Esta estratégia mede o Stochastic Oscillator contra sua própria média móvel para localizar oscilações sobreestendidas. Quando %K se move vários desvios padrão longe de sua média, a expectativa é que o indicador retorne para valores típicos.
Os testes indicam um retorno anual médio de aproximadamente 64%. Funciona melhor no mercado de câmbio.
Uma operação comprada é colocada quando o Stochastic %K cai abaixo da banda inferior definida pela média menos Multiplier vezes o desvio padrão. Uma operação vendida ocorre quando %K excede a banda superior. As posições são fechadas quando %K cruza de volta pela sua linha de média.
O método é projetado para traders de curto prazo que gostam de operar em extremos de sobrecompra e sobrevenda. O stop-loss protege contra o momentum sustentado que não consegue reverter à média.
Detalhes
- Critérios de entrada:
- Comprado: %K < Avg - Multiplier * StdDev
- Vendido: %K > Avg + Multiplier * StdDev
- Comprado/Vendido: Ambos os lados.
- Critérios de saída:
- Comprado: Sair quando %K > Avg
- Vendido: Sair quando %K < Avg
- Stops: Sim, stop-loss percentual.
- Valores padrão:
StochPeriod = 14
KPeriod = 3
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 %K, incluindo o atual. O stop é um StopLossPercent fixo do preço de entrada, vigiado também entre os candles; 0 o desativa. %K é o estocástico do primeiro período suavizado em KPeriod candles; o %D não participa das regras, por isso DPeriod foi removido. Um sinal de entrada contra uma posição aberta a inverte.
- Filtros:
- Categoria: Mean reversion
- Direção: Ambos
- Indicadores: Stochastic Oscillator
- 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>
/// 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()