Color Zerolag X10 MA 策略
该策略是 MetaTrader 示例 Exp_ColorZerolagX10MA.mq5 的简化移植版本。它利用零滞后指数移动平均线 (Zero Lag EMA) 来检测斜率变化。当均线在连续两根柱子下降后转而向上时,策略会开多或反手做多;反之,当均线在上升后转而向下时,策略会开空。
原始系统依赖由十条平滑均线构成的复杂指标。此处使用 StockSharp 内置的 ZeroLagExponentialMovingAverage 代替,使实现更加简洁。策略在选定的K线时间框架上运行,并可通过参数启用或禁用各个动作(开/平多空)。
细节
- 入场条件:
- 多头:
ZLEMA[t-2] > ZLEMA[t-1]且ZLEMA[t] > ZLEMA[t-1]。 - 空头:
ZLEMA[t-2] < ZLEMA[t-1]且ZLEMA[t] < ZLEMA[t-1]。
- 多头:
- 多空方向:双向。
- 出场条件:
- 当出现空头信号且启用
BuyPosClose时平多。 - 当出现多头信号且启用
SellPosClose时平空。
- 当出现空头信号且启用
- 止损:默认无,依靠反向信号退出。
- 默认值:
Length= 20。CandleType= 4 小时时间框架。- 所有动作标志 (
BuyPosOpen,SellPosOpen,BuyPosClose,SellPosClose) 启用。
- 过滤器:
- 类别:趋势跟随
- 方向:双向
- 指标:单一
- 止损:否
- 复杂度:简单
- 时间框架:中期
- 季节性:否
- 神经网络:否
- 背离:否
- 风险等级:中等
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>
/// Trend detection strategy based on the slope of a zero lag moving average.
/// </summary>
public class ColorZerolagX10MaStrategy : Strategy
{
private readonly StrategyParam<int> _length;
private readonly StrategyParam<DataType> _candleType;
private decimal _prev1;
private decimal _prev2;
private int _count;
public int Length { get => _length.Value; set => _length.Value = value; }
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public ColorZerolagX10MaStrategy()
{
_length = Param(nameof(Length), 20)
.SetDisplay("Length", "MA length", "Indicators");
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(1).TimeFrame())
.SetDisplay("Candle Type", "Candle timeframe", "General");
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
=> [(Security, CandleType)];
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_prev1 = 0;
_prev2 = 0;
_count = 0;
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
var zlma = new ZeroLagExponentialMovingAverage { Length = Length };
SubscribeCandles(CandleType)
.Bind(zlma, ProcessCandle)
.Start();
}
private void ProcessCandle(ICandleMessage candle, decimal ma)
{
if (candle.State != CandleStates.Finished)
return;
_count++;
if (_count < 3)
{
_prev2 = _prev1;
_prev1 = ma;
return;
}
// Detect trend turn via slope direction change
var trendUp = _prev1 < _prev2 && ma > _prev1;
var trendDown = _prev1 > _prev2 && ma < _prev1;
if (trendUp && Position <= 0)
{
if (Position < 0) BuyMarket();
BuyMarket();
}
else if (trendDown && Position >= 0)
{
if (Position > 0) SellMarket();
SellMarket();
}
_prev2 = _prev1;
_prev1 = ma;
}
}
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 ZeroLagExponentialMovingAverage
from StockSharp.Algo.Strategies import Strategy
class color_zerolag_x10_ma_strategy(Strategy):
"""
Trend detection strategy based on the slope of a zero lag moving average.
"""
def __init__(self):
super(color_zerolag_x10_ma_strategy, self).__init__()
self._length = self.Param("Length", 20) \
.SetDisplay("Length", "MA length", "Indicators")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(1))) \
.SetDisplay("Candle Type", "Candle timeframe", "General")
self._prev1 = 0.0
self._prev2 = 0.0
self._count = 0
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(color_zerolag_x10_ma_strategy, self).OnReseted()
self._prev1 = 0.0
self._prev2 = 0.0
self._count = 0
def OnStarted2(self, time):
super(color_zerolag_x10_ma_strategy, self).OnStarted2(time)
zlma = ZeroLagExponentialMovingAverage()
zlma.Length = self._length.Value
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(zlma, self.on_process).Start()
def on_process(self, candle, ma_val):
if candle.State != CandleStates.Finished:
return
self._count += 1
if self._count < 3:
self._prev2 = self._prev1
self._prev1 = ma_val
return
trend_up = self._prev1 < self._prev2 and ma_val > self._prev1
trend_down = self._prev1 > self._prev2 and ma_val < self._prev1
if trend_up and self.Position <= 0:
if self.Position < 0:
self.BuyMarket()
self.BuyMarket()
elif trend_down and self.Position >= 0:
if self.Position > 0:
self.SellMarket()
self.SellMarket()
self._prev2 = self._prev1
self._prev1 = ma_val
def CreateClone(self):
return color_zerolag_x10_ma_strategy()