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KAMA, SMMA, ZLEMA

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This commit is contained in:
Miha Kralj
2022-04-24 17:34:58 -07:00
parent 6b9aa85aa1
commit 0fb8c7c381
13 changed files with 286 additions and 71 deletions
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Docs/coverage.md
+2 -2
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@@ -52,7 +52,7 @@
| HMA - Hull Moving Average |✔️||✔️|✔️|
| HWMA - Holt-Winter Moving Average ||||✔️|
| JMA - Jurik Moving Average |✔️|||✔️|
| KAMA - Kaufman's Adaptive Moving Average ||✔️|✔️|✔️|
| KAMA - Kaufman's Adaptive Moving Average |✔️|✔️|✔️|✔️|
| LSMA - Least Squares Moving Average |||✔️||
| MACD - Moving Average Convergence/Divergence ||✔️|✔️|✔️|
| MAMA - MESA Adaptive Moving Average ||✔️|✔️||
@@ -63,7 +63,7 @@
| RMA - WildeR's Moving Average |✔️|||✔️|
| SINWMA - Sine Weighted Moving Average ||||✔️|
| SMA - Simple Moving Average |✔️|✔️|✔️|✔️|
| SMMA - Smoothed Moving Average |||✔️||
| SMMA - Smoothed Moving Average |✔️||✔️||
| STOCH - Stochastic Oscillator ||✔️|✔️|✔️|
| SSF - Ehler's Super Smoother Filter ||||✔️|
| SUP - Supertrend |||✔️|✔️|
Quantower/Indicators/ZLEMA_chart.cs → Quantower/Indicators/SMMA_chart.cs
+12 -12
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@@ -2,7 +2,7 @@ using System.Drawing;
using TradingPlatform.BusinessLayer;
namespace QuanTAlib;
public class ZLEMA_chart : Indicator
public class SMMA_chart : Indicator
{
#region Parameters
@@ -16,27 +16,28 @@ public class ZLEMA_chart : Indicator
#endregion Parameters
private TBars bars;
private TBars bars;
///////
private ZLEMA_Series indicator;
private SMMA_Series indicator;
///////
public ZLEMA_chart()
public SMMA_chart()
{
this.SeparateWindow = false;
this.Name = "ZLEMA - Zero-lag Exponential Moving Average";
this.Description = "Zero-Lag Exponential Moving Average description";
this.AddLineSeries("ZLEMA", Color.RoyalBlue, 3, LineStyle.Solid);
this.Name = "SMMA - Smoothed Moving Average";
this.Description = "Smoothed Moving Average description";
this.AddLineSeries("SMMA", Color.RoyalBlue, 3, LineStyle.Solid);
}
protected override void OnInit()
{
this.bars = new();
this.ShortName = "ZLEMA (" + TBars.SelectStr(this.DataSource) + ", " + this.Period + ")";
this.indicator = new(source: bars.Select(this.DataSource), period: this.Period, useNaN: false);
this.ShortName = "SMMA (" + TBars.SelectStr(this.DataSource) + ", " + this.Period + ")";
this.bars = new();
this.indicator = new(source: bars.Select(this.DataSource), period: this.Period, useNaN: false);
}
protected override void OnUpdate(UpdateArgs args)
protected override void OnUpdate(UpdateArgs args)
{
bool update = !(args.Reason == UpdateReason.NewBar ||
args.Reason == UpdateReason.HistoricalBar);
@@ -44,7 +45,6 @@ public class ZLEMA_chart : Indicator
this.GetPrice(PriceType.High), this.GetPrice(PriceType.Low),
this.GetPrice(PriceType.Close),
this.GetPrice(PriceType.Volume), update);
double result = this.indicator[this.indicator.Count - 1].v;
this.SetValue(result);
}
Quantower/Indicators/ZLMA_chart.cs
+94
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@@ -0,0 +1,94 @@
using System.Collections;
using System.Drawing;
using System.Drawing.Text;
using TradingPlatform.BusinessLayer;
namespace QuanTAlib;
public class ZLMA_chart : Indicator
{
#region Parameters
[InputParameter("Smoothing period", 0, 1, 999, 1, 1)]
private int Period = 10;
[InputParameter("Data source", 1, variants: new object[]
{ "Open", 0, "High", 1, "Low", 2, "Close", 3, "HL2", 4, "OC2", 5,
"OHL3", 6, "HLC3", 7, "OHLC4", 8, "Weighted (HLCC4)", 9 })]
private int DataSource = 3;
[InputParameter("MA algorithm", 2, variants: new object[]
{ "SMA", 0,
"WMA", 1,
"EMA", 2,
"DEMA", 3,
"TEMA", 4,
"HMA", 5,
"KAMA", 6,
"JMA", 7,
"SMMA", 8
})]
private int matype = 2;
#endregion Parameters
private TBars bars;
///////
private ZL_Series zerolag;
private TSeries indicator;
///////
public ZLMA_chart()
{
this.SeparateWindow = false;
this.Name = "ZLMA - Zero-lag Moving Average";
this.Description = "Zero-Lag Moving Average description";
this.AddLineSeries("ZLMA", Color.RoyalBlue, 3, LineStyle.Solid);
}
protected override void OnInit()
{
this.bars = new();
string maname = matype switch
{
0 => "SMA",
1 => "WMA",
2 => "EMA",
3 => "DEMA",
4 => "TEMA",
5 => "HMA",
6 => "KAMA",
7 => "JMA",
8 => "SMMA",
_ => "???"
};
this.ShortName = "ZLMA (" + maname + ", " + TBars.SelectStr(this.DataSource) + ", " + this.Period + ")";
this.zerolag = new(source: bars.Select(this.DataSource), period: this.Period, useNaN: false);
this.indicator = matype switch
{
0 => new SMA_Series(source: zerolag, period: this.Period, useNaN: false),
1 => new WMA_Series(source: zerolag, period: this.Period, useNaN: false),
2 => new EMA_Series(source: zerolag, period: this.Period, useNaN: false),
3 => new DEMA_Series(source: zerolag, period: this.Period, useNaN: false),
4 => new TEMA_Series(source: zerolag, period: this.Period, useNaN: false),
5 => new HMA_Series(source: zerolag, period: this.Period, useNaN: false),
6 => new KAMA_Series(source: zerolag, period: this.Period, useNaN: false),
7 => new JMA_Series(source: zerolag, period: this.Period, useNaN: false),
8 => new SMMA_Series(source: zerolag, period: this.Period, useNaN: false),
_ => new EMA_Series(source: zerolag, period: this.Period, useNaN: false)
};
}
protected override void OnUpdate(UpdateArgs args)
{
bool update = !(args.Reason == UpdateReason.NewBar ||
args.Reason == UpdateReason.HistoricalBar);
this.bars.Add(this.Time(), this.GetPrice(PriceType.Open),
this.GetPrice(PriceType.High), this.GetPrice(PriceType.Low),
this.GetPrice(PriceType.Close),
this.GetPrice(PriceType.Volume), update);
double result = this.indicator[this.indicator.Count - 1].v;
this.SetValue(result);
}
}
Source/Basics/ZL_Series.cs
+3 -3
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@@ -3,12 +3,12 @@ using System;
/* <summary>
ZL: Zero Lag
Data is de-lagged by removing the data from “lag” days ago, thus removing
Data is de-lagged by removing the data from “lag” days ago, thus removing
(or attempting to) the cumulative effect of the moving average.
Calculation:
Lag = (Period-1)/2
ZL = Data + (Data - Data(Lag days ago) )
ZL = Data + (Data - Data(Lag days ago) )
Sources:
https://mudrex.com/blog/zero-lag-ema-trading-strategy/
@@ -24,7 +24,7 @@ public class ZL_Series : Single_TSeries_Indicator
public override void Add((DateTime t, double v) TValue, bool update)
{
int _lag = (int)((_p-1) * 0.5);
_lag = (_data.Count-_lag < 0) ? 0 : _data.Count-_lag;
_lag = (this.Count-_lag < 0) ? 0 : this.Count-_lag;
double _zl = TValue.v + (TValue.v - _data[_lag].v);
Source/Indicators/HMA_Series.cs
+1 -1
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@@ -59,7 +59,7 @@ public class HMA_Series : TSeries
this._buf1.Add(data.v);
this._buf2.Add(data.v);
}
if (this._buf1.Count > (int)(Math.Ceiling((double)this._p / 2)))
if (this._buf1.Count > (int)((double)this._p / 2))
{
this._buf1.RemoveAt(0);
}
Source/Indicators/KAMA_Series.cs
+22 -24
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@@ -35,30 +35,28 @@ public class KAMA_Series : Single_TSeries_Indicator
_scSlow = 2.0 / (slow+1);
if (base._data.Count > 0) { base.Add(base._data); }
}
public override void Add((System.DateTime t, double v) TValue, bool update)
{
if (update){
_buffer[_buffer.Count - 1] = TValue.v;
this._lastkama = this._lastlastkama;
} else {
_buffer.Add(TValue.v);
}
if (_buffer.Count > _p + 1) { _buffer.RemoveAt(0); }
double _kama = TValue.v;
if (this.Count < this._p) {
for (int i = 0; i < this._buffer.Count; i++) { _kama += this._buffer[i]; }
_kama /= this._buffer.Count;
} else {
double _change = Math.Abs(_buffer[_buffer.Count - 1] - _buffer[(_buffer.Count > _p + 1) ? 1 : 0]);
double _sumpv = 0;
for (int i = 1; i < _buffer.Count; i++)
{
_sumpv += Math.Abs(_buffer[(_buffer.Count > 0) ? i : 0] - _buffer[i - 1]);
}
double _er = (_sumpv == 0) ? 0 : _change / _sumpv;
double _sc = (_er * (_scFast - _scSlow)) + _scSlow;
_kama = (_lastkama + (_sc * _sc * (TValue.v - _lastkama)));
}
public override void Add((System.DateTime t, double v) TValue, bool update)
{
if (update){
_buffer[_buffer.Count - 1] = TValue.v;
this._lastkama = this._lastlastkama;
} else {
_buffer.Add(TValue.v);
}
if (_buffer.Count > _p + 1) { _buffer.RemoveAt(0); }
double _kama = 0;
if (this.Count < this._p) {
for (int i = 0; i < this._buffer.Count; i++) { _kama += this._buffer[i]; }
_kama /= this._buffer.Count;
} else {
double _change = Math.Abs(_buffer[_buffer.Count - 1] - _buffer[(_buffer.Count > _p + 1) ? 1 : 0]);
double _sumpv = 0;
for (int i = 1; i < _buffer.Count; i++)
{ _sumpv += Math.Abs(_buffer[(_buffer.Count > 0) ? i : 0] - _buffer[i - 1]); }
double _er = (_sumpv == 0) ? 0 : _change / _sumpv;
double _sc = (_er * (_scFast - _scSlow)) + _scSlow;
_kama = (_lastkama + (_sc * _sc * (TValue.v - _lastkama)));
}
_lastlastkama = _lastkama;
_lastkama = _kama;
var result = (TValue.t, (this.Count < this._p - 1 && this._NaN) ? double.NaN : _kama);
Source/Indicators/SMMA_Series.cs
+58
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@@ -0,0 +1,58 @@
namespace QuanTAlib;
using System;
/* <summary>
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
</summary> */
public class SMMA_Series : Single_TSeries_Indicator
{
private readonly System.Collections.Generic.List<double> _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);
}
}
Source/Indicators/ZLEMA_Series.cs
+43 -28
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@@ -21,36 +21,51 @@ Remark:
public class ZLEMA_Series : Single_TSeries_Indicator
{
private readonly double _k, _k1m;
private double _lastema, _lastlastema;
private readonly System.Collections.Generic.List<double> _buffer = new();
private readonly double _k, _k1m;
private double _lastema, _lastlastema;
public ZLEMA_Series(TSeries source, int period, bool useNaN = false) : base(source, period, useNaN)
{
this._k = 2.0 / (double)(period + 1);
this._k1m = 1.0 - this._k;
this._lastema = this._lastlastema = double.NaN;
public ZLEMA_Series(TSeries source, int period, bool useNaN = false) : base(source, period, useNaN)
{
this._k = 2.0 / (this._p + 1);
this._k1m = 1.0 - this._k;
this._lastema = this._lastlastema = double.NaN;
if (base._data.Count > 0)
{ base.Add(base._data); }
}
public override void Add((System.DateTime t, double v) TValue, bool update)
{
int _lag = (int)((_p - 1) * 0.5);
_lag = (this.Count - _lag < 0) ? 0 : this.Count - _lag;
double _zl = TValue.v + (TValue.v - _data[_lag].v);
double _ema = 0;
if (update)
{ this._lastema = this._lastlastema; }
if (this.Count < this._p)
{
if (update)
{ this._buffer[this._buffer.Count - 1] = _zl; }
else
{
this._buffer.Add(_zl);
}
if (this._buffer.Count > this._p)
{ this._buffer.RemoveAt(0); }
if (base._data.Count > 0) { base.Add(base._data); }
}
for (int i = 0; i < this._buffer.Count; i++)
{ _ema += this._buffer[i]; }
_ema /= this._buffer.Count;
}
else
{
_ema = TValue.v * this._k + this._lastema * this._k1m;
}
public override void Add((System.DateTime t, double v) TValue, bool update)
{
if (update)
{
this._lastema = this._lastlastema;
}
int _lag = (int)(0.5 * (_p - 1));
int _l = Math.Max(this._data.Count - _lag, 0);
double _lagdata = 1 * TValue.v - this._data[_l].v;
this._lastlastema = this._lastema;
this._lastema = _ema;
double _ema = System.Double.IsNaN(this._lastema) ? _lagdata : _lagdata * this._k + this._lastema * this._k1m;
this._lastlastema = this._lastema;
this._lastema = _ema;
(System.DateTime t, double v) result =
(TValue.t, (this.Count < this._p - 1 && this._NaN) ? double.NaN : _ema);
base.Add(result, update);
}
}
var ret = (TValue.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _ema);
base.Add(ret, update);
}
}
Source/QuanTAlib.csproj
+1 -1
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@@ -1,6 +1,6 @@
<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<Version>0.1.11</Version>
<Version>0.1.12</Version>
<releaseNotes></releaseNotes>
<Title>QuanTAlib</Title>
<Product>Library of Technical Indicators for .NET</Product>
Tests/MovingAvg/SMMA_Test.cs
+33
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@@ -0,0 +1,33 @@
using Xunit;
using System;
using QuanTAlib;
namespace MovingAvg;
public class SMMA_Test
{
[Fact]
public void Add_Test()
{
TSeries a = new() { 0, 1, 2, 3, 4, 5 };
SMMA_Series c = new(a, 3);
Assert.Equal(6, c.Count);
a.Add(5);
Assert.Equal(a.Count, c.Count);
a.Add(0, update: true);
Assert.Equal(a.Count, c.Count);
}
[Fact]
public void Edge_Test()
{
TSeries a = new() { double.NaN, double.Epsilon, double.PositiveInfinity, double.MaxValue };
SMMA_Series c = new(a, 3);
Assert.Equal(a.Count, c.Count);
a.Add(double.NaN);
Assert.Equal(a.Count, c.Count);
a.Add(double.PositiveInfinity);
Assert.Equal(a.Count, c.Count);
}
}
Tests/Tests.csproj
+8
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@@ -26,6 +26,14 @@
<NoWarn>1701;1702;MSB3270</NoWarn>
</PropertyGroup>
<ItemGroup>
<None Remove="Validations\Pandas_TA.cstemp" />
</ItemGroup>
<ItemGroup>
<Compile Include="Validations\Pandas_TA.cstemp" />
</ItemGroup>
<ItemGroup>
<PackageReference Include="JetBrains.dotCover.CommandLineTools" Version="2022.1.0-eap10">
<PrivateAssets>all</PrivateAssets>
Tests/Validations/Pandas_TA.cs → Tests/Validations/Pandas_TA.cstemp
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Tests/Validations/Skender_Stock.cs
+9
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@@ -117,4 +117,13 @@ public class Skender_Stock
Assert.Equal(Math.Round((double)SK.Last().Kama!, 8), Math.Round(QL.Last().v, 8));
}
[Fact]
public void SMMA()
{
SMMA_Series QL = new(this.bars.Close, this.period, useNaN: false);
var SK = this.quotes.GetSmma(this.period);
Assert.Equal(Math.Round((double)SK.Last().Smma!, 8), Math.Round(QL.Last().v, 8));
}
}