Stochastic Oscillator Mean Reversion-Strategie
Diese Strategie misst den Stochastic Oscillator gegen seinen eigenen gleitenden Durchschnitt, um überdehnte Schwingungen zu lokalisieren. Wenn %K sich mehrere Standardabweichungen von seinem Mittelwert entfernt, wird erwartet, dass der Indikator zu typischen Werten zurückdriftet.
Tests zeigen eine durchschnittliche jährliche Rendite von etwa 64%. Er funktioniert am besten auf dem Devisenmarkt.
Ein Long-Trade wird platziert, wenn Stochastic %K unter das untere Band fällt, das durch den Durchschnitt minus Multiplier mal die Standardabweichung definiert wird. Ein Short-Trade erfolgt, wenn %K das obere Band überschreitet. Positionen werden geschlossen, sobald %K wieder durch seine Durchschnittslinie kreuzt.
Die Methode ist für kurzfristige Trader konzipiert, die gerne an überkauften und überverkauften Extremen handeln. Der Stop-Loss schützt vor anhaltendem Momentum, das nicht zur Mean Reversion neigt.
Details
- Einstiegskriterien:
- Long: %K < Avg - Multiplier * StdDev
- Short: %K > Avg + Multiplier * StdDev
- Long/Short: Beide Seiten.
- Ausstiegskriterien:
- Long: Ausstieg wenn %K > Avg
- Short: Ausstieg wenn %K < Avg
- Stops: Ja, prozentualer Stop-Loss.
- Standardwerte:
StochPeriod = 14
KPeriod = 3
AveragePeriod = 20
Multiplier = 2
StopLossPercent = 2
CandleType = TimeSpan.FromMinutes(5)
Avg und StdDev sind Mittelwert und Standardabweichung der letzten AveragePeriod Werte von %K einschließlich des aktuellen. Der Stop liegt bei festen StopLossPercent vom Einstiegspreis und wird auch zwischen den Kerzen überwacht; 0 schaltet ihn ab. %K ist die Stochastik über die erste Periode, geglättet über KPeriod Kerzen; %D spielt in den Regeln keine Rolle, daher entfällt DPeriod. Ein Einstiegssignal gegen eine offene Position dreht sie.
- Filter:
- Kategorie: Mean Reversion
- Richtung: Beide
- Indikatoren: Stochastic Oscillator
- Stops: Ja
- Komplexität: Mittel
- Zeitrahmen: Intraday
- Saisonalität: Nein
- Neuronale Netze: Nein
- Divergenz: Nein
- Risikolevel: Mittel
using System;
using System.Collections.Generic;
using System.Linq;
using Ecng.Common;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
/// <summary>
/// Stochastic Mean Reversion strategy.
/// The bands lie Multiplier standard deviations around the average of the last AveragePeriod %K values, the current one included.
/// %K below the lower band goes long and %K above the upper band goes short,
/// reversing an opposite position. A long closes once %K is back above its average and a short once it is back below it, and a percent stop limits the loss.
/// </summary>
public class StochasticMeanReversionStrategy : Strategy
{
private readonly StrategyParam<int> _stochPeriod;
private readonly StrategyParam<int> _kPeriod;
private readonly StrategyParam<int> _averagePeriod;
private readonly StrategyParam<decimal> _multiplier;
private readonly StrategyParam<decimal> _stopLossPercent;
private readonly StrategyParam<DataType> _candleType;
private readonly Queue<decimal> _values = [];
/// <summary>
/// Lookback period of the raw stochastic.
/// </summary>
public int StochPeriod
{
get => _stochPeriod.Value;
set => _stochPeriod.Value = value;
}
/// <summary>
/// Smoothing period of %K.
/// </summary>
public int KPeriod
{
get => _kPeriod.Value;
set => _kPeriod.Value = value;
}
/// <summary>
/// Values of %K the average and the standard deviation span.
/// </summary>
public int AveragePeriod
{
get => _averagePeriod.Value;
set => _averagePeriod.Value = value;
}
/// <summary>
/// Standard deviations between the average and a band.
/// </summary>
public decimal Multiplier
{
get => _multiplier.Value;
set => _multiplier.Value = value;
}
/// <summary>
/// Stop loss percentage from entry price.
/// </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>
/// Constructor.
/// </summary>
public StochasticMeanReversionStrategy()
{
_stochPeriod = Param(nameof(StochPeriod), 14)
.SetGreaterThanZero()
.SetDisplay("Stochastic Period", "Lookback period of the raw stochastic", "Indicators");
_kPeriod = Param(nameof(KPeriod), 3)
.SetGreaterThanZero()
.SetDisplay("%K Period", "Smoothing period of %K", "Indicators");
_averagePeriod = Param(nameof(AveragePeriod), 20)
.SetGreaterThanZero()
.SetDisplay("Average Period", "Values of %K the average and the standard deviation span", "Indicators");
_multiplier = Param(nameof(Multiplier), 2m)
.SetGreaterThanZero()
.SetDisplay("Multiplier", "Standard deviations between the average and a band", "Indicators");
_stopLossPercent = Param(nameof(StopLossPercent), 2m)
.SetNotNegative()
.SetDisplay("Stop Loss %", "Stop loss percentage from entry price", "Risk");
_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();
_values.Clear();
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_values.Clear();
var stochastic = new StochasticOscillator
{
K = { Length = StochPeriod },
D = { Length = KPeriod },
};
var subscription = SubscribeCandles(CandleType);
subscription
.BindEx(stochastic, ProcessCandle)
.Start();
StartProtection(new Unit(), new Unit(StopLossPercent, UnitTypes.Percent), useMarketOrders: true, isLocalStop: true);
// The stop has to see prices between candles, not only at their close.
foreach (var field in new[] { Level1Fields.BestBidPrice, Level1Fields.BestAskPrice })
{
var quotes = new Subscription(DataType.Level1, Security);
quotes.MarketData.BuildField = field;
SubscribeLevel1(quotes).Bind(ObserveProtectionQuote).Start();
}
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawOwnTrades(area);
var oscillators = CreateChartArea();
if (oscillators != null)
{
DrawIndicator(oscillators, stochastic);
}
}
}
private void ObserveProtectionQuote(Level1ChangeMessage quote)
{
// The high-level handler activates native protection before this callback, also between signal bars.
}
private void ProcessCandle(ICandleMessage candle, IIndicatorValue stochasticValue)
{
if (candle.State != CandleStates.Finished)
return;
// The smoothed %K is the moving average the core oscillator exposes as D.
if (!stochasticValue.IsFormed || stochasticValue is not IStochasticOscillatorValue { D: decimal value })
return;
_values.Enqueue(value);
if (_values.Count > AveragePeriod)
_values.Dequeue();
if (_values.Count < AveragePeriod)
return;
if (!IsFormedAndOnlineAndAllowTrading())
return;
var mean = _values.Average();
var deviation = (decimal)Math.Sqrt((double)_values.Average(v => (v - mean) * (v - mean)));
var upper = mean + Multiplier * deviation;
var lower = mean - Multiplier * deviation;
if (value < lower && Position <= 0)
BuyMarket(Volume + Math.Abs(Position));
else if (value > upper && Position >= 0)
SellMarket(Volume + Math.Abs(Position));
else if (Position > 0 && value > mean)
SellMarket(Position);
else if (Position < 0 && value < mean)
BuyMarket(-Position);
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")
clr.AddReference("StockSharp.BusinessEntities")
from System import TimeSpan, Decimal, Math
from StockSharp.Messages import DataType, CandleStates, Unit, UnitTypes, Level1Fields
from StockSharp.BusinessEntities import Subscription
from StockSharp.Algo.Indicators import StochasticOscillator
from StockSharp.Algo.Strategies import Strategy
class stochastic_mean_reversion_strategy(Strategy):
"""
Stochastic Mean Reversion strategy.
The bands lie Multiplier standard deviations around the average of the last AveragePeriod %K values, the current one included.
%K below the lower band goes long and %K above the upper band goes short,
reversing an opposite position. A long closes once %K is back above its average and a short once it is back below it, and a percent stop limits the loss.
"""
def __init__(self):
super(stochastic_mean_reversion_strategy, self).__init__()
self._stoch_period = self.Param("StochPeriod", 14).SetGreaterThanZero().SetDisplay("Stochastic Period", "Lookback period of the raw stochastic", "Indicators")
self._k_period = self.Param("KPeriod", 3).SetGreaterThanZero().SetDisplay("%K Period", "Smoothing period of %K", "Indicators")
self._average_period = self.Param("AveragePeriod", 20).SetGreaterThanZero().SetDisplay("Average Period", "Values of %K the average and the standard deviation span", "Indicators")
self._multiplier = self.Param("Multiplier", 2.0).SetGreaterThanZero().SetDisplay("Multiplier", "Standard deviations between the average and a band", "Indicators")
self._stop_loss_percent = self.Param("StopLossPercent", 2.0).SetNotNegative().SetDisplay("Stop Loss %", "Stop loss percentage from entry price", "Risk")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(5))).SetDisplay("Candle Type", "Type of candles to use", "General")
self._reset_state()
@property
def candle_type(self):
return self._candle_type.Value
def _reset_state(self):
self._values = []
def OnReseted(self):
super(stochastic_mean_reversion_strategy, self).OnReseted()
self._reset_state()
def OnStarted2(self, time):
super(stochastic_mean_reversion_strategy, self).OnStarted2(time)
self._reset_state()
stochastic = StochasticOscillator()
stochastic.K.Length = self._stoch_period.Value
stochastic.D.Length = self._k_period.Value
subscription = self.SubscribeCandles(self.candle_type)
subscription.BindEx(stochastic, self._process_candle).Start()
self.StartProtection(Unit(), Unit(Decimal(self._stop_loss_percent.Value), UnitTypes.Percent), useMarketOrders=True, isLocalStop=True)
# The stop has to see prices between candles, not only at their close.
for field in (Level1Fields.BestBidPrice, Level1Fields.BestAskPrice):
quotes = Subscription(DataType.Level1, self.Security)
quotes.MarketData.BuildField = field
self.SubscribeLevel1(quotes).Bind(self._observe_protection_quote).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawOwnTrades(area)
oscillators = self.CreateChartArea()
if oscillators is not None:
self.DrawIndicator(oscillators, stochastic)
def _observe_protection_quote(self, quote):
# The high-level handler activates native protection before the callback, including between bars.
pass
def _process_candle(self, candle, stochastic_value):
if candle.State != CandleStates.Finished:
return
# The smoothed %K is the moving average the core oscillator exposes as D.
if not stochastic_value.IsFormed or stochastic_value.D is None:
return
value = stochastic_value.D
period = self._average_period.Value
self._values.append(value)
if len(self._values) > period:
self._values.pop(0)
if len(self._values) < period:
return
if not self.IsFormedAndOnlineAndAllowTrading():
return
total = Decimal(0)
for item in self._values:
total += item
mean = total / Decimal(period)
squares = Decimal(0)
for item in self._values:
squares += (item - mean) * (item - mean)
deviation = Decimal(Math.Sqrt(Decimal.ToDouble(squares / Decimal(period))))
multiplier = Decimal(self._multiplier.Value)
upper = mean + multiplier * deviation
lower = mean - multiplier * deviation
if value < lower and self.Position <= 0:
self.BuyMarket(self.Volume + abs(self.Position))
elif value > upper and self.Position >= 0:
self.SellMarket(self.Volume + abs(self.Position))
elif self.Position > 0 and value > mean:
self.SellMarket(self.Position)
elif self.Position < 0 and value < mean:
self.BuyMarket(-self.Position)
def CreateClone(self):
return stochastic_mean_reversion_strategy()