Diese Strategie analysiert die kurzfristige Preis-Autokorrelation, um zu beurteilen, ob aktuelle Bewegungen wahrscheinlich umkehren werden. Negative Autokorrelation deutet darauf hin, dass aufeinanderfolgende Preisänderungen dazu neigen, die Richtung zu wechseln, was Mean-Reversion-Bedingungen schafft.
Tests zeigen eine durchschnittliche jährliche Rendite von etwa 124%. Er funktioniert am besten auf dem Devisenmarkt.
Wenn die berechnete Autokorrelation unter den Schwellenwert fällt und der Preis unter einem gleitenden Durchschnitt liegt, kauft das System in Erwartung eines Rebounds. Wenn die Autokorrelation negativ ist und der Preis über dem Durchschnitt liegt, wird eine Short-Position eröffnet. Ausstiege erfolgen, sobald der Preis den Durchschnitt kreuzt oder die Autokorrelation über den Schwellenwert steigt.
Der Ansatz ist für Trader geeignet, die nach statistischen Vorteilen suchen, anstatt nach Chartmustern. Ein prozentualer Stop-Loss wird angewendet, um gegen anhaltende Trends zu schützen, die die erwartete Umkehr verletzen.
Details
Einstiegskriterien:
Long: Autocorrelation < Threshold && Close < MA
Short: Autocorrelation < Threshold && Close > MA
Long/Short: Beide Seiten.
Ausstiegskriterien:
Long: Ausstieg wenn Close > MA oder autocorrelation > Threshold
Short: Ausstieg wenn Close < MA oder autocorrelation > Threshold
Stops: Ja, prozentualer Stop-Loss.
Standardwerte:
AutoCorrPeriod = 20
AutoCorrThreshold = -0.3
StopLossPercent = 2
Die Autokorrelation ist die Lag-1-Autokorrelation der Schlusskursänderungen über die letzten AutoCorrPeriod Schlusskurse, MA der einfache gleitende Durchschnitt über dieselben AutoCorrPeriod Kerzen. Der Stop liegt bei festen StopLossPercent vom Einstiegspreis und wird auch zwischen den Kerzen überwacht; 0 schaltet ihn ab. Ein Einstiegssignal gegen eine offene Position dreht sie.
CandleType = TimeSpan.FromMinutes(5)
Filter:
Kategorie: Mean Reversion
Richtung: Beide
Indikatoren: Autocorrelation, MA
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>
/// Autocorrelation Reversal strategy.
/// The autocorrelation is the lag-one autocorrelation of the close-to-close changes over the last AutoCorrPeriod closes. Below
/// AutoCorrThreshold a close under the AutoCorrPeriod simple moving average goes long and a close above it goes short, reversing an opposite
/// position. A long closes once the close is above the average or the autocorrelation rises above the threshold, a short mirrors it,
/// and a percent stop limits the loss.
/// </summary>
public class AutocorrelationReversionStrategy : Strategy
{
private readonly StrategyParam<int> _autoCorrPeriod;
private readonly StrategyParam<decimal> _autoCorrThreshold;
private readonly StrategyParam<decimal> _stopLossPercent;
private readonly StrategyParam<DataType> _candleType;
private readonly Queue<decimal> _closes = [];
/// <summary>
/// Closes the autocorrelation and the average span.
/// </summary>
public int AutoCorrPeriod
{
get => _autoCorrPeriod.Value;
set => _autoCorrPeriod.Value = value;
}
/// <summary>
/// Autocorrelation below which the market reverts.
/// </summary>
public decimal AutoCorrThreshold
{
get => _autoCorrThreshold.Value;
set => _autoCorrThreshold.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 AutocorrelationReversionStrategy()
{
_autoCorrPeriod = Param(nameof(AutoCorrPeriod), 20)
.SetGreaterThanZero()
.SetDisplay("Autocorrelation Period", "Closes the autocorrelation and the average span", "Indicators");
_autoCorrThreshold = Param(nameof(AutoCorrThreshold), -0.3m)
.SetDisplay("Autocorrelation Threshold", "Autocorrelation below which the market reverts", "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();
_closes.Clear();
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_closes.Clear();
var sma = new SimpleMovingAverage { Length = AutoCorrPeriod };
var subscription = SubscribeCandles(CandleType);
subscription
.BindEx(sma, 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);
DrawIndicator(area, sma);
DrawOwnTrades(area);
}
}
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 smaValue)
{
if (candle.State != CandleStates.Finished)
return;
var close = candle.ClosePrice;
_closes.Enqueue(close);
if (_closes.Count > AutoCorrPeriod)
_closes.Dequeue();
if (_closes.Count < AutoCorrPeriod || !smaValue.IsFormed)
return;
if (!IsFormedAndOnlineAndAllowTrading())
return;
var autocorrelation = CalculateAutocorrelation();
var sma = smaValue.GetValue<decimal>();
var reverting = autocorrelation < AutoCorrThreshold;
if (reverting && close < sma && Position <= 0)
BuyMarket(Volume + Math.Abs(Position));
else if (reverting && close > sma && Position >= 0)
SellMarket(Volume + Math.Abs(Position));
else if (Position > 0 && (close > sma || autocorrelation > AutoCorrThreshold))
SellMarket(Position);
else if (Position < 0 && (close < sma || autocorrelation > AutoCorrThreshold))
BuyMarket(-Position);
}
private decimal CalculateAutocorrelation()
{
var closes = _closes.ToArray();
var changes = new decimal[closes.Length - 1];
for (var i = 1; i < closes.Length; i++)
changes[i - 1] = closes[i] - closes[i - 1];
var mean = changes.Average();
var numerator = 0m;
var denominator = 0m;
for (var i = 0; i < changes.Length; i++)
{
var deviation = changes[i] - mean;
denominator += deviation * deviation;
if (i > 0)
numerator += (changes[i - 1] - mean) * deviation;
}
return denominator == 0 ? 0 : numerator / denominator;
}
}
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
from StockSharp.Messages import DataType, CandleStates, Unit, UnitTypes, Level1Fields
from StockSharp.BusinessEntities import Subscription
from StockSharp.Algo.Indicators import SimpleMovingAverage
from StockSharp.Algo.Strategies import Strategy
class autocorrelation_reversion_strategy(Strategy):
"""
Autocorrelation Reversal strategy.
The autocorrelation is the lag-one autocorrelation of the close-to-close changes over the last AutoCorrPeriod closes. Below
AutoCorrThreshold a close under the AutoCorrPeriod simple moving average goes long and a close above it goes short, reversing an opposite
position. A long closes once the close is above the average or the autocorrelation rises above the threshold, a short mirrors it,
and a percent stop limits the loss.
"""
def __init__(self):
super(autocorrelation_reversion_strategy, self).__init__()
self._auto_corr_period = self.Param("AutoCorrPeriod", 20).SetGreaterThanZero().SetDisplay("Autocorrelation Period", "Closes the autocorrelation and the average span", "Indicators")
self._auto_corr_threshold = self.Param("AutoCorrThreshold", -0.3).SetDisplay("Autocorrelation Threshold", "Autocorrelation below which the market reverts", "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._closes = []
def OnReseted(self):
super(autocorrelation_reversion_strategy, self).OnReseted()
self._reset_state()
def OnStarted2(self, time):
super(autocorrelation_reversion_strategy, self).OnStarted2(time)
self._reset_state()
sma = SimpleMovingAverage()
sma.Length = self._auto_corr_period.Value
subscription = self.SubscribeCandles(self.candle_type)
subscription.BindEx(sma, 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.DrawIndicator(area, sma)
self.DrawOwnTrades(area)
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, sma_value):
if candle.State != CandleStates.Finished:
return
close = candle.ClosePrice
period = self._auto_corr_period.Value
self._closes.append(close)
if len(self._closes) > period:
self._closes.pop(0)
if len(self._closes) < period or not sma_value.IsFormed:
return
if not self.IsFormedAndOnlineAndAllowTrading():
return
autocorrelation = self._calculate_autocorrelation()
sma = sma_value.GetValue[Decimal](None)
threshold = Decimal(self._auto_corr_threshold.Value)
reverting = autocorrelation < threshold
if reverting and close < sma and self.Position <= 0:
self.BuyMarket(self.Volume + abs(self.Position))
elif reverting and close > sma and self.Position >= 0:
self.SellMarket(self.Volume + abs(self.Position))
elif self.Position > 0 and (close > sma or autocorrelation > threshold):
self.SellMarket(self.Position)
elif self.Position < 0 and (close < sma or autocorrelation > threshold):
self.BuyMarket(-self.Position)
def _calculate_autocorrelation(self):
changes = [self._closes[i] - self._closes[i - 1] for i in range(1, len(self._closes))]
total = Decimal(0)
for change in changes:
total += change
mean = total / Decimal(len(changes))
numerator = Decimal(0)
denominator = Decimal(0)
for i in range(len(changes)):
deviation = changes[i] - mean
denominator += deviation * deviation
if i > 0:
numerator += (changes[i - 1] - mean) * deviation
if denominator == 0:
return Decimal(0)
return numerator / denominator
def CreateClone(self):
return autocorrelation_reversion_strategy()