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MACD 均值回归策略

该方法关注 MACD 柱状图相对于其平均值的偏离程度。极端的柱状图往往在动能消散后回归，通过监控 MACD 与信号线的差距来捕捉过度的走势。

测试表明年均收益约为 67%，该策略在股票市场表现最佳。

当柱状图低于均值 DeviationMultiplier 倍标准差时做多；当柱状图高于均值同样倍数时做空。柱状图回到平均水平即平仓。

此策略适合愿意反转动量极端的交易者，并以价格百分比止损，防止趋势继续扩展。

详细信息

  • 入场条件:
    • 做多: MACD Histogram < Avg - DeviationMultiplier * StdDev
    • 做空: MACD Histogram > Avg + DeviationMultiplier * StdDev
  • 多空方向: 双向
  • 退出条件:
    • 做多: Exit when Histogram > Avg
    • 做空: Exit when Histogram < Avg
  • 止损: 是
  • 默认值:
    • FastMacdPeriod = 12
    • SlowMacdPeriod = 26
    • SignalPeriod = 9
    • AveragePeriod = 20
    • DeviationMultiplier = 2m
    • CandleType = TimeSpan.FromMinutes(5)
  • 筛选条件:
    • 类别: 均值回归
    • 方向: 双向
    • 指标: MACD
    • 止损: 是
    • 复杂度: 中等
    • 时间框架: 日内
    • 季节性: 否
    • 神经网络: 否
    • 背离: 否
    • 风险等级: 中等
namespace StockSharp.Samples.Strategies;

using System;
using System.Collections.Generic;

using Ecng.Common;

using StockSharp.Algo;
using StockSharp.Algo.Candles;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;

/// <summary>
/// MACD Histogram Mean Reversion strategy.
/// This strategy enters positions when MACD Histogram is significantly below or above its average value.
/// </summary>
public class MacdMeanReversionStrategy : Strategy
{
	private readonly StrategyParam<int> _fastMacdPeriod;
	private readonly StrategyParam<int> _slowMacdPeriod;
	private readonly StrategyParam<int> _signalPeriod;
	private readonly StrategyParam<int> _averagePeriod;
	private readonly StrategyParam<decimal> _deviationMultiplier;
	private readonly StrategyParam<DataType> _candleType;
	private readonly StrategyParam<decimal> _stopLossPercent;

	private decimal _prevMacdHist;
	private decimal _avgMacdHist;
	private decimal _stdDevMacdHist;
	private decimal _sumMacdHist;
	private decimal _sumSquaresMacdHist;
	private int _count;
	private readonly Queue<decimal> _macdHistValues = [];

	/// <summary>
	/// Fast EMA period for MACD.
	/// </summary>
	public int FastMacdPeriod
	{
		get => _fastMacdPeriod.Value;
		set => _fastMacdPeriod.Value = value;
	}

	/// <summary>
	/// Slow EMA period for MACD.
	/// </summary>
	public int SlowMacdPeriod
	{
		get => _slowMacdPeriod.Value;
		set => _slowMacdPeriod.Value = value;
	}

	/// <summary>
	/// Signal line period for MACD.
	/// </summary>
	public int SignalPeriod
	{
		get => _signalPeriod.Value;
		set => _signalPeriod.Value = value;
	}

	/// <summary>
	/// Period for calculating mean and standard deviation of MACD Histogram.
	/// </summary>
	public int AveragePeriod
	{
		get => _averagePeriod.Value;
		set => _averagePeriod.Value = value;
	}

	/// <summary>
	/// Deviation multiplier for entry signals.
	/// </summary>
	public decimal DeviationMultiplier
	{
		get => _deviationMultiplier.Value;
		set => _deviationMultiplier.Value = value;
	}

	/// <summary>
	/// Candle type.
	/// </summary>
	public DataType CandleType
	{
		get => _candleType.Value;
		set => _candleType.Value = value;
	}

	/// <summary>
	/// Stop-loss percentage.
	/// </summary>
	public decimal StopLossPercent
	{
		get => _stopLossPercent.Value;
		set => _stopLossPercent.Value = value;
	}

	/// <summary>
	/// Constructor.
	/// </summary>
	public MacdMeanReversionStrategy()
	{
		_fastMacdPeriod = Param(nameof(FastMacdPeriod), 12)
			.SetGreaterThanZero()
			
			.SetOptimize(8, 16, 4)
			.SetDisplay("Fast EMA Period", "Fast EMA period for MACD", "Indicators");

		_slowMacdPeriod = Param(nameof(SlowMacdPeriod), 26)
			.SetGreaterThanZero()
			
			.SetOptimize(20, 30, 5)
			.SetDisplay("Slow EMA Period", "Slow EMA period for MACD", "Indicators");

		_signalPeriod = Param(nameof(SignalPeriod), 9)
			.SetGreaterThanZero()
			
			.SetOptimize(5, 13, 4)
			.SetDisplay("Signal Period", "Signal line period for MACD", "Indicators");

		_averagePeriod = Param(nameof(AveragePeriod), 20)
			.SetGreaterThanZero()
			
			.SetOptimize(10, 50, 10)
			.SetDisplay("Average Period", "Period for calculating MACD Histogram average", "Settings");

		_deviationMultiplier = Param(nameof(DeviationMultiplier), 2m)
			.SetGreaterThanZero()
			
			.SetOptimize(1.5m, 3m, 0.5m)
			.SetDisplay("Deviation Multiplier", "Multiplier for standard deviation", "Settings");

		_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(5).TimeFrame())
			.SetDisplay("Candle Type", "Type of candles to use", "General");

		_stopLossPercent = Param(nameof(StopLossPercent), 2m)
			.SetGreaterThanZero()
			
			.SetOptimize(1m, 3m, 0.5m)
			.SetDisplay("Stop Loss %", "Stop loss as percentage of entry price", "Risk Management");
	}

	/// <inheritdoc />
	public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
	{
		return [(Security, CandleType)];
	}

	/// <inheritdoc />
	protected override void OnReseted()
	{
		base.OnReseted();
		_prevMacdHist = 0;
		_avgMacdHist = 0;
		_stdDevMacdHist = 0;
		_sumMacdHist = 0;
		_sumSquaresMacdHist = 0;
		_count = 0;
		_macdHistValues.Clear();
	}

	/// <inheritdoc />
	protected override void OnStarted2(DateTime time)
	{
		// Reset variables

		// Create MACD indicator
		var macd = new MovingAverageConvergenceDivergenceHistogram
		{
			Macd =
			{
				ShortMa = { Length = FastMacdPeriod },
				LongMa = { Length = SlowMacdPeriod },
			},
			SignalMa = { Length = SignalPeriod }
		};

		var macdHistogram = new MovingAverageConvergenceDivergenceHistogram(macd.Macd, new());

		// Create subscription and bind indicator
		var subscription = SubscribeCandles(CandleType);
		subscription
			.BindEx(macdHistogram, ProcessCandle)
			.Start();

		// Setup chart visualization
		var area = CreateChartArea();
		if (area != null)
		{
			DrawCandles(area, subscription);
			DrawIndicator(area, macd);
			DrawIndicator(area, macdHistogram);
			DrawOwnTrades(area);
		}

		// Enable position protection
		StartProtection(
			takeProfit: new Unit(0m), // We'll manage exits ourselves based on MACD Histogram
			stopLoss: new Unit(StopLossPercent, UnitTypes.Percent)
		);

		base.OnStarted2(time);
	}

	private void ProcessCandle(ICandleMessage candle, IIndicatorValue macdValue)
	{
		// Skip unfinished candles
		if (candle.State != CandleStates.Finished)
			return;

		// Check if strategy is ready to trade
		if (!IsFormedAndOnlineAndAllowTrading())
			return;

		// Extract MACD Histogram value
		var macdTyped = (MovingAverageConvergenceDivergenceHistogramValue)macdValue;
		if (macdTyped.Macd is not decimal macd || macdTyped.Signal is not decimal signal)
		{
			return;
		}

		// Update MACD Histogram statistics
		UpdateMacdHistStatistics(macd);

		// Save current MACD Histogram for next iteration
		_prevMacdHist = macd;

		// If we don't have enough data yet for statistics
		if (_count < AveragePeriod)
			return;

		// Check for entry conditions
		if (Position == 0)
		{
			// Long entry - MACD Histogram is significantly below its average
			if (macd < _avgMacdHist - DeviationMultiplier * _stdDevMacdHist)
			{
				BuyMarket(Volume);
				LogInfo($"Long entry: MACD Hist = {macd}, Avg = {_avgMacdHist}, StdDev = {_stdDevMacdHist}");
			}
			// Short entry - MACD Histogram is significantly above its average
			else if (macd > _avgMacdHist + DeviationMultiplier * _stdDevMacdHist)
			{
				SellMarket(Volume);
				LogInfo($"Short entry: MACD Hist = {macd}, Avg = {_avgMacdHist}, StdDev = {_stdDevMacdHist}");
			}
		}
		// Check for exit conditions
		else if (Position > 0) // Long position
		{
			if (macd > _avgMacdHist)
			{
				ClosePosition();
				LogInfo($"Long exit: MACD Hist = {macd}, Avg = {_avgMacdHist}");
			}
		}
		else if (Position < 0) // Short position
		{
			if (macd < _avgMacdHist)
			{
				ClosePosition();
				LogInfo($"Short exit: MACD Hist = {macd}, Avg = {_avgMacdHist}");
			}
		}
	}

	private void UpdateMacdHistStatistics(decimal currentMacdHist)
	{
		// Add current value to the queue
		_macdHistValues.Enqueue(currentMacdHist);
		_sumMacdHist += currentMacdHist;
		_sumSquaresMacdHist += currentMacdHist * currentMacdHist;
		_count++;

		// If queue is larger than period, remove oldest value
		if (_macdHistValues.Count > AveragePeriod)
		{
			var oldestMacdHist = _macdHistValues.Dequeue();
			_sumMacdHist -= oldestMacdHist;
			_sumSquaresMacdHist -= oldestMacdHist * oldestMacdHist;
			_count--;
		}

		// Calculate average and standard deviation
		if (_count > 0)
		{
			_avgMacdHist = _sumMacdHist / _count;
			
			if (_count > 1)
			{
				var variance = (_sumSquaresMacdHist - (_sumMacdHist * _sumMacdHist) / _count) / (_count - 1);
				_stdDevMacdHist = variance <= 0 ? 0 : (decimal)Math.Sqrt((double)variance);
			}
			else
			{
				_stdDevMacdHist = 0;
			}
		}
	}
}