Modelo de Momentum Ponderado por Gamma para Futuros BTC
La estrategia calcula un precio promedio ponderado por Gamma (GWAP) para capturar el momentum en futuros de BTC. Se abren posiciones largas cuando el precio permanece por encima del GWAP y los tres últimos cierres suben consecutivamente. Se toman posiciones cortas cuando el precio está por debajo del GWAP y los tres últimos cierres caen consecutivamente.
Detalles
- Criterios de entrada:
- Largo: Cierre por encima del GWAP y los tres últimos cierres en ascenso.
- Corto: Cierre por debajo del GWAP y los tres últimos cierres en descenso.
- Largo/Corto: Ambos lados.
- Criterios de salida: Señal inversa.
- Stops: Ninguno.
- Valores predeterminados:
Length= 60GammaFactor= 0.75
- Filtros:
- Categoría: Momentum
- Dirección: Ambos
- Indicadores: GWAP
- Stops: Ninguno
- Complejidad: Bajo
- Marco temporal: 1m
- Estacionalidad: No
- Redes neuronales: No
- Divergencia: No
- Nivel de riesgo: Medio
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;
/// <summary>
/// BTC Future Gamma-Weighted Momentum Model strategy.
/// Uses an exponentially-weighted average price (GWAP) as trend filter
/// and EMA crossover for entry signals.
/// </summary>
public class BtcFutureGammaWeightedMomentumModelStrategy : 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 BtcFutureGammaWeightedMomentumModelStrategy()
{
_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");
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_prevFastEma = 0m;
_prevSlowEma = 0m;
}
/// <inheritdoc />
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;
}
// Buy on golden cross
if (_prevFastEma <= _prevSlowEma && fastEmaValue > slowEmaValue && Position <= 0)
{
BuyMarket();
}
// Sell on death cross
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 btc_future_gamma_weighted_momentum_model_strategy(Strategy):
def __init__(self):
super(btc_future_gamma_weighted_momentum_model_strategy, self).__init__()
self._fast_ema_period = self.Param("FastEmaPeriod", 120) .SetDisplay("Fast EMA", "Fast EMA period", "Indicators")
self._slow_ema_period = self.Param("SlowEmaPeriod", 450) .SetDisplay("Slow EMA", "Slow EMA period", "Indicators")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(1))) .SetDisplay("Candle Type", "Type of candles to use", "General")
self._prev_fast_ema = 0.0
self._prev_slow_ema = 0.0
@property
def fast_ema_period(self):
return self._fast_ema_period.Value
@property
def slow_ema_period(self):
return self._slow_ema_period.Value
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(btc_future_gamma_weighted_momentum_model_strategy, self).OnReseted()
self._prev_fast_ema = 0.0
self._prev_slow_ema = 0.0
def OnStarted2(self, time):
super(btc_future_gamma_weighted_momentum_model_strategy, self).OnStarted2(time)
fast_ema = ExponentialMovingAverage()
fast_ema.Length = self.fast_ema_period
slow_ema = ExponentialMovingAverage()
slow_ema.Length = self.slow_ema_period
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(fast_ema, slow_ema, self.OnProcess).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawIndicator(area, fast_ema)
self.DrawIndicator(area, slow_ema)
self.DrawOwnTrades(area)
def OnProcess(self, candle, fast_ema_value, slow_ema_value):
if candle.State != CandleStates.Finished:
return
if self._prev_fast_ema == 0 or self._prev_slow_ema == 0:
self._prev_fast_ema = float(fast_ema_value)
self._prev_slow_ema = float(slow_ema_value)
return
if self._prev_fast_ema <= self._prev_slow_ema and fast_ema_value > slow_ema_value and self.Position <= 0:
self.BuyMarket()
elif self._prev_fast_ema >= self._prev_slow_ema and fast_ema_value < slow_ema_value and self.Position >= 0:
self.SellMarket()
self._prev_fast_ema = float(fast_ema_value)
self._prev_slow_ema = float(slow_ema_value)
def CreateClone(self):
return btc_future_gamma_weighted_momentum_model_strategy()