Стратегия возврата по стохастику
Стратегия сравнивает значение стохастического осциллятора с его собственной скользящей средней, чтобы выявить чрезмерные колебания. Когда %K отклоняется на несколько стандартных отклонений от своего среднего, ожидается возврат индикатора к обычным значениям.
Тестирование показывает среднегодичную доходность около 64%. Стратегию лучше запускать на рынке Форекс.
Длинная сделка совершается, когда %K падает ниже нижней полосы, определённой средним минус Multiplier стандартных отклонений. Короткая сделка происходит, когда %K превышает верхнюю полосу. Позиции закрываются, как только %K пересекает свою среднюю линию.
Метод предназначен для краткосрочных трейдеров, любящих торговать на перекупленности и перепроданности. Стоп‑лосс защищает от устойчивого импульса, который не стремится к возврату.
Подробности
- Условия входа:
- Long: %K < Avg − Multiplier * StdDev
- Short: %K > Avg + Multiplier * StdDev
- Long/Short: обе стороны.
- Условия выхода:
- Long: выход при %K > Avg
- Short: выход при %K < Avg
- Стопы: да, процентный стоп‑лосс.
- Параметры по умолчанию:
StochPeriod= 14KPeriod= 3AveragePeriod= 20Multiplier= 2StopLossPercent= 2CandleType= TimeSpan.FromMinutes(5) Avg и StdDev — среднее и стандартное отклонение последних AveragePeriod значений %K, включая текущее. Стоп — фиксированный StopLossPercent от цены входа, он отслеживается и между свечами; 0 отключает его. %K — стохастик за первый период, сглаженный за KPeriod свечей; линия %D в правилах не участвует, поэтому DPeriod убран. Сигнал на вход против открытой позиции разворачивает её.
- Фильтры:
- Категория: Возврат к среднему
- Направление: Обе стороны
- Индикаторы: Стохастик
- Стопы: Да
- Сложность: Средняя
- Таймфрейм: Внутридневной
- Сезонность: Нет
- Нейросети: Нет
- Дивергенция: Нет
- Уровень риска: Средний
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>
/// Stochastic Mean Reversion strategy.
/// The bands lie Multiplier standard deviations around the average of the last AveragePeriod %K values, the current one included.
/// %K below the lower band goes long and %K above the upper band goes short,
/// reversing an opposite position. A long closes once %K is back above its average and a short once it is back below it, and a percent stop limits the loss.
/// </summary>
public class StochasticMeanReversionStrategy : Strategy
{
private readonly StrategyParam<int> _stochPeriod;
private readonly StrategyParam<int> _kPeriod;
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>
/// Lookback period of the raw stochastic.
/// </summary>
public int StochPeriod
{
get => _stochPeriod.Value;
set => _stochPeriod.Value = value;
}
/// <summary>
/// Smoothing period of %K.
/// </summary>
public int KPeriod
{
get => _kPeriod.Value;
set => _kPeriod.Value = value;
}
/// <summary>
/// Values of %K 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 StochasticMeanReversionStrategy()
{
_stochPeriod = Param(nameof(StochPeriod), 14)
.SetGreaterThanZero()
.SetDisplay("Stochastic Period", "Lookback period of the raw stochastic", "Indicators");
_kPeriod = Param(nameof(KPeriod), 3)
.SetGreaterThanZero()
.SetDisplay("%K Period", "Smoothing period of %K", "Indicators");
_averagePeriod = Param(nameof(AveragePeriod), 20)
.SetGreaterThanZero()
.SetDisplay("Average Period", "Values of %K 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 stochastic = new StochasticOscillator
{
K = { Length = StochPeriod },
D = { Length = KPeriod },
};
var subscription = SubscribeCandles(CandleType);
subscription
.BindEx(stochastic, 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, stochastic);
}
}
}
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 stochasticValue)
{
if (candle.State != CandleStates.Finished)
return;
// The smoothed %K is the moving average the core oscillator exposes as D.
if (!stochasticValue.IsFormed || stochasticValue is not IStochasticOscillatorValue { D: decimal value })
return;
_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 StochasticOscillator
from StockSharp.Algo.Strategies import Strategy
class stochastic_mean_reversion_strategy(Strategy):
"""
Stochastic Mean Reversion strategy.
The bands lie Multiplier standard deviations around the average of the last AveragePeriod %K values, the current one included.
%K below the lower band goes long and %K above the upper band goes short,
reversing an opposite position. A long closes once %K 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(stochastic_mean_reversion_strategy, self).__init__()
self._stoch_period = self.Param("StochPeriod", 14).SetGreaterThanZero().SetDisplay("Stochastic Period", "Lookback period of the raw stochastic", "Indicators")
self._k_period = self.Param("KPeriod", 3).SetGreaterThanZero().SetDisplay("%K Period", "Smoothing period of %K", "Indicators")
self._average_period = self.Param("AveragePeriod", 20).SetGreaterThanZero().SetDisplay("Average Period", "Values of %K 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(stochastic_mean_reversion_strategy, self).OnReseted()
self._reset_state()
def OnStarted2(self, time):
super(stochastic_mean_reversion_strategy, self).OnStarted2(time)
self._reset_state()
stochastic = StochasticOscillator()
stochastic.K.Length = self._stoch_period.Value
stochastic.D.Length = self._k_period.Value
subscription = self.SubscribeCandles(self.candle_type)
subscription.BindEx(stochastic, 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, stochastic)
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, stochastic_value):
if candle.State != CandleStates.Finished:
return
# The smoothed %K is the moving average the core oscillator exposes as D.
if not stochastic_value.IsFormed or stochastic_value.D is None:
return
value = stochastic_value.D
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 stochastic_mean_reversion_strategy()