Estrategia de Filtro de Tendencia por Gradiente
La estrategia aplica suavizado exponencial triple para detectar la dirección de la tendencia. Las operaciones se abren cuando la diferencia del filtro cruza el cero y se cierran con señales opuestas.
using System;
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 GradientTrendFilterStrategy : Strategy
{
private readonly StrategyParam<int> _fastEmaPeriod;
private readonly StrategyParam<int> _slowEmaPeriod;
private readonly StrategyParam<DataType> _candleType;
private decimal _prevFastEma;
private decimal _prevSlowEma;
public int FastEmaPeriod { get => _fastEmaPeriod.Value; set => _fastEmaPeriod.Value = value; }
public int SlowEmaPeriod { get => _slowEmaPeriod.Value; set => _slowEmaPeriod.Value = value; }
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public GradientTrendFilterStrategy()
{
_fastEmaPeriod = Param(nameof(FastEmaPeriod), 120)
.SetGreaterThanZero()
.SetDisplay("Fast EMA", "Fast EMA period", "Indicators");
_slowEmaPeriod = Param(nameof(SlowEmaPeriod), 450)
.SetGreaterThanZero()
.SetDisplay("Slow EMA", "Slow EMA period", "Indicators");
_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(1).TimeFrame())
.SetDisplay("Candle Type", "Type of candles to use", "General");
}
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
protected override void OnReseted()
{
base.OnReseted();
_prevFastEma = 0m;
_prevSlowEma = 0m;
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
var fastEma = new ExponentialMovingAverage { Length = FastEmaPeriod };
var slowEma = new ExponentialMovingAverage { Length = SlowEmaPeriod };
var subscription = SubscribeCandles(CandleType);
subscription.Bind(fastEma, slowEma, ProcessCandle).Start();
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawIndicator(area, fastEma);
DrawIndicator(area, slowEma);
DrawOwnTrades(area);
}
}
private void ProcessCandle(ICandleMessage candle, decimal fastEmaValue, decimal slowEmaValue)
{
if (candle.State != CandleStates.Finished) return;
if (_prevFastEma == 0m || _prevSlowEma == 0m)
{
_prevFastEma = fastEmaValue;
_prevSlowEma = slowEmaValue;
return;
}
if (_prevFastEma <= _prevSlowEma && fastEmaValue > slowEmaValue && Position <= 0)
BuyMarket();
else if (_prevFastEma >= _prevSlowEma && fastEmaValue < slowEmaValue && Position >= 0)
SellMarket();
_prevFastEma = fastEmaValue;
_prevSlowEma = slowEmaValue;
}
}
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 ExponentialMovingAverage
from StockSharp.Algo.Strategies import Strategy
class gradient_trend_filter_strategy(Strategy):
"""
EMA crossover strategy.
Buys when fast EMA crosses above slow EMA, sells when it crosses below.
"""
def __init__(self):
super(gradient_trend_filter_strategy, self).__init__()
self._fast_period = self.Param("FastPeriod", 120) \
.SetDisplay("Fast Period", "Fast EMA period", "General")
self._slow_period = self.Param("SlowPeriod", 450) \
.SetDisplay("Slow Period", "Slow EMA period", "General")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(1))) \
.SetDisplay("Candle Type", "Candle timeframe", "General")
self._prev_fast = 0.0
self._prev_slow = 0.0
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(gradient_trend_filter_strategy, self).OnReseted()
self._prev_fast = 0.0
self._prev_slow = 0.0
def OnStarted2(self, time):
super(gradient_trend_filter_strategy, self).OnStarted2(time)
fast_ema = ExponentialMovingAverage()
fast_ema.Length = self._fast_period.Value
slow_ema = ExponentialMovingAverage()
slow_ema.Length = self._slow_period.Value
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(fast_ema, slow_ema, self._process_candle).Start()
def _process_candle(self, candle, fast_val, slow_val):
if candle.State != CandleStates.Finished:
return
fast = float(fast_val)
slow = float(slow_val)
if self._prev_fast != 0.0 and self._prev_slow != 0.0:
if self._prev_fast <= self._prev_slow and fast > slow:
if self.Position <= 0:
self.BuyMarket()
elif self._prev_fast >= self._prev_slow and fast < slow:
if self.Position >= 0:
self.SellMarket()
self._prev_fast = fast
self._prev_slow = slow
def CreateClone(self):
return gradient_trend_filter_strategy()