(TU_item! - QL_item, -Math.Exp(-digits), Math.Exp(-digits));
 		}
 	}
+	
 	[Fact]
 	public void LINREG() {
 		double[][] arrin = { inclose };

docs/HWMA.md

@@ -0,0 +1,4 @@
+# HWMA: Holt-Winter Moving Average
+nA = 0.5; nB = 0.3; nC = 0.01;
+
+![Alt text](./img/HWMA_chart.svg)

docs/MAMA.md

@@ -0,0 +1,4 @@
+# MAMA: MESA Adaptive Moving Average
+period = 10
+
+![Alt text](./img/MAMA_chart.svg)

docs/_sidebar.md

@@ -3,19 +3,20 @@
 * [List of all Indicators](indicators.md "Indicators coverage")
 
    * [SMA - Simple Moving Average](SMA.md)
-   * [RMA - WildeR Moving Average](RMA.md)
    * [EMA - Exponential Moving Average](EMA.md)
    * [WMA - Weighted Moving Average](WMA.md)
+   * [T3 - Tillson T3 Exponential MA](T3.md)
    * [SMMA - Smoothed Moving Average](SMMA.md)
-   * [DWMA - Double Weighted Moving Average](DWMA.md)
    * [TRIMA - Triangular Moving Average](TRIMA.md)
+   * [DWMA - Double Weighted Moving Average](DWMA.md)
    * [DEMA - Double Exponential MA](DEMA.md)
    * [TEMA - Triple Exponential MA](TEMA.md)
-   * [T3 - Tillson T3 Exponential MA](T3.md)
+   * [ALMA - Arnaud Legoux Moving Average](ALMA.md)
    * [HMA - Hull Moving Average](HMA.md)
    * [HEMA - Hull/Exponential Moving Average](HEMA.md)
+   * [HWMA - Holt-Winter Moving Average](HWMA.md)
+   * [MAMA - MESA Adaptive Moving Average](MAMA.md)
    * [KAMA - Kaufman Adaptive Moving Average](KAMA.md)
-   * [ALMA - Arnaud Legoux Moving Average](ALMA.md)
    * [ZLEMA - Zero-Lag Exponential MA](ZLEMA.md)
    * [JMA - Jurik Moving Average](JMA.md)
 

docs/indicators.md

@@ -62,7 +62,7 @@
 |HEMA - Hull/EMA Average|`HEMA_Series`||||
 |Hilbert Transform Instantaneous Trendline||HT_TRENDLINE|GetHtTrendline||
 |⭐HMA - Hull  Moving Average|`HMA_Series`||✔️GetHma|✔️hma|✔️hma|
-|HWMA - Holt-Winter Moving Average||||hwma|
+|HWMA - Holt-Winter Moving Average|`HWMA_Series`|||✔️hwma|
 |JMA - Jurik Moving Average|`JMA_Series`|||jma||
 |KAMA - Kaufman's Adaptive Moving Average|`KAMA_Series`|✔️KAMA|✔️GetKama|✔️kama|✔️kama|
 |KDJ - KDJ Indicator (trend reversal)||||kdj|