Volumen Slope Mean Reversion-Strategie
Die Volumen Slope Mean Reversion-Strategie konzentriert sich auf extreme Volumen-Werte, um Rückkehrbewegungen auszunutzen. Starke Abweichungen vom typischen Niveau halten selten lange an.
Trades werden ausgelöst, wenn der Indikator weit von seinem Mittelwert abweicht und dann beginnt, sich umzukehren. Sowohl Long- als auch Short-Setups enthalten einen Schutz-Stop.
Geeignet für Swing-Trader, die Oszillationen erwarten; die Strategie schließt die Position, sobald das Volumen zum Gleichgewicht zurückkehrt. Startparameter VolumeMaPeriod = 20.
Details
- Einstiegskriterien: Der Indikator kreuzt zurück in Richtung Mittelwert.
- Long/Short: Beide Richtungen.
- Ausstiegskriterien: Der Indikator kehrt zum Durchschnitt zurück.
- Stops: Ja.
- Standardwerte:
VolumeMaPeriod= 20LookbackPeriod= 20DeviationMultiplier= 2.0mStopLossPercent= 2.0mCandleType= TimeSpan.FromMinutes(5)
- Filter:
- Kategorie: Mean Reversion
- Richtung: Beide
- Indikatoren: Volumen
- Stops: Ja
- Komplexität: Mittel
- Zeitrahmen: Kurzfristig
- Saisonalität: Nein
- Neuronale Netze: Nein
- Divergenz: Nein
- Risikolevel: Mittel
using System;
using System.Collections.Generic;
using Ecng.Common;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
/// <summary>
/// Volume slope mean reversion.
/// The slope of the smoothed volume is compared with its average: buys when the slope is far below the average
/// and starts turning up, sells when it is far above and starts turning down.
/// Exits when the slope returns to its average.
/// </summary>
public class VolumeSlopeMeanReversionStrategy : Strategy
{
private readonly StrategyParam<int> _volumeMaPeriod;
private readonly StrategyParam<int> _lookbackPeriod;
private readonly StrategyParam<decimal> _deviationMultiplier;
private readonly StrategyParam<decimal> _stopLossPercent;
private readonly StrategyParam<DataType> _candleType;
private SimpleMovingAverage _volumeMa;
private SimpleMovingAverage _slopeAverage;
private StandardDeviation _slopeStdDev;
private decimal? _prevVolume;
private decimal? _prevSlope;
/// <summary>
/// Period of the volume moving average.
/// </summary>
public int VolumeMaPeriod
{
get => _volumeMaPeriod.Value;
set => _volumeMaPeriod.Value = value;
}
/// <summary>
/// Lookback period for slope statistics.
/// </summary>
public int LookbackPeriod
{
get => _lookbackPeriod.Value;
set => _lookbackPeriod.Value = value;
}
/// <summary>
/// Standard deviation multiplier for extreme slope.
/// </summary>
public decimal DeviationMultiplier
{
get => _deviationMultiplier.Value;
set => _deviationMultiplier.Value = value;
}
/// <summary>
/// Stop-loss percentage.
/// </summary>
public decimal StopLossPercent
{
get => _stopLossPercent.Value;
set => _stopLossPercent.Value = value;
}
/// <summary>
/// Candle type.
/// </summary>
public DataType CandleType
{
get => _candleType.Value;
set => _candleType.Value = value;
}
/// <summary>
/// Initialize <see cref="VolumeSlopeMeanReversionStrategy"/>.
/// </summary>
public VolumeSlopeMeanReversionStrategy()
{
_volumeMaPeriod = Param(nameof(VolumeMaPeriod), 20)
.SetGreaterThanZero()
.SetDisplay("Volume MA Period", "Period of the volume moving average", "Indicators");
_lookbackPeriod = Param(nameof(LookbackPeriod), 20)
.SetGreaterThanZero()
.SetDisplay("Lookback Period", "Period for slope statistics", "Strategy");
_deviationMultiplier = Param(nameof(DeviationMultiplier), 2.0m)
.SetGreaterThanZero()
.SetDisplay("Deviation Multiplier", "Standard deviation multiplier for extreme slope", "Strategy");
_stopLossPercent = Param(nameof(StopLossPercent), 2.0m)
.SetNotNegative()
.SetDisplay("Stop Loss %", "Stop-loss percentage", "Risk Management");
_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(5).TimeFrame())
.SetDisplay("Candle Type", "Type of candles to use", "General");
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_volumeMa = null;
_slopeAverage = null;
_slopeStdDev = null;
_prevVolume = null;
_prevSlope = null;
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_volumeMa = new SimpleMovingAverage { Length = VolumeMaPeriod };
_slopeAverage = new SimpleMovingAverage { Length = LookbackPeriod };
_slopeStdDev = new StandardDeviation { Length = LookbackPeriod };
var subscription = SubscribeCandles(CandleType);
subscription
.Bind(ProcessCandle)
.Start();
StartProtection(
takeProfit: null,
stopLoss: StopLossPercent > 0 ? new Unit(StopLossPercent, UnitTypes.Percent) : null
);
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawOwnTrades(area);
}
}
private void ProcessCandle(ICandleMessage candle)
{
if (candle.State != CandleStates.Finished)
return;
var volume = _volumeMa.Process(candle.TotalVolume, candle.ServerTime, true).ToDecimal();
if (!_volumeMa.IsFormed)
return;
if (_prevVolume is not decimal prevVolume)
{
_prevVolume = volume;
return;
}
_prevVolume = volume;
var slope = volume - prevVolume;
var avgSlope = _slopeAverage.Process(slope, candle.ServerTime, true).ToDecimal();
var stdSlope = _slopeStdDev.Process(slope, candle.ServerTime, true).ToDecimal();
var prevSlope = _prevSlope;
_prevSlope = slope;
if (!_slopeAverage.IsFormed || !_slopeStdDev.IsFormed || prevSlope is not decimal prev)
return;
if (!IsFormedAndOnlineAndAllowTrading())
return;
// Extreme reading that has started to turn back toward the average.
if (slope < avgSlope - DeviationMultiplier * stdSlope && slope > prev && Position <= 0)
{
BuyMarket(Volume + Math.Abs(Position));
}
else if (slope > avgSlope + DeviationMultiplier * stdSlope && slope < prev && Position >= 0)
{
SellMarket(Volume + Math.Abs(Position));
}
else if (Position > 0 && slope >= avgSlope)
{
SellMarket(Position);
}
else if (Position < 0 && slope <= avgSlope)
{
BuyMarket(-Position);
}
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")
from System import TimeSpan
from StockSharp.Messages import DataType, CandleStates, Unit, UnitTypes
from StockSharp.Algo.Indicators import SimpleMovingAverage, StandardDeviation
from StockSharp.Algo.Strategies import Strategy
from indicator_extensions import *
class volume_slope_mean_reversion_strategy(Strategy):
"""
Volume slope mean reversion.
The slope of the smoothed volume is compared with its average: buys when the slope is far below the average
and starts turning up, sells when it is far above and starts turning down.
Exits when the slope returns to its average.
"""
def __init__(self):
super(volume_slope_mean_reversion_strategy, self).__init__()
self._volume_ma_period = self.Param("VolumeMaPeriod", 20) \
.SetGreaterThanZero() \
.SetDisplay("Volume MA Period", "Period of the volume moving average", "Indicators")
self._lookback_period = self.Param("LookbackPeriod", 20) \
.SetGreaterThanZero() \
.SetDisplay("Lookback Period", "Period for slope statistics", "Strategy")
self._deviation_multiplier = self.Param("DeviationMultiplier", 2.0) \
.SetGreaterThanZero() \
.SetDisplay("Deviation Multiplier", "Standard deviation multiplier for extreme slope", "Strategy")
self._stop_loss_percent = self.Param("StopLossPercent", 2.0) \
.SetNotNegative() \
.SetDisplay("Stop Loss %", "Stop-loss percentage", "Risk Management")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(5))) \
.SetDisplay("Candle Type", "Type of candles to use", "General")
self._volume_ma = None
self._slope_average = None
self._slope_std_dev = None
self._prev_volume = None
self._prev_slope = None
@property
def CandleType(self):
return self._candle_type.Value
def GetWorkingSecurities(self):
return [(self.Security, self.CandleType)]
def OnReseted(self):
super(volume_slope_mean_reversion_strategy, self).OnReseted()
self._volume_ma = None
self._slope_average = None
self._slope_std_dev = None
self._prev_volume = None
self._prev_slope = None
def OnStarted2(self, time):
super(volume_slope_mean_reversion_strategy, self).OnStarted2(time)
self._volume_ma = SimpleMovingAverage()
self._volume_ma.Length = self._volume_ma_period.Value
self._slope_average = SimpleMovingAverage()
self._slope_average.Length = self._lookback_period.Value
self._slope_std_dev = StandardDeviation()
self._slope_std_dev.Length = self._lookback_period.Value
subscription = self.SubscribeCandles(self.CandleType)
subscription.Bind(self._process_candle).Start()
stop = float(self._stop_loss_percent.Value)
self.StartProtection(None, Unit(stop, UnitTypes.Percent) if stop > 0 else None)
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawOwnTrades(area)
def _process_candle(self, candle):
if candle.State != CandleStates.Finished:
return
volume = float(process_float(self._volume_ma, candle.TotalVolume, candle.ServerTime, True))
if not self._volume_ma.IsFormed:
return
if self._prev_volume is None:
self._prev_volume = volume
return
slope = volume - self._prev_volume
self._prev_volume = volume
avg_slope = float(process_float(self._slope_average, slope, candle.ServerTime, True))
std_slope = float(process_float(self._slope_std_dev, slope, candle.ServerTime, True))
prev = self._prev_slope
self._prev_slope = slope
if not self._slope_average.IsFormed or not self._slope_std_dev.IsFormed or prev is None:
return
if not self.IsFormedAndOnlineAndAllowTrading():
return
k = float(self._deviation_multiplier.Value)
# Extreme reading that has started to turn back toward the average.
if slope < avg_slope - k * std_slope and slope > prev and self.Position <= 0:
self.BuyMarket(self.Volume + abs(self.Position))
elif slope > avg_slope + k * std_slope and slope < prev and self.Position >= 0:
self.SellMarket(self.Volume + abs(self.Position))
elif self.Position > 0 and slope >= avg_slope:
self.SellMarket(self.Position)
elif self.Position < 0 and slope <= avg_slope:
self.BuyMarket(-self.Position)
def CreateClone(self):
return volume_slope_mean_reversion_strategy()