Zero-lag Volatility-Breakout EMA Trend Strategy
Стратегия пробоя волатильности на основе нулелаговой разницы EMA и полос Боллинджера с фильтром тренда EMA. При желании удерживает позицию до противоположного сигнала.
Детали
- Критерии входа: пересечение dif выше верхней полосы с фильтром наклона EMA.
- Длинные/короткие: оба направления.
- Критерии выхода: опционально при пересечении средней полосы.
- Стопы: нет.
- Значения по умолчанию:
EmaLength= 200StdMultiplier= 2mUseBinary= trueCandleType= TimeSpan.FromMinutes(5)
- Фильтры:
- Категория: Тренд
- Направление: Оба
- Индикаторы: EMA, Bollinger Bands
- Стопы: Нет
- Сложность: Средняя
- Таймфрейм: Внутридневной (5m)
- Сезонность: Нет
- Нейросети: Нет
- Дивергенция: Нет
- Уровень риска: Средний
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>
/// Zero-lag volatility breakout strategy with EMA trend filter.
/// Uses Bollinger Bands on price-EMA divergence to detect breakouts.
/// </summary>
public class ZeroLagVolatilityBreakoutEmaTrendStrategy : Strategy
{
private readonly StrategyParam<int> _emaLength;
private readonly StrategyParam<decimal> _stdMultiplier;
private readonly StrategyParam<bool> _useBinary;
private readonly StrategyParam<DataType> _candleType;
private decimal _prevEma;
private decimal _prevDif;
private bool _hasPrev;
private readonly List<decimal> _difs = new();
public int EmaLength { get => _emaLength.Value; set => _emaLength.Value = value; }
public decimal StdMultiplier { get => _stdMultiplier.Value; set => _stdMultiplier.Value = value; }
public bool UseBinary { get => _useBinary.Value; set => _useBinary.Value = value; }
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public ZeroLagVolatilityBreakoutEmaTrendStrategy()
{
_emaLength = Param(nameof(EmaLength), 50).SetDisplay("EMA Length", "Base EMA length", "Indicators");
_stdMultiplier = Param(nameof(StdMultiplier), 2m).SetDisplay("Std Mult", "Standard deviation multiplier", "Indicators");
_useBinary = Param(nameof(UseBinary), true).SetDisplay("Use Binary", "Hold until opposite signal", "General");
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(1).TimeFrame()).SetDisplay("Candle Type", "Candle timeframe", "General");
}
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
protected override void OnReseted()
{
base.OnReseted();
_prevEma = 0;
_prevDif = 0;
_hasPrev = false;
_difs.Clear();
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
var ema = new ExponentialMovingAverage { Length = EmaLength };
_prevEma = 0;
_prevDif = 0;
_hasPrev = false;
_difs.Clear();
var subscription = SubscribeCandles(CandleType);
subscription.Bind(ema, ProcessCandle).Start();
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawIndicator(area, ema);
DrawOwnTrades(area);
}
}
private void ProcessCandle(ICandleMessage candle, decimal emaValue)
{
if (candle.State != CandleStates.Finished)
return;
var hJumper = Math.Max(candle.ClosePrice, emaValue);
var lJumper = Math.Min(candle.ClosePrice, emaValue);
var dif = lJumper == 0 ? 0 : (hJumper / lJumper) - 1m;
_difs.Add(dif);
if (_difs.Count > EmaLength + 10)
_difs.RemoveAt(0);
if (_difs.Count < 20)
{
_prevEma = emaValue;
_prevDif = dif;
_hasPrev = true;
return;
}
// Compute Bollinger-like bands on dif values
var lookback = Math.Min(_difs.Count, EmaLength);
var recent = _difs.Skip(_difs.Count - lookback).ToList();
var mean = recent.Average();
var sumSq = recent.Sum(v => (v - mean) * (v - mean));
var std = (decimal)Math.Sqrt((double)(sumSq / lookback));
var bbu = mean + std * StdMultiplier;
var bbm = mean;
if (!_hasPrev)
{
_prevDif = dif;
_prevEma = emaValue;
_hasPrev = true;
return;
}
var sigEnter = _prevDif <= bbu && dif > bbu;
var sigExit = dif < bbm;
var enterLong = sigEnter && emaValue > _prevEma;
var enterShort = sigEnter && emaValue < _prevEma;
if (enterLong && Position <= 0)
{
BuyMarket();
}
else if (enterShort && Position >= 0)
{
SellMarket();
}
else if (!UseBinary && sigExit)
{
if (Position > 0)
SellMarket();
else if (Position < 0)
BuyMarket();
}
_prevDif = dif;
_prevEma = emaValue;
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")
from System import TimeSpan, Math
from StockSharp.Messages import DataType, CandleStates
from StockSharp.Algo.Indicators import ExponentialMovingAverage
from StockSharp.Algo.Strategies import Strategy
class zero_lag_volatility_breakout_ema_trend_strategy(Strategy):
def __init__(self):
super(zero_lag_volatility_breakout_ema_trend_strategy, self).__init__()
self._ema_length = self.Param("EmaLength", 50) \
.SetDisplay("EMA Length", "Base EMA length", "Indicators")
self._std_multiplier = self.Param("StdMultiplier", 2.0) \
.SetDisplay("Std Mult", "Standard deviation multiplier", "Indicators")
self._use_binary = self.Param("UseBinary", True) \
.SetDisplay("Use Binary", "Hold until opposite signal", "General")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(1))) \
.SetDisplay("Candle Type", "Candle timeframe", "General")
self._difs = []
self._prev_ema = 0.0
self._prev_dif = 0.0
self._has_prev = False
@property
def ema_length(self):
return self._ema_length.Value
@property
def std_multiplier(self):
return self._std_multiplier.Value
@property
def use_binary(self):
return self._use_binary.Value
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(zero_lag_volatility_breakout_ema_trend_strategy, self).OnReseted()
self._difs = []
self._prev_ema = 0.0
self._prev_dif = 0.0
self._has_prev = False
def OnStarted2(self, time):
super(zero_lag_volatility_breakout_ema_trend_strategy, self).OnStarted2(time)
ema = ExponentialMovingAverage()
ema.Length = self.ema_length
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(ema, self.on_process).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawIndicator(area, ema)
self.DrawOwnTrades(area)
def on_process(self, candle, ema_value):
if candle.State != CandleStates.Finished:
return
close = float(candle.ClosePrice)
ema_val = float(ema_value)
h_jumper = max(close, ema_val)
l_jumper = min(close, ema_val)
dif = 0.0 if l_jumper == 0 else (h_jumper / l_jumper) - 1.0
self._difs.append(dif)
el = int(self.ema_length)
while len(self._difs) > el + 10:
self._difs.pop(0)
if len(self._difs) < 20:
self._prev_ema = ema_val
self._prev_dif = dif
self._has_prev = True
return
lookback = min(len(self._difs), el)
recent = self._difs[-lookback:]
mean = sum(recent) / lookback
sum_sq = sum((v - mean) * (v - mean) for v in recent)
std = Math.Sqrt(float(sum_sq / lookback))
bbu = mean + std * float(self.std_multiplier)
bbm = mean
if not self._has_prev:
self._prev_dif = dif
self._prev_ema = ema_val
self._has_prev = True
return
sig_enter = self._prev_dif <= bbu and dif > bbu
sig_exit = dif < bbm
enter_long = sig_enter and ema_val > self._prev_ema
enter_short = sig_enter and ema_val < self._prev_ema
if enter_long and self.Position <= 0:
self.BuyMarket()
elif enter_short and self.Position >= 0:
self.SellMarket()
elif not self.use_binary and sig_exit:
if self.Position > 0:
self.SellMarket()
elif self.Position < 0:
self.BuyMarket()
self._prev_dif = dif
self._prev_ema = ema_val
def CreateClone(self):
return zero_lag_volatility_breakout_ema_trend_strategy()