在 GitHub 上查看
AG 双重 MACD 策略
概述
本策略是 MetaTrader 4 专家顾问 AG.mq4 的 StockSharp 移植版。机器人同时计算两组不同参数的 MACD 指标:第一组作为入场触发器,第二组放大后的 MACD 用来过滤趋势并控制离场。策略仅在 K 线收盘后评估信号,从而还原原始 EA 的行为。
交易逻辑
- 指标设置
- 主 MACD:快速 EMA =
FastEmaLength、慢速 EMA = SlowEmaLength、信号 SMA = SignalSmaLength。
- 次 MACD:快速 EMA =
SlowEmaLength * 2、慢速 EMA = FastEmaLength * 2、信号 SMA = SignalSmaLength * 2。
- 做多条件
- 主 MACD 主线位于信号线之上。
- 主 MACD 信号线小于 0。
- 次 MACD 主线位于信号线之上。
- 次 MACD 信号线小于 0。
- 做空条件
- 主 MACD 主线位于信号线之下。
- 主 MACD 信号线大于 0。
- 次 MACD 主线位于信号线之下。
- 次 MACD 信号线大于 0。
- 离场规则
- 当次 MACD 变为看空且主 MACD 信号线仍大于 0 时平掉多头。
- 当次 MACD 变为看多且主 MACD 信号线仍小于 0 时平掉空头。
- 仅处理已完成的 K 线,忽略未收盘数据以避免重绘。
仓位管理
- 所有交易均使用
OrderVolume 指定的固定手数,以市价单执行。
MaxOpenOrders 对应原始输入 ORDER,限制活动订单与持仓的总数;设为 0 即取消限制。
- 在启动时调用
StartProtection(),让 StockSharp 风控模块监控敞口。
参数
| 名称 |
说明 |
OrderVolume |
开仓和加仓使用的基础手数。 |
FastEmaLength |
主 MACD 的快速 EMA 周期。 |
SlowEmaLength |
主 MACD 的慢速 EMA 周期。 |
SignalSmaLength |
两个 MACD 共用的信号线平滑周期。 |
MaxOpenOrders |
活动订单和持仓的最大数量,0 表示不限。 |
CandleType |
构建指标所使用的 K 线类型或周期。 |
备注
- 次 MACD 的快、慢周期保持与原始 EA 相同的顺序,即使快速周期大于慢速周期也不会调整,以确保行为一致。
- 策略不会挂出挂单,信号触发后立即以市价进出场。
- 未额外添加止损或止盈,完全依赖信号反转离场,与原版一致。
using System;
using System.Collections.Generic;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
/// <summary>
/// AG MACD Dual strategy - MACD histogram crossover with EMA trend filter.
/// Buys when MACD histogram crosses above zero while price is above EMA.
/// Sells when MACD histogram crosses below zero while price is below EMA.
/// </summary>
public class AgMacdDualStrategy : Strategy
{
private readonly StrategyParam<int> _emaPeriod;
private readonly StrategyParam<DataType> _candleType;
private decimal _prevMacd;
private decimal _prevSignal;
private bool _hasPrev;
private decimal _currentEma;
public int EmaPeriod { get => _emaPeriod.Value; set => _emaPeriod.Value = value; }
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public AgMacdDualStrategy()
{
_emaPeriod = Param(nameof(EmaPeriod), 50)
.SetDisplay("EMA Period", "EMA trend filter", "Indicators");
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(4).TimeFrame())
.SetDisplay("Candle Type", "Candle timeframe", "General");
}
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities() => [(Security, CandleType)];
protected override void OnReseted() { base.OnReseted(); _prevMacd = 0m; _prevSignal = 0m; _hasPrev = false; _currentEma = 0m; }
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_hasPrev = false;
var macd = new MovingAverageConvergenceDivergenceSignal();
var ema = new ExponentialMovingAverage { Length = EmaPeriod };
var subscription = SubscribeCandles(CandleType);
subscription
.BindEx(macd, ProcessMacd)
.Bind(ema, ProcessEma)
.Start();
}
private void ProcessEma(ICandleMessage candle, decimal ema)
{
if (candle.State != CandleStates.Finished)
return;
_currentEma = ema;
}
private void ProcessMacd(ICandleMessage candle, IIndicatorValue value)
{
if (candle.State != CandleStates.Finished)
return;
if (!value.IsFinal || value.IsEmpty)
return;
var macdVal = value as MovingAverageConvergenceDivergenceSignalValue;
if (macdVal == null)
return;
var macdLine = macdVal.Macd;
var signalLine = macdVal.Signal;
if (macdLine == null || signalLine == null)
return;
var histogram = macdLine.Value - signalLine.Value;
if (!_hasPrev)
{
_prevMacd = macdLine.Value;
_prevSignal = signalLine.Value;
_hasPrev = true;
return;
}
var prevHist = _prevMacd - _prevSignal;
var close = candle.ClosePrice;
if (prevHist <= 0 && histogram > 0 && close > _currentEma && Position <= 0)
{
if (Position < 0)
BuyMarket();
BuyMarket();
}
else if (prevHist >= 0 && histogram < 0 && close < _currentEma && Position >= 0)
{
if (Position > 0)
SellMarket();
SellMarket();
}
_prevMacd = macdLine.Value;
_prevSignal = signalLine.Value;
}
}
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 MovingAverageConvergenceDivergenceSignal, ExponentialMovingAverage
from StockSharp.Algo.Strategies import Strategy
class ag_macd_dual_strategy(Strategy):
def __init__(self):
super(ag_macd_dual_strategy, self).__init__()
self._ema_period = self.Param("EmaPeriod", 50).SetDisplay("EMA Period", "EMA trend filter", "Indicators")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))).SetDisplay("Candle Type", "Candle timeframe", "General")
self._prev_macd = 0.0; self._prev_signal = 0.0; self._has_prev = False; self._current_ema = 0.0
@property
def ema_period(self): return self._ema_period.Value
@property
def candle_type(self): return self._candle_type.Value
def OnReseted(self):
super(ag_macd_dual_strategy, self).OnReseted()
self._prev_macd = 0.0; self._prev_signal = 0.0; self._has_prev = False; self._current_ema = 0.0
def OnStarted2(self, time):
super(ag_macd_dual_strategy, self).OnStarted2(time)
self._has_prev = False
macd = MovingAverageConvergenceDivergenceSignal()
ema = ExponentialMovingAverage(); ema.Length = self.ema_period
sub = self.SubscribeCandles(self.candle_type)
sub.BindEx(macd, self.process_macd).Bind(ema, self.process_ema).Start()
def process_ema(self, candle, ema):
if candle.State != CandleStates.Finished: return
self._current_ema = float(ema)
def process_macd(self, candle, value):
if candle.State != CandleStates.Finished: return
if not value.IsFinal or value.IsEmpty: return
if value.Macd is None or value.Signal is None: return
ml = float(value.Macd); sl = float(value.Signal); hist = ml - sl
if not self._has_prev: self._prev_macd = ml; self._prev_signal = sl; self._has_prev = True; return
prev_hist = self._prev_macd - self._prev_signal; close = float(candle.ClosePrice)
if prev_hist <= 0 and hist > 0 and close > self._current_ema and self.Position <= 0:
if self.Position < 0: self.BuyMarket()
self.BuyMarket()
elif prev_hist >= 0 and hist < 0 and close < self._current_ema and self.Position >= 0:
if self.Position > 0: self.SellMarket()
self.SellMarket()
self._prev_macd = ml; self._prev_signal = sl
def CreateClone(self): return ag_macd_dual_strategy()