RSI 均值回归策略
该策略跟踪相对强弱指数(RSI)与其平均值的偏离程度。当 RSI 偏离超过近期标准差的数倍时,预期其向均值回归。
测试表明年均收益约为 61%,该策略在加密市场表现最佳。
当 RSI 低于平均值减 Multiplier 倍标准差时做多;当 RSI 高于平均值加同样倍数时做空。RSI 回到移动平均附近即平仓。
此方法适合寻找超买超卖信号的交易者,波动率带可以根据市况调整阈值,止损有助于控制风险。
详细信息
- 入场条件:
- 做多: RSI < Avg - Multiplier * StdDev
- 做空: RSI > Avg + Multiplier * StdDev
- 多空方向: 双向
- 退出条件:
- 做多: Exit when RSI > Avg
- 做空: Exit when RSI < Avg
- 止损: 是
- 默认值:
RsiPeriod= 14AveragePeriod= 20Multiplier= 2StopLossPercent= 2CandleType= TimeSpan.FromMinutes(5) Avg和StdDev为最近AveragePeriod个RSI值(含当前值)的平均值和标准差。止损为入场价的固定StopLossPercent百分比,在K线之间同样监控;设为0则关闭。与持仓方向相反的入场信号会反转持仓。
- 筛选条件:
- 类别: 均值回归
- 方向: 双向
- 指标: RSI
- 止损: 是
- 复杂度: 中等
- 时间框架: 日内
- 季节性: 否
- 神经网络: 否
- 背离: 否
- 风险等级: 中等
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()