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MAMA

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This commit is contained in:
Miha Kralj
2022-11-17 21:59:17 -08:00
parent 73e3420379
commit cfa10c79e8
7 changed files with 161 additions and 10 deletions
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Quantower/Quantower.csproj
+4
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@@ -13,6 +13,7 @@
<PlatformTarget>AnyCPU</PlatformTarget>
<Nullable>disable</Nullable>
<SignAssembly>False</SignAssembly>
<CodeAnalysisRuleSet>..\.sonarlint\mihakralj_quantalibcsharp.ruleset</CodeAnalysisRuleSet>
</PropertyGroup>
<PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Debug|AnyCPU'">
<Optimize>True</Optimize>
@@ -36,6 +37,9 @@
<Target Name="CopyCustomContent" AfterTargets="AfterBuild">
<Copy SourceFiles=".\bin\$(Configuration)\net48\Quantower_QTAlib.dll" DestinationFolder="\Quantower\Settings\Scripts\Indicators\QuanTAlib" />
</Target>
<ItemGroup>
<AdditionalFiles Include="..\.sonarlint\mihakralj_quantalib\CSharp\SonarLint.xml" Link="SonarLint.xml" />
</ItemGroup>
<ItemGroup>
<Reference Include="TradingPlatform.BusinessLayer">
<HintPath>C:\Quantower\TradingPlatform\v1.124.6\bin\TradingPlatform.BusinessLayer.dll</HintPath>
Source/QuanTAlib.csproj
+3 -2
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@@ -2,7 +2,7 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<Title>QuanTAlib</Title>
<Version>0.1.20</Version>
<Version>0.1.21</Version>
<Product>Library of Technical Indicators for .NET</Product>
<Description>Quantitative Technical Analysis library for both real-time (streaming) and historical data analysis</Description>
<RepositoryType>git</RepositoryType>
@@ -51,7 +51,7 @@
<PackageIcon>QuanTAlib2.png</PackageIcon>
<PackageIconUrl>https://raw.githubusercontent.com/mihakralj/QuanTAlib/main/.github/QuanTAlib2.png</PackageIconUrl>
<EnforceCodeStyleInBuild>True</EnforceCodeStyleInBuild>
<CodeAnalysisRuleSet>QuanTAlib.ruleset</CodeAnalysisRuleSet>
<CodeAnalysisRuleSet>..\.sonarlint\mihakralj_quantalibcsharp.ruleset</CodeAnalysisRuleSet>
</PropertyGroup>
<ItemGroup>
<AdditionalFiles Include="..\.sonarlint\mihakralj_quantalib\CSharp\SonarLint.xml" Link="SonarLint.xml" />
@@ -66,5 +66,6 @@
<Visible>False</Visible>
<PackagePath></PackagePath>
</None>
<PackageReference Include="System.Text.Json" Version="7.0.0" />
</ItemGroup>
</Project>
Source/QuanTAlib.ruleset
-5
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@@ -1,5 +0,0 @@
<?xml version="1.0" encoding="utf-8"?>
<RuleSet Name="SonarQube - QuanTAlib QuanTAlib" ToolsVersion="17.0">
<Include Path="..\.sonarlint\mihakralj_quantalibcsharp.ruleset" Action="Default" />
<Include Path="..\.sonarlint\mihakralj_quantalibcsharp.ruleset" Action="Default" />
</RuleSet>
Source/Trends/MAMA_Series.cs
+131
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@@ -0,0 +1,131 @@
namespace QuanTAlib;
using System;
/* <summary>
MAMA: MESA Adaptive Moving Average
Created by John Ehlers, the MAMA indicator is a 5-period adaptive moving average of
high/low price that uses classic electrical radio-frequency signal processing algorithms
to reduce noise.
KAMAi = KAMAi - 1 + SC * ( price - KAMAi-1 )
Sources:
https://mesasoftware.com/papers/MAMA.pdf
https://www.tradingview.com/script/foQxLbU3-Ehlers-MESA-Adaptive-Moving-Average-LazyBear/
</summary> */
public class MAMA_Series : Single_TSeries_Indicator
{
public MAMA_Series(TSeries source, double fastlimit = 0.5, double slowlimit = 0.05, bool useNaN = false) : base(source, period: 5, useNaN)
{
fastl = fastlimit;
slowl = slowlimit;
i = 0;
if (base._data.Count > 0) { base.Add(base._data); }
}
private int i;
private double sumPr, jI, jQ, fastl, slowl;
private (double i, double i1, double i2, double i3, double i4, double i5, double i6, double io) pr, i1, q1, sm, dt;
private (double i, double i1, double io) i2, q2, re, im, pd, ph, mama, fama;
public override void Add((System.DateTime t, double v) TValue, bool update)
{
if (update) {
i--;
pr.i = pr.i1; pr.i1 = pr.i2; pr.i2 = pr.i3; pr.i3 = pr.i4; pr.i4 = pr.i5; pr.i5 = pr.i6; pr.i6 = pr.io;
i1.i = i1.i1; i1.i1 = i1.i2; i1.i2 = i1.i3; i1.i3 = i1.i4; i1.i4 = i1.i5; i1.i5 = i1.i6; i1.i6 = i1.io;
q1.i = q1.i1; q1.i1 = q1.i2; q1.i2 = q1.i3; q1.i3 = q1.i4; q1.i4 = q1.i5; q1.i5 = q1.i6; q1.i6 = q1.io;
dt.i = dt.i1; dt.i1 = dt.i2; dt.i2 = dt.i3; dt.i3 = dt.i4; dt.i4 = dt.i5; dt.i5 = dt.i6; dt.i6 = dt.io;
sm.i = sm.i1; sm.i1 = sm.i2; sm.i2 = sm.i3; sm.i3 = sm.i4; dt.i4 = sm.i5; sm.i5 = sm.i6; sm.i6 = sm.io;
i2.i = i2.i1; i2.i1 = i2.io;
q2.i = q2.i1; q2.i1 = q2.io;
re.i = re.i1; re.i1 = re.io;
im.i = im.i1; im.i1 = im.io;
pd.i = pd.i1; pd.i1 = pd.io;
ph.i = ph.i1; ph.i1 = ph.io;
mama.i = mama.i1; mama.i1 = mama.io;
fama.i = fama.i1; fama.i1 = fama.io;
}
pr.i = TValue.v;
if (i > 5) {
double adj = (0.075 * pd.i1) + 0.54;
// smooth and detrender
sm.i = ((4 * pr.i) + (3 * pr.i1) + (2 * pr.i2) + pr.i3) / 10;
dt.i = ((0.0962 * sm.i) + (0.5769 * sm.i2) - (0.5769 * sm.i4) - (0.0962 * sm.i6)) * adj;
// in-phase and quadrature
q1.i = ((0.0962 * dt.i) + (0.5769 * dt.i2) - (0.5769 * dt.i4) - (0.0962 * dt.i6)) * adj;
i1.i = dt.i3;
// advance the phases by 90 degrees
jI = ((0.0962 * i1.i) + (0.5769 * i1.i2) - (0.5769 * i1.i4) - (0.0962 * i1.i6)) * adj;
jQ = ((0.0962 * q1.i) + (0.5769 * q1.i2) - (0.5769 * q1.i4) - (0.0962 * q1.i6)) * adj;
// phasor addition for 3-bar averaging
i2.i = i1.i - jQ;
q2.i = q1.i + jI;
i2.i = (0.2 * i2.i) + (0.8 * i2.i1); // smoothing it
q2.i = (0.2 * q2.i) + (0.8 * q2.i1);
// homodyne discriminator
re.i = (i2.i * i2.i1) + (q2.i * q2.i1);
im.i = (i2.i * q2.i1) - (q2.i * i2.i1);
re.i = (0.2 * re.i) + (0.8 * re.i1); // smoothing it
im.i = (0.2 * im.i) + (0.8 * im.i1);
// calculate period
pd.i = (im.i != 0 && re.i != 0) ? (6.283185307179586 / Math.Atan(im.i / re.i)) : 0d;
// adjust period to thresholds
pd.i = (pd.i > 1.5 * pd.i1) ? 1.5 * pd.i1 : pd.i;
pd.i = (pd.i < 0.67 * pd.i1) ? 0.67 * pd.i1 : pd.i;
pd.i = (pd.i < 6d) ? 6d : pd.i;
pd.i = (pd.i > 50d) ? 50d : pd.i;
// smooth the period
pd.i = (0.2 * pd.i) + (0.8 * pd.i1);
// determine phase position
ph.i = (i1.i != 0) ? Math.Atan(q1.i / i1.i) * 57.29577951308232 : 0;
// change in phase
double delta = Math.Max(ph.i1 - ph.i, 1d);
// adaptive alpha value
double alpha = Math.Max(fastl / delta, slowl);
// final indicators
mama.i = ((alpha * pr.i) + ((1d - alpha) * mama.i1));
fama.i = ((0.5d * alpha * mama.i) + ((1d - (0.5d * alpha)) * fama.i1));
}
else {
sumPr += pr.i;
pd.i = sm.i = dt.i = i1.i = q1.i = i2.i = q2.i = re.i = im.i = ph.i = 0;
mama.i = fama.i = sumPr / (i+1);
}
i++;
pr.io = pr.i6; pr.i6 = pr.i5; pr.i5 = pr.i4; pr.i4 = pr.i3; pr.i3 = pr.i2; pr.i2 = pr.i1; pr.i1 = pr.i;
i1.io = i1.i6; i1.i6 = i1.i5; i1.i5 = i1.i4; i1.i4 = i1.i3; i1.i3 = i1.i2; i1.i2 = i1.i1; i1.i1 = i1.i;
q1.io = q1.i6; q1.i6 = q1.i5; q1.i5 = q1.i4; q1.i4 = q1.i3; q1.i3 = q1.i2; q1.i2 = q1.i1; q1.i1 = q1.i;
dt.io = dt.i6; dt.i6 = dt.i5; dt.i5 = dt.i4; dt.i4 = dt.i3; dt.i3 = dt.i2; dt.i2 = dt.i1; dt.i1 = dt.i;
sm.io = sm.i6; sm.i6 = sm.i5; sm.i5 = sm.i4; sm.i4 = sm.i3; sm.i3 = sm.i2; sm.i2 = sm.i1; sm.i1 = sm.i;
i2.io = i2.i1; i2.i1 = i2.i;
q2.io = q2.i1; q2.i1 = q2.i;
re.io = re.i1; re.i1 = re.i;
im.io = im.i1; im.i1 = im.i;
pd.io = pd.i1; pd.i1 = pd.i;
ph.io = ph.i1; ph.i1 = ph.i;
mama.io = mama.i1; mama.i1 = mama.i;
fama.io = fama.i1; fama.i1 = fama.i;
base.Add((TValue.t, mama.i), update, _NaN);
}
}
Tests/Validations/Pandas_TA.cs
+1 -1
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@@ -157,7 +157,7 @@ public class PandasTA : IDisposable
[Fact]
void TRIMA()
{
//TODO: return length to variable length (period) when Pandas-TA fixes trima
// TODO: return length to variable length (period) when Pandas-TA fixes trima
TRIMA_Series QL = new(bars.Close, 11);
var pta = df.ta.trima(close: df.close, length: 11);
Assert.Equal(Math.Round((double)pta.tail(1), 4), Math.Round(QL.Last().v, 4));
Tests/Validations/Skender_Stock.cs
+10 -1
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@@ -71,7 +71,16 @@ public class Skender_Stock
Assert.Equal(Math.Round((double)SK.Last().Tema!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
[Fact]
public void MAMA() {
MAMA_Series QL = new(bars.HL2, fastlimit: 0.5, slowlimit: 0.05);
var SK = quotes.GetMama(fastLimit: 0.5, slowLimit: 0.05);
Assert.Equal(Math.Round((double)SK.Last().Mama!, 6), Math.Round(QL.Last().v, 6));
}
[Fact]
public void MAD()
{
MAD_Series QL = new(bars.Close, period, false);
Tests/Validations/TA_LIB.cs
+12 -1
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@@ -10,6 +10,7 @@ public class TA_LIB
private readonly Random rnd = new();
private readonly int period;
private readonly double[] TALIB;
private readonly double[] TALIB2;
private readonly double[] inopen;
private readonly double[] inhigh;
private readonly double[] inlow;
@@ -21,6 +22,7 @@ public class TA_LIB
bars = new(5000);
period = rnd.Next(28) + 3;
TALIB = new double[bars.Count];
TALIB2 = new double[bars.Count];
inopen = bars.Open.v.ToArray();
inhigh = bars.High.v.ToArray();
inlow = bars.Low.v.ToArray();
@@ -130,7 +132,16 @@ public class TA_LIB
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
[Fact]
public void MAMA() {
MAMA_Series QL = new(bars.Close, fastlimit: 0.5, slowlimit: 0.05);
Core.Mama(inReal: inclose, startIdx: 0, endIdx: bars.Count - 1, outMama: TALIB, outFama: TALIB2, outBegIdx: out int outBegIdx, outNbElement: out _, optInFastLimit: 0.5, optInSlowLimit: 0.05);
Assert.Equal(Math.Round(TALIB[TALIB.Length - outBegIdx - 1], 6, MidpointRounding.AwayFromZero), Math.Round(QL.Last().v, 6, MidpointRounding.AwayFromZero));
}
[Fact]
public void TRIMA()
{
TRIMA_Series QL = new(bars.Close, period, false);