RSI Mean Reversion-Strategie
Diese Strategie verfolgt den Relative Strength Index und misst seinen Abstand von einem Durchschnittsniveau. Wenn RSI um mehr als ein Vielfaches seiner jüngsten Standardabweichung abweicht, erwartet der Algorithmus eine Rückkehr zum Mittelwert.
Tests zeigen eine durchschnittliche jährliche Rendite von etwa 61%. Er funktioniert am besten auf dem Kryptomarkt.
Ein Long-Trade wird eröffnet, wenn RSI unter das untere Band fällt, das durch den Durchschnitt minus Multiplier mal die Standardabweichung definiert wird. Ein Short-Trade wird eingegangen, wenn RSI über das obere Band steigt. Ausstiege erfolgen, wenn RSI zu seinem gleitenden Durchschnitt zurückkehrt.
Die Methode eignet sich für Trader, die nach objektiven überverkauften und überkauften Signalen suchen. Die Verwendung eines volatilitätsbasierten Bandes passt die Schwellenwerte an die aktuellen Marktbedingungen an, während ein Stop-Loss die Verluste begrenzt.
Details
- Einstiegskriterien:
- Long: RSI < Avg - Multiplier * StdDev
- Short: RSI > Avg + Multiplier * StdDev
- Long/Short: Beide Seiten.
- Ausstiegskriterien:
- Long: Ausstieg wenn RSI > Avg
- Short: Ausstieg wenn RSI < Avg
- Stops: Ja, prozentualer Stop-Loss.
- Standardwerte:
RsiPeriod = 14
AveragePeriod = 20
Multiplier = 2
StopLossPercent = 2
CandleType = TimeSpan.FromMinutes(5)
Avg und StdDev sind Mittelwert und Standardabweichung der letzten AveragePeriod Werte von RSI einschließlich des aktuellen. 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.
- Filter:
- Kategorie: Mean Reversion
- Richtung: Beide
- Indikatoren: RSI
- 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>
/// RSI Mean Reversion strategy.
/// The bands lie Multiplier standard deviations around the average of the last AveragePeriod RSI values, the current one included.
/// RSI below the lower band goes long and RSI above the upper band goes short,
/// reversing an opposite position. A long closes once RSI is back above its average and a short once it is back below it, and a percent stop limits the loss.
/// </summary>
public class RsiMeanReversionStrategy : Strategy
{
private readonly StrategyParam<int> _rsiPeriod;
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>
/// Period of RSI.
/// </summary>
public int RsiPeriod
{
get => _rsiPeriod.Value;
set => _rsiPeriod.Value = value;
}
/// <summary>
/// Values of RSI 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 RsiMeanReversionStrategy()
{
_rsiPeriod = Param(nameof(RsiPeriod), 14)
.SetGreaterThanZero()
.SetDisplay("RSI Period", "Period of RSI", "Indicators");
_averagePeriod = Param(nameof(AveragePeriod), 20)
.SetGreaterThanZero()
.SetDisplay("Average Period", "Values of RSI 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 rsi = new RelativeStrengthIndex { Length = RsiPeriod };
var subscription = SubscribeCandles(CandleType);
subscription
.BindEx(rsi, 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, rsi);
}
}
}
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 rsiValue)
{
if (candle.State != CandleStates.Finished)
return;
if (!rsiValue.IsFormed)
return;
var value = rsiValue.GetValue<decimal>();
_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 RelativeStrengthIndex
from StockSharp.Algo.Strategies import Strategy
class rsi_mean_reversion_strategy(Strategy):
"""
RSI Mean Reversion strategy.
The bands lie Multiplier standard deviations around the average of the last AveragePeriod RSI values, the current one included.
RSI below the lower band goes long and RSI above the upper band goes short,
reversing an opposite position. A long closes once RSI 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(rsi_mean_reversion_strategy, self).__init__()
self._rsi_period = self.Param("RsiPeriod", 14).SetGreaterThanZero().SetDisplay("RSI Period", "Period of RSI", "Indicators")
self._average_period = self.Param("AveragePeriod", 20).SetGreaterThanZero().SetDisplay("Average Period", "Values of RSI 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(rsi_mean_reversion_strategy, self).OnReseted()
self._reset_state()
def OnStarted2(self, time):
super(rsi_mean_reversion_strategy, self).OnStarted2(time)
self._reset_state()
rsi = RelativeStrengthIndex()
rsi.Length = self._rsi_period.Value
subscription = self.SubscribeCandles(self.candle_type)
subscription.BindEx(rsi, 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, rsi)
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, rsi_value):
if candle.State != CandleStates.Finished:
return
if not rsi_value.IsFormed:
return
value = rsi_value.GetValue[Decimal](None)
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 rsi_mean_reversion_strategy()