Labouchere EA 策略
本策略结合了随机振荡指标交叉与 Labouchere 资金管理序列。当 %K 线与 %D 线交叉时生成买卖信号。Labouchere 系统在每次平仓后调整交易手数:亏损时在序列末尾添加首尾元素之和,盈利时移除首尾元素。
策略仅在已完成的 K 线上执行交易。序列在所有元素被移除后可选择重新开始。时间过滤器允许在指定时段内交易,反向信号可用于平仓。支持以价格步长为单位的固定止损和止盈。
细节
- 入场条件:
- 做多:%K 从下向上穿越 %D。
- 做空:%K 从上向下穿越 %D。
- 多空方向:双向。
- 出场条件:
- 可选的反向信号平仓。
- 固定止损和止盈(若设置)。
- 止损:支持。
- 资金管理:Labouchere 序列。
- 默认参数:
LotSequence= "0.01,0.02,0.01,0.02,0.01,0.01,0.01,0.01"NewRecycle= trueStopLoss= 40TakeProfit= 50IsReversed= falseUseOppositeExit= falseUseWorkTime= falseStartTime= 00:00StopTime= 24:00KPeriod= 10DPeriod= 190
- 筛选:
- 类别:混合
- 方向:双向
- 指标:Stochastic Oscillator
- 止损:有
- 复杂度:中等
- 时间框架:日内
- 季节性:无
- 神经网络:无
- 背离:无
- 风险等级:中等
using System;
using System.Linq;
using System.Collections.Generic;
using Ecng.Common;
using Ecng.Collections;
using Ecng.Serialization;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
/// <summary>
/// Labouchere betting system strategy using Stochastic oscillator for signals.
/// Adjusts position sizing based on the Labouchere sequence.
/// </summary>
public class LabouchereEaStrategy : Strategy
{
private readonly StrategyParam<DataType> _candleType;
private readonly StrategyParam<int> _kPeriod;
private readonly StrategyParam<int> _dPeriod;
private readonly StrategyParam<decimal> _stopLossPct;
private readonly StrategyParam<decimal> _takeProfitPct;
private decimal? _prevK;
private decimal? _prevD;
private decimal _entryPrice;
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public int KPeriod { get => _kPeriod.Value; set => _kPeriod.Value = value; }
public int DPeriod { get => _dPeriod.Value; set => _dPeriod.Value = value; }
public decimal StopLossPct { get => _stopLossPct.Value; set => _stopLossPct.Value = value; }
public decimal TakeProfitPct { get => _takeProfitPct.Value; set => _takeProfitPct.Value = value; }
public LabouchereEaStrategy()
{
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(4).TimeFrame())
.SetDisplay("Candle Type", "Type of candles used", "General");
_kPeriod = Param(nameof(KPeriod), 10)
.SetDisplay("K Period", "Stochastic %K period", "Indicator")
.SetGreaterThanZero();
_dPeriod = Param(nameof(DPeriod), 3)
.SetDisplay("D Period", "Stochastic %D period", "Indicator")
.SetGreaterThanZero();
_stopLossPct = Param(nameof(StopLossPct), 1m)
.SetDisplay("Stop Loss %", "Stop loss percent", "Risk")
.SetGreaterThanZero();
_takeProfitPct = Param(nameof(TakeProfitPct), 1.5m)
.SetDisplay("Take Profit %", "Take profit percent", "Risk")
.SetGreaterThanZero();
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
var stoch = new StochasticOscillator
{
K = { Length = KPeriod },
D = { Length = DPeriod }
};
StartProtection(
takeProfit: new Unit(TakeProfitPct, UnitTypes.Percent),
stopLoss: new Unit(StopLossPct, UnitTypes.Percent));
var subscription = SubscribeCandles(CandleType);
subscription.BindEx(stoch, ProcessCandle).Start();
}
private void ProcessCandle(ICandleMessage candle, IIndicatorValue stochValue)
{
if (candle.State != CandleStates.Finished)
return;
if (!stochValue.IsFinal || !stochValue.IsFormed)
return;
var stoch = (IStochasticOscillatorValue)stochValue;
if (stoch.K is not decimal k || stoch.D is not decimal d)
return;
var signal = 0;
if (_prevK.HasValue && _prevD.HasValue)
{
if (_prevK <= _prevD && k > d)
signal = 1;
else if (_prevK >= _prevD && k < d)
signal = -1;
}
_prevK = k;
_prevD = d;
if (signal == 0)
return;
if (signal > 0 && Position <= 0)
{
if (Position < 0)
BuyMarket();
BuyMarket();
_entryPrice = candle.ClosePrice;
}
else if (signal < 0 && Position >= 0)
{
if (Position > 0)
SellMarket();
SellMarket();
_entryPrice = candle.ClosePrice;
}
}
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_prevK = null;
_prevD = null;
_entryPrice = 0m;
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")
from System import TimeSpan
from StockSharp.Messages import DataType, CandleStates, Unit, UnitTypes
from StockSharp.Algo.Indicators import StochasticOscillator
from StockSharp.Algo.Strategies import Strategy
class labouchere_ea_strategy(Strategy):
"""
Labouchere strategy using Stochastic K/D crossover for entry signals.
Uses StartProtection for percentage-based SL/TP.
"""
def __init__(self):
super(labouchere_ea_strategy, self).__init__()
self._k_period = self.Param("KPeriod", 10) \
.SetDisplay("K Period", "Stochastic %K period", "Indicator")
self._d_period = self.Param("DPeriod", 3) \
.SetDisplay("D Period", "Stochastic %D period", "Indicator")
self._stop_loss_pct = self.Param("StopLossPct", 1.0) \
.SetDisplay("Stop Loss %", "Stop loss percent", "Risk")
self._take_profit_pct = self.Param("TakeProfitPct", 1.5) \
.SetDisplay("Take Profit %", "Take profit percent", "Risk")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))) \
.SetDisplay("Candle Type", "Type of candles used", "General")
self._prev_k = None
self._prev_d = None
self._entry_price = 0.0
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(labouchere_ea_strategy, self).OnReseted()
self._prev_k = None
self._prev_d = None
self._entry_price = 0.0
def OnStarted2(self, time):
super(labouchere_ea_strategy, self).OnStarted2(time)
stoch = StochasticOscillator()
stoch.K.Length = self._k_period.Value
stoch.D.Length = self._d_period.Value
self.StartProtection(
Unit(self._take_profit_pct.Value, UnitTypes.Percent),
Unit(self._stop_loss_pct.Value, UnitTypes.Percent))
subscription = self.SubscribeCandles(self.candle_type)
subscription.BindEx(stoch, self._process_candle).Start()
def _process_candle(self, candle, stoch_value):
if candle.State != CandleStates.Finished:
return
if not stoch_value.IsFormed:
return
k = stoch_value.K
d = stoch_value.D
if k is None or d is None:
return
k = float(k)
d = float(d)
signal = 0
if self._prev_k is not None and self._prev_d is not None:
if self._prev_k <= self._prev_d and k > d:
signal = 1
elif self._prev_k >= self._prev_d and k < d:
signal = -1
self._prev_k = k
self._prev_d = d
if signal == 0:
return
if signal > 0 and self.Position <= 0:
if self.Position < 0:
self.BuyMarket()
self.BuyMarket()
self._entry_price = float(candle.ClosePrice)
elif signal < 0 and self.Position >= 0:
if self.Position > 0:
self.SellMarket()
self.SellMarket()
self._entry_price = float(candle.ClosePrice)
def CreateClone(self):
return labouchere_ea_strategy()