ADX: средневозврат по наклону
Стратегия ADX Slope Mean Reversion сосредоточена на экстремальных значениях индекса среднего направленного движения (ADX), чтобы использовать возврат к среднему. Широкие отклонения от среднего уровня редко продолжаются долго.
Сделки открываются, когда индикатор значительно отклоняется от своего среднего значения и начинает разворачиваться. Вход в длинные и короткие позиции сопровождается защитным стопом.
Подходит свинг‑трейдерам, ожидающим колебаний; стратегия закрывает позицию, когда ADX возвращается к равновесию. Начальное значение AdxPeriod = 14.
Детали
- Условия входа: Индикатор разворачивается в сторону среднего значения.
- Длинные/Короткие: Оба направления.
- Условия выхода: Индикатор возвращается к среднему.
- Стопы: Да.
- Значения по умолчанию:
AdxPeriod= 14LookbackPeriod= 20DeviationMultiplier= 1.0mStopLossPercent= 2.0mCandleType= TimeSpan.FromMinutes(5)
- Фильтры:
- Категория: Средневозвратная
- Направление: Оба
- Индикаторы: ADX
- Стопы: Да
- Сложность: Средняя
- Таймфрейм: Краткосрочный
- Сезонность: Нет
- Нейросети: Нет
- Дивергенция: Нет
- Уровень риска: Средний
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>
/// ADX slope mean reversion strategy.
/// Trades reversion of extreme ADX slope moves once the recent slope distribution is formed.
/// </summary>
public class AdxSlopeMeanReversionStrategy : Strategy
{
private readonly StrategyParam<int> _adxPeriod;
private readonly StrategyParam<int> _slopeLookback;
private readonly StrategyParam<decimal> _thresholdMultiplier;
private readonly StrategyParam<decimal> _stopLossPercent;
private readonly StrategyParam<int> _cooldownBars;
private readonly StrategyParam<decimal> _minAdx;
private readonly StrategyParam<DataType> _candleType;
private AverageDirectionalIndex _adx;
private decimal _previousAdxValue;
private decimal[] _slopeHistory;
private int _currentIndex;
private int _filledCount;
private int _cooldown;
private bool _isInitialized;
/// <summary>
/// ADX period.
/// </summary>
public int AdxPeriod
{
get => _adxPeriod.Value;
set => _adxPeriod.Value = value;
}
/// <summary>
/// Lookback used to estimate slope mean and standard deviation.
/// </summary>
public int SlopeLookback
{
get => _slopeLookback.Value;
set => _slopeLookback.Value = value;
}
/// <summary>
/// Standard deviation multiplier for entry threshold.
/// </summary>
public decimal ThresholdMultiplier
{
get => _thresholdMultiplier.Value;
set => _thresholdMultiplier.Value = value;
}
/// <summary>
/// Stop loss percentage.
/// </summary>
public decimal StopLossPercent
{
get => _stopLossPercent.Value;
set => _stopLossPercent.Value = value;
}
/// <summary>
/// Bars to wait between orders.
/// </summary>
public int CooldownBars
{
get => _cooldownBars.Value;
set => _cooldownBars.Value = value;
}
/// <summary>
/// Minimum ADX level required for entries.
/// </summary>
public decimal MinAdx
{
get => _minAdx.Value;
set => _minAdx.Value = value;
}
/// <summary>
/// Candle type.
/// </summary>
public DataType CandleType
{
get => _candleType.Value;
set => _candleType.Value = value;
}
/// <summary>
/// Initializes a new instance of <see cref="AdxSlopeMeanReversionStrategy"/>.
/// </summary>
public AdxSlopeMeanReversionStrategy()
{
_adxPeriod = Param(nameof(AdxPeriod), 14)
.SetGreaterThanZero()
.SetDisplay("ADX Period", "Period for ADX calculation", "Indicator Parameters")
.SetOptimize(10, 20, 2);
_slopeLookback = Param(nameof(SlopeLookback), 20)
.SetGreaterThanZero()
.SetDisplay("Slope Lookback", "Period for slope statistics", "Strategy Parameters")
.SetOptimize(10, 50, 5);
_thresholdMultiplier = Param(nameof(ThresholdMultiplier), 1.5m)
.SetGreaterThanZero()
.SetDisplay("Threshold Multiplier", "Standard deviation multiplier for entries", "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");
_minAdx = Param(nameof(MinAdx), 18m)
.SetGreaterThanZero()
.SetDisplay("Min ADX", "Minimum ADX level required for entries", "Signal Filters");
_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();
_adx = null;
_previousAdxValue = default;
_slopeHistory = new decimal[SlopeLookback];
_currentIndex = default;
_filledCount = default;
_cooldown = default;
_isInitialized = default;
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_adx = new AverageDirectionalIndex { Length = AdxPeriod };
_slopeHistory = new decimal[SlopeLookback];
_currentIndex = 0;
_filledCount = 0;
_cooldown = 0;
var subscription = SubscribeCandles(CandleType);
subscription
.BindEx(_adx, ProcessCandle)
.Start();
StartProtection(new(), new Unit(StopLossPercent, UnitTypes.Percent));
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawIndicator(area, _adx);
DrawOwnTrades(area);
}
}
private void ProcessCandle(ICandleMessage candle, IIndicatorValue adxValue)
{
if (candle.State != CandleStates.Finished)
return;
if (!_adx.IsFormed)
return;
var typedValue = (AverageDirectionalIndexValue)adxValue;
if (typedValue.MovingAverage is not decimal adx)
return;
var dx = typedValue.Dx;
if (dx.Plus is not decimal diPlus || dx.Minus is not decimal diMinus)
return;
if (!_isInitialized)
{
_previousAdxValue = adx;
_isInitialized = true;
return;
}
var slope = adx - _previousAdxValue;
_previousAdxValue = adx;
_slopeHistory[_currentIndex] = slope;
_currentIndex = (_currentIndex + 1) % SlopeLookback;
if (_filledCount < SlopeLookback)
_filledCount++;
if (_filledCount < SlopeLookback)
return;
CalculateStatistics(out var averageSlope, out var slopeStdDev);
if (!IsFormedAndOnlineAndAllowTrading())
return;
if (slopeStdDev <= 0)
return;
if (_cooldown > 0)
{
_cooldown--;
return;
}
var lowerThreshold = averageSlope - ThresholdMultiplier * slopeStdDev;
var upperThreshold = averageSlope + ThresholdMultiplier * slopeStdDev;
var isBullish = diPlus >= diMinus;
var isBearish = diMinus > diPlus;
if (Position == 0)
{
if (adx >= MinAdx && slope <= lowerThreshold && isBullish)
{
BuyMarket();
_cooldown = CooldownBars;
}
else if (adx >= MinAdx && slope >= upperThreshold && isBearish)
{
SellMarket();
_cooldown = CooldownBars;
}
}
else if (Position > 0)
{
if (slope >= averageSlope || !isBullish)
{
SellMarket(Math.Abs(Position));
_cooldown = CooldownBars;
}
}
else if (Position < 0)
{
if (slope <= averageSlope || !isBearish)
{
BuyMarket(Math.Abs(Position));
_cooldown = CooldownBars;
}
}
}
private void CalculateStatistics(out decimal averageSlope, out decimal slopeStdDev)
{
averageSlope = 0m;
var sumSquaredDiffs = 0m;
for (var i = 0; i < SlopeLookback; i++)
averageSlope += _slopeHistory[i];
averageSlope /= SlopeLookback;
for (var i = 0; i < SlopeLookback; i++)
{
var diff = _slopeHistory[i] - averageSlope;
sumSquaredDiffs += diff * diff;
}
slopeStdDev = (decimal)Math.Sqrt((double)(sumSquaredDiffs / SlopeLookback));
}
}
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 AverageDirectionalIndex
from StockSharp.Algo.Strategies import Strategy
class adx_slope_mean_reversion_strategy(Strategy):
"""
ADX slope mean reversion strategy.
Trades reversion of extreme ADX slope moves once the recent slope distribution is formed.
"""
def __init__(self):
super(adx_slope_mean_reversion_strategy, self).__init__()
self._adx_period = self.Param("AdxPeriod", 14) \
.SetGreaterThanZero() \
.SetDisplay("ADX Period", "Period for ADX calculation", "Indicator Parameters")
self._slope_lookback = self.Param("SlopeLookback", 20) \
.SetGreaterThanZero() \
.SetDisplay("Slope Lookback", "Period for slope statistics", "Strategy Parameters")
self._threshold_multiplier = self.Param("ThresholdMultiplier", 1.5) \
.SetGreaterThanZero() \
.SetDisplay("Threshold Multiplier", "Standard deviation multiplier for entries", "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._min_adx = self.Param("MinAdx", 18.0) \
.SetGreaterThanZero() \
.SetDisplay("Min ADX", "Minimum ADX level required for entries", "Signal Filters")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(5))) \
.SetDisplay("Candle Type", "Type of candles to use", "General")
self._adx = None
self._previous_adx_value = 0.0
self._slope_history = None
self._current_index = 0
self._filled_count = 0
self._cooldown = 0
self._is_initialized = False
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(adx_slope_mean_reversion_strategy, self).OnReseted()
self._adx = None
self._previous_adx_value = 0.0
lb = int(self._slope_lookback.Value)
self._slope_history = [0.0] * lb
self._current_index = 0
self._filled_count = 0
self._cooldown = 0
self._is_initialized = False
def OnStarted2(self, time):
super(adx_slope_mean_reversion_strategy, self).OnStarted2(time)
lb = int(self._slope_lookback.Value)
self._slope_history = [0.0] * lb
self._current_index = 0
self._filled_count = 0
self._cooldown = 0
self._adx = AverageDirectionalIndex()
self._adx.Length = int(self._adx_period.Value)
subscription = self.SubscribeCandles(self.candle_type)
subscription.BindEx(self._adx, self._process_candle).Start()
self.StartProtection(Unit(), Unit(self._stop_loss_percent.Value, UnitTypes.Percent))
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawIndicator(area, self._adx)
self.DrawOwnTrades(area)
def _process_candle(self, candle, adx_value):
if candle.State != CandleStates.Finished:
return
if not self._adx.IsFormed:
return
adx_ma = adx_value.MovingAverage
if adx_ma is None:
return
adx_val = float(adx_ma)
dx = adx_value.Dx
if dx is None or dx.Plus is None or dx.Minus is None:
return
di_plus = float(dx.Plus)
di_minus = float(dx.Minus)
if not self._is_initialized:
self._previous_adx_value = adx_val
self._is_initialized = True
return
slope = adx_val - self._previous_adx_value
self._previous_adx_value = adx_val
lb = int(self._slope_lookback.Value)
self._slope_history[self._current_index] = slope
self._current_index = (self._current_index + 1) % lb
if self._filled_count < lb:
self._filled_count += 1
if self._filled_count < lb:
return
avg_slope = 0.0
for i in range(lb):
avg_slope += self._slope_history[i]
avg_slope /= float(lb)
sum_sq = 0.0
for i in range(lb):
diff = self._slope_history[i] - avg_slope
sum_sq += diff * diff
std_slope = math.sqrt(sum_sq / float(lb))
if not self.IsFormedAndOnlineAndAllowTrading():
return
if std_slope <= 0:
return
if self._cooldown > 0:
self._cooldown -= 1
return
tm = float(self._threshold_multiplier.Value)
lower_threshold = avg_slope - tm * std_slope
upper_threshold = avg_slope + tm * std_slope
min_adx = float(self._min_adx.Value)
is_bullish = di_plus >= di_minus
is_bearish = di_minus > di_plus
if self.Position == 0:
if adx_val >= min_adx and slope <= lower_threshold and is_bullish:
self.BuyMarket()
self._cooldown = int(self._cooldown_bars.Value)
elif adx_val >= min_adx and slope >= upper_threshold and is_bearish:
self.SellMarket()
self._cooldown = int(self._cooldown_bars.Value)
elif self.Position > 0:
if slope >= avg_slope or not is_bullish:
self.SellMarket(Math.Abs(self.Position))
self._cooldown = int(self._cooldown_bars.Value)
elif self.Position < 0:
if slope <= avg_slope or not is_bearish:
self.BuyMarket(Math.Abs(self.Position))
self._cooldown = int(self._cooldown_bars.Value)
def CreateClone(self):
return adx_slope_mean_reversion_strategy()