Donchian Width Mean Reversion
Donchian Width Mean Reversion 策略关注指标的极端读数以捕捉均值回归。远离正常水平的情况通常不会持续太久。
测试表明年均收益约为 121%,该策略在加密市场表现最佳。
当指标大幅偏离均值后开始反转时产生交易信号,可做多也可做空,并带有保护性止损。
适合预期震荡行情的交易者,当指标回归平衡时平仓。初始参数 DonchianPeriod = 20.
详细信息
- 入场条件: Indicator crosses back toward mean.
- 多空: Both directions.
- 出场条件: Indicator reverts to average.
- 止损: Yes.
- 默认值:
DonchianPeriod= 20LookbackPeriod= 20DeviationMultiplier= 2.0mStopLossPercent= 2.0mCandleType= TimeSpan.FromMinutes(5)
- 过滤器:
- 分类: Mean Reversion
- 方向: Both
- 指标: Donchian
- 止损: Yes
- 复杂度: Intermediate
- 时间框架: Short-term
- 季节性: No
- 神经网络: No
- 背离: No
- 风险级别: Medium
using System;
using System.Collections.Generic;
using Ecng.Common;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
/// <summary>
/// Donchian width mean reversion strategy.
/// Trades contractions and expansions of Donchian Channel width around its recent average.
/// </summary>
public class DonchianWidthMeanReversionStrategy : Strategy
{
private readonly StrategyParam<int> _donchianPeriod;
private readonly StrategyParam<int> _lookbackPeriod;
private readonly StrategyParam<decimal> _deviationMultiplier;
private readonly StrategyParam<decimal> _stopLossPercent;
private readonly StrategyParam<int> _cooldownBars;
private readonly StrategyParam<DataType> _candleType;
private DonchianChannels _donchian;
private decimal[] _widthHistory;
private int _currentIndex;
private int _filledCount;
private int _cooldown;
/// <summary>
/// Donchian Channel period.
/// </summary>
public int DonchianPeriod
{
get => _donchianPeriod.Value;
set => _donchianPeriod.Value = value;
}
/// <summary>
/// Lookback period for width statistics.
/// </summary>
public int LookbackPeriod
{
get => _lookbackPeriod.Value;
set => _lookbackPeriod.Value = value;
}
/// <summary>
/// Deviation multiplier for mean reversion detection.
/// </summary>
public decimal DeviationMultiplier
{
get => _deviationMultiplier.Value;
set => _deviationMultiplier.Value = value;
}
/// <summary>
/// Stop loss percentage.
/// </summary>
public decimal StopLossPercent
{
get => _stopLossPercent.Value;
set => _stopLossPercent.Value = value;
}
/// <summary>
/// Cooldown bars between orders.
/// </summary>
public int CooldownBars
{
get => _cooldownBars.Value;
set => _cooldownBars.Value = value;
}
/// <summary>
/// Candle type.
/// </summary>
public DataType CandleType
{
get => _candleType.Value;
set => _candleType.Value = value;
}
/// <summary>
/// Initializes a new instance of <see cref="DonchianWidthMeanReversionStrategy"/>.
/// </summary>
public DonchianWidthMeanReversionStrategy()
{
_donchianPeriod = Param(nameof(DonchianPeriod), 20)
.SetGreaterThanZero()
.SetDisplay("Donchian Period", "Donchian Channel period", "Indicators")
.SetOptimize(10, 50, 5);
_lookbackPeriod = Param(nameof(LookbackPeriod), 20)
.SetGreaterThanZero()
.SetDisplay("Lookback Period", "Lookback period for width statistics", "Strategy Parameters")
.SetOptimize(10, 50, 5);
_deviationMultiplier = Param(nameof(DeviationMultiplier), 1.5m)
.SetGreaterThanZero()
.SetDisplay("Deviation Multiplier", "Deviation multiplier for mean reversion detection", "Strategy Parameters")
.SetOptimize(1m, 3m, 0.5m);
_stopLossPercent = Param(nameof(StopLossPercent), 2m)
.SetGreaterThanZero()
.SetDisplay("Stop Loss %", "Stop loss percentage", "Risk Management");
_cooldownBars = Param(nameof(CooldownBars), 1200)
.SetRange(1, 5000)
.SetDisplay("Cooldown Bars", "Bars to wait between orders", "Risk Management");
_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(5).TimeFrame())
.SetDisplay("Candle Type", "Candle type for strategy", "General");
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_donchian = null;
_currentIndex = default;
_filledCount = default;
_cooldown = default;
_widthHistory = new decimal[LookbackPeriod];
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_donchian = new DonchianChannels { Length = DonchianPeriod };
_widthHistory = new decimal[LookbackPeriod];
_currentIndex = 0;
_filledCount = 0;
_cooldown = 0;
var subscription = SubscribeCandles(CandleType);
subscription
.BindEx(_donchian, ProcessDonchian)
.Start();
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawIndicator(area, _donchian);
DrawOwnTrades(area);
}
StartProtection(new(), new Unit(StopLossPercent, UnitTypes.Percent));
}
private void ProcessDonchian(ICandleMessage candle, IIndicatorValue donchianValue)
{
if (candle.State != CandleStates.Finished)
return;
if (!_donchian.IsFormed)
return;
var typedValue = (DonchianChannelsValue)donchianValue;
if (typedValue.UpperBand is not decimal upperBand ||
typedValue.LowerBand is not decimal lowerBand)
return;
var width = upperBand - lowerBand;
_widthHistory[_currentIndex] = width;
_currentIndex = (_currentIndex + 1) % LookbackPeriod;
if (_filledCount < LookbackPeriod)
_filledCount++;
if (_filledCount < LookbackPeriod)
return;
var avgWidth = 0m;
var sumSq = 0m;
for (var i = 0; i < LookbackPeriod; i++)
avgWidth += _widthHistory[i];
avgWidth /= LookbackPeriod;
for (var i = 0; i < LookbackPeriod; i++)
{
var diff = _widthHistory[i] - avgWidth;
sumSq += diff * diff;
}
var stdWidth = (decimal)Math.Sqrt((double)(sumSq / LookbackPeriod));
if (!IsFormedAndOnlineAndAllowTrading())
return;
if (_cooldown > 0)
{
_cooldown--;
return;
}
var narrowThreshold = avgWidth - stdWidth * DeviationMultiplier;
var wideThreshold = avgWidth + stdWidth * DeviationMultiplier;
if (Position == 0)
{
if (width < narrowThreshold)
{
BuyMarket();
_cooldown = CooldownBars;
}
else if (width > wideThreshold)
{
SellMarket();
_cooldown = CooldownBars;
}
}
else if (Position > 0 && width >= avgWidth)
{
SellMarket(Math.Abs(Position));
_cooldown = CooldownBars;
}
else if (Position < 0 && width <= avgWidth)
{
BuyMarket(Math.Abs(Position));
_cooldown = CooldownBars;
}
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")
import math
from System import TimeSpan, Math
from StockSharp.Messages import DataType, Unit, UnitTypes, CandleStates
from StockSharp.Algo.Indicators import DonchianChannels
from StockSharp.Algo.Strategies import Strategy
class donchian_width_mean_reversion_strategy(Strategy):
"""
Donchian width mean reversion strategy.
Trades contractions and expansions of Donchian Channel width around its recent average.
"""
def __init__(self):
super(donchian_width_mean_reversion_strategy, self).__init__()
self._donchian_period = self.Param("DonchianPeriod", 20) \
.SetGreaterThanZero() \
.SetDisplay("Donchian Period", "Donchian Channel period", "Indicators")
self._lookback_period = self.Param("LookbackPeriod", 20) \
.SetGreaterThanZero() \
.SetDisplay("Lookback Period", "Lookback period for width statistics", "Strategy Parameters")
self._deviation_multiplier = self.Param("DeviationMultiplier", 1.5) \
.SetGreaterThanZero() \
.SetDisplay("Deviation Multiplier", "Deviation multiplier for mean reversion detection", "Strategy Parameters")
self._stop_loss_percent = self.Param("StopLossPercent", 2.0) \
.SetGreaterThanZero() \
.SetDisplay("Stop Loss %", "Stop loss percentage", "Risk Management")
self._cooldown_bars = self.Param("CooldownBars", 1200) \
.SetDisplay("Cooldown Bars", "Bars to wait between orders", "Risk Management")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(5))) \
.SetDisplay("Candle Type", "Candle type for strategy", "General")
self._donchian = None
self._width_history = None
self._current_index = 0
self._filled_count = 0
self._cooldown = 0
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(donchian_width_mean_reversion_strategy, self).OnReseted()
self._donchian = None
lb = int(self._lookback_period.Value)
self._width_history = [0.0] * lb
self._current_index = 0
self._filled_count = 0
self._cooldown = 0
def OnStarted2(self, time):
super(donchian_width_mean_reversion_strategy, self).OnStarted2(time)
lb = int(self._lookback_period.Value)
self._width_history = [0.0] * lb
self._current_index = 0
self._filled_count = 0
self._cooldown = 0
self._donchian = DonchianChannels()
self._donchian.Length = int(self._donchian_period.Value)
subscription = self.SubscribeCandles(self.candle_type)
subscription.BindEx(self._donchian, self._process_donchian).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawIndicator(area, self._donchian)
self.DrawOwnTrades(area)
self.StartProtection(Unit(), Unit(self._stop_loss_percent.Value, UnitTypes.Percent))
def _process_donchian(self, candle, donchian_value):
if candle.State != CandleStates.Finished:
return
if not self._donchian.IsFormed:
return
upper_band = donchian_value.UpperBand
lower_band = donchian_value.LowerBand
if upper_band is None or lower_band is None:
return
upper_val = float(upper_band)
lower_val = float(lower_band)
width = upper_val - lower_val
lb = int(self._lookback_period.Value)
self._width_history[self._current_index] = width
self._current_index = (self._current_index + 1) % lb
if self._filled_count < lb:
self._filled_count += 1
if self._filled_count < lb:
return
avg_width = 0.0
for i in range(lb):
avg_width += self._width_history[i]
avg_width /= float(lb)
sum_sq = 0.0
for i in range(lb):
diff = self._width_history[i] - avg_width
sum_sq += diff * diff
std_width = math.sqrt(sum_sq / float(lb))
if not self.IsFormedAndOnlineAndAllowTrading():
return
if self._cooldown > 0:
self._cooldown -= 1
return
dm = float(self._deviation_multiplier.Value)
narrow_threshold = avg_width - std_width * dm
wide_threshold = avg_width + std_width * dm
if self.Position == 0:
if width < narrow_threshold:
self.BuyMarket()
self._cooldown = int(self._cooldown_bars.Value)
elif width > wide_threshold:
self.SellMarket()
self._cooldown = int(self._cooldown_bars.Value)
elif self.Position > 0 and width >= avg_width:
self.SellMarket(Math.Abs(self.Position))
self._cooldown = int(self._cooldown_bars.Value)
elif self.Position < 0 and width <= avg_width:
self.BuyMarket(Math.Abs(self.Position))
self._cooldown = int(self._cooldown_bars.Value)
def CreateClone(self):
return donchian_width_mean_reversion_strategy()