Esta estratégia rastreia o índice de força relativa e mede sua distância de um nível médio. Quando o RSI se desvia em mais de um múltiplo de seu desvio padrão recente, o algoritmo espera um retorno à média.
Os testes indicam um retorno anual médio de aproximadamente 61%. Funciona melhor no mercado de criptomoedas.
Uma operação comprada é aberta quando o RSI cai abaixo da banda inferior definida pela média menos Multiplier vezes o desvio padrão. Uma operação vendida é tomada quando o RSI sobe acima da banda superior. As saídas ocorrem quando o RSI retorna à sua média móvel.
O método é adequado para traders que buscam sinais objetivos de sobrecompra e sobrevenda. Usar uma banda baseada em volatilidade adapta os limiares às condições atuais do mercado, enquanto um stop-loss mantém as perdas limitadas.
Detalhes
- Critérios de entrada:
- Comprado: RSI < Avg - Multiplier * StdDev
- Vendido: RSI > Avg + Multiplier * StdDev
- Comprado/Vendido: Ambos os lados.
- Critérios de saída:
- Comprado: Sair quando RSI > Avg
- Vendido: Sair quando RSI < Avg
- Stops: Sim, stop-loss percentual.
- Valores padrão:
RsiPeriod = 14
AveragePeriod = 20
Multiplier = 2
StopLossPercent = 2
CandleType = TimeSpan.FromMinutes(5)
Avg e StdDev são a média e o desvio padrão dos últimos AveragePeriod valores de RSI, incluindo o atual. O stop é um StopLossPercent fixo do preço de entrada, vigiado também entre os candles; 0 o desativa. Um sinal de entrada contra uma posição aberta a inverte.
- Filtros:
- Categoria: Mean reversion
- Direção: Ambos
- Indicadores: RSI
- Stops: Sim
- Complexidade: Intermediário
- Período: Intradiário
- Sazonalidade: Não
- Redes neurais: Não
- Divergência: Não
- Nível de risco: Médio
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()