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MACD Hidden Markov Model戦略

MACD Hidden Markov Model戦略はMACD Hidden Markov Modelを中心に構築されています。

テストでは年平均リターン約61%が示されています。暗号通貨市場で最もよいパフォーマンスを発揮します。

MarkovがイントラデイデータでのトレンドTransitionを確認するとシグナルが発生します (5m)。この手法はアクティブなトレーダーに適しています。

ストップはATRの倍数とMacdFast、MacdSlowなどのパラメーターに依存します。リスクとリワードのバランスを取るためにこれらのデフォルト値を調整してください。

詳細

  • エントリー条件: インジケーター条件の実装を参照。
  • ロング/ショート: 両方向。
  • エグジット条件: 逆シグナルまたはストップロジック。
  • ストップ: はい、インジケーターベースの計算を使用。
  • デフォルト値:
    • MacdFast = 12
    • MacdSlow = 26
    • MacdSignal = 9
    • CandleType = TimeSpan.FromMinutes(5).TimeFrame()
    • HmmHistoryLength = 100
  • フィルター:
    • カテゴリ: トレンドフォロー
    • 方向: 両方
    • インジケーター: Markov
    • ストップ: はい
    • 複雑さ: 中級
    • 時間軸: イントラデイ (5m)
    • 季節性: いいえ
    • ニューラルネットワーク: はい
    • ダイバージェンス: いいえ
    • リスクレベル: 中
using System;
using System.Collections.Generic;

using Ecng.Common;
using Ecng.Serialization;

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

namespace StockSharp.Samples.Strategies;

/// <summary>
/// MACD strategy with Hidden Markov Model for state detection.
/// </summary>
public class MacdHmmStrategy : Strategy
{
	private readonly StrategyParam<int> _macdFast;
	private readonly StrategyParam<int> _macdSlow;
	private readonly StrategyParam<int> _macdSignal;
	private readonly StrategyParam<DataType> _candleType;
	private readonly StrategyParam<int> _hmmHistoryLength;
	private readonly StrategyParam<int> _atrPeriod;
	private readonly StrategyParam<decimal> _atrStopMultiplier;
	private readonly StrategyParam<int> _signalCooldownBars;

	private MovingAverageConvergenceDivergenceSignal _macd;
	private AverageTrueRange _atr;

	// Hidden Markov Model states, listed in the order used by the model tables below.
	private enum MarketStates
	{
		Bullish,
		Neutral,
		Bearish
	}

	// Typical move of every state measured in average ranges: the bullish state rises by one
	// average range, the bearish state falls by one and the neutral state goes nowhere.
	private static readonly double[] _stateMeans = [1.0, 0.0, -1.0];

	// Transition matrix of the hidden chain. States are sticky, and a jump from bullish
	// straight to bearish is far less likely than a stop in the neutral state.
	private static readonly double[][] _transitions =
	[
		[0.80, 0.15, 0.05],
		[0.15, 0.70, 0.15],
		[0.05, 0.15, 0.80],
	];

	private MarketStates _currentState = MarketStates.Neutral;

	// Data for HMM calculations
	private readonly List<decimal> _priceChanges = [];
	private decimal _prevPrice;
	private decimal? _prevMacd;
	private decimal? _prevSignal;
	private decimal? _stopPrice;
	private int _cooldownRemaining;

	/// <summary>
	/// MACD fast period.
	/// </summary>
	public int MacdFast
	{
		get => _macdFast.Value;
		set => _macdFast.Value = value;
	}

	/// <summary>
	/// MACD slow period.
	/// </summary>
	public int MacdSlow
	{
		get => _macdSlow.Value;
		set => _macdSlow.Value = value;
	}

	/// <summary>
	/// MACD signal period.
	/// </summary>
	public int MacdSignal
	{
		get => _macdSignal.Value;
		set => _macdSignal.Value = value;
	}

	/// <summary>
	/// Candle type to use for the strategy.
	/// </summary>
	public DataType CandleType
	{
		get => _candleType.Value;
		set => _candleType.Value = value;
	}

	/// <summary>
	/// Length of history for Hidden Markov Model.
	/// </summary>
	public int HmmHistoryLength
	{
		get => _hmmHistoryLength.Value;
		set => _hmmHistoryLength.Value = value;
	}

	/// <summary>
	/// ATR period used to measure the stop distance.
	/// </summary>
	public int AtrPeriod
	{
		get => _atrPeriod.Value;
		set => _atrPeriod.Value = value;
	}

	/// <summary>
	/// Stop distance expressed in ATR multiples.
	/// </summary>
	public decimal AtrStopMultiplier
	{
		get => _atrStopMultiplier.Value;
		set => _atrStopMultiplier.Value = value;
	}

	/// <summary>
	/// Bars to wait between trading actions.
	/// </summary>
	public int SignalCooldownBars
	{
		get => _signalCooldownBars.Value;
		set => _signalCooldownBars.Value = value;
	}

	/// <summary>
	/// Initializes a new instance of the <see cref="MacdHmmStrategy"/>.
	/// </summary>
	public MacdHmmStrategy()
	{
		_macdFast = Param(nameof(MacdFast), 12)
		.SetDisplay("MACD Fast Period", "Fast EMA period for MACD", "Indicators")
		.SetOptimize(8, 20, 2);

		_macdSlow = Param(nameof(MacdSlow), 26)
		.SetDisplay("MACD Slow Period", "Slow EMA period for MACD", "Indicators")
		.SetOptimize(20, 40, 2);

		_macdSignal = Param(nameof(MacdSignal), 9)
		.SetDisplay("MACD Signal Period", "Signal EMA period for MACD", "Indicators")
		.SetOptimize(7, 15, 1);

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

		_hmmHistoryLength = Param(nameof(HmmHistoryLength), 100)
		.SetGreaterThanZero()
		.SetDisplay("HMM History Length", "Number of observations the model is estimated on", "HMM Parameters")
		.SetOptimize(50, 200, 10);

		_atrPeriod = Param(nameof(AtrPeriod), 14)
		.SetGreaterThanZero()
		.SetDisplay("ATR Period", "ATR period used to measure the stop distance", "Protection")
		.SetOptimize(7, 28, 7);

		_atrStopMultiplier = Param(nameof(AtrStopMultiplier), 2m)
		.SetGreaterThanZero()
		.SetDisplay("ATR Stop Multiplier", "Stop distance in ATR multiples", "Protection")
		.SetOptimize(1m, 4m, 0.5m);

		_signalCooldownBars = Param(nameof(SignalCooldownBars), 12)
		.SetGreaterThanZero()
		.SetDisplay("Signal Cooldown", "Bars to wait between position changes", "Trading");
	}

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

	/// <inheritdoc />
	protected override void OnReseted()
	{
		base.OnReseted();

		_currentState = MarketStates.Neutral;
		_prevPrice = 0;
		_prevMacd = null;
		_prevSignal = null;
		_stopPrice = null;
		_cooldownRemaining = 0;
		_priceChanges.Clear();

		_macd?.Reset();
		_atr?.Reset();
	}

	/// <inheritdoc />
	protected override void OnStarted2(DateTime time)
	{
		base.OnStarted2(time);

		// Create MACD indicator

		_macd = new MovingAverageConvergenceDivergenceSignal
		{
			Macd =
			{
				ShortMa = { Length = MacdFast },
				LongMa = { Length = MacdSlow },
			},
			SignalMa = { Length = MacdSignal }
		};

		// ATR measures the current range and sets how far the protective stop sits from the entry
		_atr = new AverageTrueRange
		{
			Length = AtrPeriod
		};

		// Create subscription and bind indicators
		var subscription = SubscribeCandles(CandleType);

		subscription
		.BindEx(_macd, _atr, ProcessCandle)
		.Start();

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

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

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

		// Update HMM data
		UpdateHmmData(candle);

		// Determine market state using HMM
		CalculateMarketState();

		if (_cooldownRemaining > 0)
			_cooldownRemaining--;

		if (macdValue is not IMovingAverageConvergenceDivergenceSignalValue macdTyped ||
			macdTyped.Macd is not decimal macd ||
			macdTyped.Signal is not decimal signal)
			return;

		if (_prevMacd is not decimal previousMacd || _prevSignal is not decimal previousSignal)
		{
			_prevMacd = macd;
			_prevSignal = signal;
			return;
		}

		// Stop distance follows volatility: the wider the average range, the wider the stop.
		var stopDistance = atrValue.ToDecimal() * AtrStopMultiplier;

		var crossUp = previousMacd <= previousSignal && macd > signal;
		var crossDown = previousMacd >= previousSignal && macd < signal;
		var longStop = Position > 0 && _stopPrice is decimal longLevel && candle.LowPrice <= longLevel;
		var shortStop = Position < 0 && _stopPrice is decimal shortLevel && candle.HighPrice >= shortLevel;
		var longExit = Position > 0 && (_currentState == MarketStates.Bearish || crossDown);
		var shortExit = Position < 0 && (_currentState == MarketStates.Bullish || crossUp);

		// Generate trade signals based on MACD transitions and HMM state.
		if (longStop || longExit)
		{
			SellMarket(Position);
			_stopPrice = null;
			_cooldownRemaining = SignalCooldownBars;
		}
		else if (shortStop || shortExit)
		{
			BuyMarket(Math.Abs(Position));
			_stopPrice = null;
			_cooldownRemaining = SignalCooldownBars;
		}
		else if (_cooldownRemaining == 0 && crossUp && _currentState == MarketStates.Bullish && Position <= 0)
		{
			BuyMarket(Volume + Math.Abs(Position));
			_stopPrice = candle.ClosePrice - stopDistance;
			_cooldownRemaining = SignalCooldownBars;
		}
		else if (_cooldownRemaining == 0 && crossDown && _currentState == MarketStates.Bearish && Position >= 0)
		{
			SellMarket(Volume + Math.Abs(Position));
			_stopPrice = candle.ClosePrice + stopDistance;
			_cooldownRemaining = SignalCooldownBars;
		}

		_prevMacd = macd;
		_prevSignal = signal;
	}

	private void UpdateHmmData(ICandleMessage candle)
	{
		// Calculate price change
		if (_prevPrice > 0)
		{
			_priceChanges.Add(candle.ClosePrice - _prevPrice);

			// Maintain the desired history length
			while (_priceChanges.Count > HmmHistoryLength)
				_priceChanges.RemoveAt(0);
		}

		_prevPrice = candle.ClosePrice;
	}

	private void CalculateMarketState()
	{
		// The model observes exactly HmmHistoryLength price changes, so it stays neutral
		// until that much history is collected.
		if (_priceChanges.Count < HmmHistoryLength)
			return;

		// The average absolute move of the window scales the observations, so the same
		// emission shapes fit both a quiet and a volatile market.
		var scale = 0m;

		foreach (var change in _priceChanges)
			scale += Math.Abs(change);

		scale /= _priceChanges.Count;

		if (scale <= 0)
			return;

		// Forward pass of the Hidden Markov Model: the belief starts uniform and every
		// observation of the window moves it, so the window length shapes the result.
		var states = _stateMeans.Length;
		var belief = new double[states];
		var updated = new double[states];

		for (var i = 0; i < states; i++)
			belief[i] = 1.0 / states;

		foreach (var change in _priceChanges)
		{
			var observation = (double)(change / scale);
			var total = 0.0;

			for (var next = 0; next < states; next++)
			{
				// Chance of standing in "next" before the observation is taken into account.
				var predicted = 0.0;

				for (var current = 0; current < states; current++)
					predicted += belief[current] * _transitions[current][next];

				// Cauchy-shaped likelihood: the closer the move is to the typical move of the
				// state, the stronger the evidence, and an extreme move never kills a state.
				var distance = observation - _stateMeans[next];

				updated[next] = predicted / (1.0 + distance * distance);
				total += updated[next];
			}

			for (var i = 0; i < states; i++)
				belief[i] = updated[i] / total;
		}

		// The state the filter considers most likely after the last observation.
		var best = 0;

		for (var i = 1; i < states; i++)
		{
			if (belief[i] > belief[best])
				best = i;
		}

		_currentState = (MarketStates)best;
	}
}