Стратегия Mean Reversion V-F
Стратегия усредняет позицию до пяти слоев при падении цены ниже скользящей средней на заданные проценты. Выход выполняется по фиксированной цели прибыли или по трейлинг-стопу.
Детали
- Вход: Цена опускается ниже уровней отклонения от выбранной скользящей средней.
- Выход: Достижение цели прибыли или срабатывание трейлинг-стопа.
- Индикаторы: Скользящая средняя.
- Направление: Только лонг.
- Стопы: Тейк-профит и опциональный трейлинг.
using System;
using System.Linq;
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;
public class MeanReversionVFStrategy : Strategy
{
private readonly StrategyParam<int> _maLength;
private readonly StrategyParam<decimal> _deviation1;
private readonly StrategyParam<decimal> _takeProfitPercent;
private readonly StrategyParam<int> _signalCooldownBars;
private readonly StrategyParam<DataType> _candleType;
private WeightedMovingAverage _ma;
private decimal _entryPrice;
private decimal _prevClose;
private bool _hasPrevClose;
private int _barsFromSignal;
public int MaLength { get => _maLength.Value; set => _maLength.Value = value; }
public decimal Deviation1 { get => _deviation1.Value; set => _deviation1.Value = value; }
public decimal TakeProfitPercent { get => _takeProfitPercent.Value; set => _takeProfitPercent.Value = value; }
public int SignalCooldownBars { get => _signalCooldownBars.Value; set => _signalCooldownBars.Value = value; }
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public MeanReversionVFStrategy()
{
_maLength = Param(nameof(MaLength), 24)
.SetGreaterThanZero()
.SetDisplay("MA Length", "WMA length", "General");
_deviation1 = Param(nameof(Deviation1), 0.5m)
.SetGreaterThanZero()
.SetDisplay("Deviation %", "Lower deviation from WMA", "General");
_takeProfitPercent = Param(nameof(TakeProfitPercent), 4m)
.SetGreaterThanZero()
.SetDisplay("Take Profit %", "Target profit percent", "General");
_signalCooldownBars = Param(nameof(SignalCooldownBars), 80)
.SetGreaterThanZero()
.SetDisplay("Signal Cooldown Bars", "Minimum bars between entries", "General");
_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(5).TimeFrame())
.SetDisplay("Candle Type", "Candles timeframe", "General");
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_ma = null;
_entryPrice = 0m;
_prevClose = 0m;
_hasPrevClose = false;
_barsFromSignal = 0;
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_ma = new WeightedMovingAverage { Length = MaLength };
_entryPrice = 0;
_prevClose = 0m;
_hasPrevClose = false;
_barsFromSignal = SignalCooldownBars;
var subscription = SubscribeCandles(CandleType);
subscription
.Bind(_ma, ProcessCandle)
.Start();
}
private void ProcessCandle(ICandleMessage candle, decimal maValue)
{
if (candle.State != CandleStates.Finished)
return;
if (maValue == 0)
return;
var l1 = maValue * (1 - Deviation1 / 100m);
var close = candle.ClosePrice;
_barsFromSignal++;
if (Position > 0 && _entryPrice > 0)
{
var tpPrice = _entryPrice * (1 + TakeProfitPercent / 100m);
if (candle.HighPrice >= tpPrice)
{
SellMarket();
_entryPrice = 0;
return;
}
}
var crossedBelow = _hasPrevClose && _prevClose >= l1 && close < l1;
if (_barsFromSignal >= SignalCooldownBars && crossedBelow && Position <= 0)
{
BuyMarket();
_entryPrice = close;
_barsFromSignal = 0;
}
else if (close > maValue && Position > 0)
{
SellMarket();
_entryPrice = 0;
}
_prevClose = close;
_hasPrevClose = true;
}
}
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
from StockSharp.Algo.Indicators import WeightedMovingAverage
from StockSharp.Algo.Strategies import Strategy
class mean_reversion_vf_strategy(Strategy):
"""
Mean Reversion VF: WMA deviation entry with take profit.
"""
def __init__(self):
super(mean_reversion_vf_strategy, self).__init__()
self._ma_length = self.Param("MaLength", 24).SetDisplay("MA Length", "WMA length", "Indicators")
self._deviation = self.Param("Deviation1", 0.5).SetDisplay("Deviation %", "Lower deviation from WMA", "Signals")
self._take_profit_pct = self.Param("TakeProfitPercent", 4.0).SetDisplay("TP %", "Target profit percent", "Risk")
self._cooldown_bars = self.Param("SignalCooldownBars", 80).SetDisplay("Cooldown", "Min bars between entries", "Risk")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(5))).SetDisplay("Candle Type", "Candles", "General")
self._entry_price = 0.0
self._prev_close = 0.0
self._has_prev = False
self._bars_from_signal = 80
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(mean_reversion_vf_strategy, self).OnReseted()
self._entry_price = 0.0
self._prev_close = 0.0
self._has_prev = False
self._bars_from_signal = self._cooldown_bars.Value
def OnStarted2(self, time):
super(mean_reversion_vf_strategy, self).OnStarted2(time)
self._entry_price = 0.0
self._prev_close = 0.0
self._has_prev = False
self._bars_from_signal = self._cooldown_bars.Value
wma = WeightedMovingAverage()
wma.Length = self._ma_length.Value
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(wma, self._process_candle).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawIndicator(area, wma)
self.DrawOwnTrades(area)
def _process_candle(self, candle, ma_val):
if candle.State != CandleStates.Finished:
return
ma = float(ma_val)
if ma == 0:
return
close = float(candle.ClosePrice)
dev = float(self._deviation.Value)
l1 = ma * (1.0 - dev / 100.0)
self._bars_from_signal += 1
tp_pct = float(self._take_profit_pct.Value) / 100.0
if self.Position > 0 and self._entry_price > 0:
tp_price = self._entry_price * (1.0 + tp_pct)
if float(candle.HighPrice) >= tp_price:
self.SellMarket()
self._entry_price = 0.0
return
crossed_below = self._has_prev and self._prev_close >= l1 and close < l1
if self._bars_from_signal >= self._cooldown_bars.Value and crossed_below and self.Position <= 0:
self.BuyMarket()
self._entry_price = close
self._bars_from_signal = 0
elif close > ma and self.Position > 0:
self.SellMarket()
self._entry_price = 0.0
self._prev_close = close
self._has_prev = True
def CreateClone(self):
return mean_reversion_vf_strategy()