Ma SAR ADX Bind 戦略

using System;
using System.Linq;
using System.Collections.Generic;
using Ecng.Common;
using Ecng.Collections;
using Ecng.Serialization;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;

namespace StockSharp.Samples.Strategies;



/// <summary>
/// Conversion of the MaSarADX MetaTrader strategy to StockSharp high level API.
/// Combines a moving average, ADX directional movement and Parabolic SAR for entries and exits.
/// </summary>
public class MaSarAdxBindStrategy : Strategy
{
	private readonly StrategyParam<int> _maPeriod;
	private readonly StrategyParam<int> _adxPeriod;
	private readonly StrategyParam<decimal> _sarStep;
	private readonly StrategyParam<decimal> _sarMax;
	private readonly StrategyParam<DataType> _candleType;

	private decimal? _previousHigh;
	private decimal? _previousLow;
	private decimal? _previousClose;
	private decimal _smoothedPlusDm;
	private decimal _smoothedMinusDm;
	private decimal _smoothedTrueRange;
	private int _adxSamples;

	/// <summary>
	/// Moving average period used for the trend filter.
	/// </summary>
	public int MaPeriod
	{
		get => _maPeriod.Value;
		set => _maPeriod.Value = value;
	}

	/// <summary>
	/// Average Directional Index calculation period.
	/// </summary>
	public int AdxPeriod
	{
		get => _adxPeriod.Value;
		set => _adxPeriod.Value = value;
	}

	/// <summary>
	/// Acceleration step for the Parabolic SAR indicator.
	/// </summary>
	public decimal SarStep
	{
		get => _sarStep.Value;
		set => _sarStep.Value = value;
	}

	/// <summary>
	/// Maximum acceleration factor for the Parabolic SAR indicator.
	/// </summary>
	public decimal SarMax
	{
		get => _sarMax.Value;
		set => _sarMax.Value = value;
	}


	/// <summary>
	/// Type of candles processed by the strategy.
	/// </summary>
	public DataType CandleType
	{
		get => _candleType.Value;
		set => _candleType.Value = value;
	}

	/// <summary>
	/// Initializes a new instance of <see cref="MaSarAdxBindStrategy"/>.
	/// </summary>
	public MaSarAdxBindStrategy()
	{
		_maPeriod = Param(nameof(MaPeriod), 120)
		.SetGreaterThanZero()
		.SetDisplay("MA Period", "Length of the trend moving average", "Indicators")
		
		.SetOptimize(20, 200, 10);

		_adxPeriod = Param(nameof(AdxPeriod), 18)
		.SetGreaterThanZero()
		.SetDisplay("ADX Period", "Length of the Average Directional Index", "Indicators")
		
		.SetOptimize(7, 28, 1);

		_sarStep = Param(nameof(SarStep), 0.02m)
		.SetRange(0.005m, 0.2m)
		.SetDisplay("SAR Step", "Acceleration step for Parabolic SAR", "Indicators")
		;

		_sarMax = Param(nameof(SarMax), 0.1m)
		.SetRange(0.05m, 1m)
		.SetDisplay("SAR Maximum", "Maximum acceleration for Parabolic SAR", "Indicators")
		;


		_candleType = Param(nameof(CandleType), TimeSpan.FromHours(2).TimeFrame())
		.SetDisplay("Candle Type", "Type of candles to request", "General");
	}

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

	/// <inheritdoc />
	protected override void OnReseted()
	{
		base.OnReseted();
		_previousHigh = null;
		_previousLow = null;
		_previousClose = null;
		_smoothedPlusDm = 0m;
		_smoothedMinusDm = 0m;
		_smoothedTrueRange = 0m;
		_adxSamples = 0;
	}

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

		// Instantiate indicators used in the original MetaTrader script.
		var movingAverage = new SimpleMovingAverage
		{
			Length = MaPeriod
		};

		var parabolicSar = new ParabolicSar
		{
			Acceleration = SarStep,
			AccelerationStep = SarStep,
			AccelerationMax = SarMax
		};

		// Subscribe to candle data and bind indicator updates to a single handler.
		var subscription = SubscribeCandles(CandleType);
		subscription
			.Bind(movingAverage, parabolicSar, ProcessCandle)
			.Start();

		// Draw the trading context for visual debugging when charts are available.
		var area = CreateChartArea();
		if (area != null)
		{
			DrawCandles(area, subscription);
			DrawIndicator(area, movingAverage);
			DrawIndicator(area, parabolicSar);
			DrawOwnTrades(area);

		}
	}

	private void ProcessCandle(ICandleMessage candle, decimal movingAverage, decimal sar)
	{
		// Work only with completed candles to mirror the original first-tick logic.
		if (candle.State != CandleStates.Finished)
			return;

		var (plusDi, minusDi, isReady) = UpdateDirectionalMovement(candle);
		if (!isReady)
			return;

		// Always allow risk exits even if trading is temporarily disabled.
		if (Position > 0 && candle.ClosePrice < sar)
		{
			SellMarket();
			return;
		}

		if (Position < 0 && candle.ClosePrice > sar)
		{
			BuyMarket();
			return;
		}

		// Entry conditions replicated from the MetaTrader version.
		var bullishSignal = candle.ClosePrice > movingAverage && plusDi >= minusDi && candle.ClosePrice > sar;
		var bearishSignal = candle.ClosePrice < movingAverage && plusDi <= minusDi && candle.ClosePrice < sar;

		if (bullishSignal && Position <= 0)
		{
			BuyMarket();
			return;
		}

		if (bearishSignal && Position >= 0)
		{
			SellMarket();
		}
	}

	private (decimal plusDi, decimal minusDi, bool isReady) UpdateDirectionalMovement(ICandleMessage candle)
	{
		if (_previousHigh is not decimal previousHigh ||
			_previousLow is not decimal previousLow ||
			_previousClose is not decimal previousClose)
		{
			_previousHigh = candle.HighPrice;
			_previousLow = candle.LowPrice;
			_previousClose = candle.ClosePrice;
			return (0m, 0m, false);
		}

		var upMove = candle.HighPrice - previousHigh;
		var downMove = previousLow - candle.LowPrice;
		var plusDm = upMove > downMove && upMove > 0m ? upMove : 0m;
		var minusDm = downMove > upMove && downMove > 0m ? downMove : 0m;
		var trueRange = Math.Max(
			candle.HighPrice - candle.LowPrice,
			Math.Max(
				Math.Abs(candle.HighPrice - previousClose),
				Math.Abs(candle.LowPrice - previousClose)));

		if (_adxSamples < AdxPeriod)
		{
			_smoothedPlusDm += plusDm;
			_smoothedMinusDm += minusDm;
			_smoothedTrueRange += trueRange;
			_adxSamples++;
		}
		else
		{
			_smoothedPlusDm = _smoothedPlusDm - (_smoothedPlusDm / AdxPeriod) + plusDm;
			_smoothedMinusDm = _smoothedMinusDm - (_smoothedMinusDm / AdxPeriod) + minusDm;
			_smoothedTrueRange = _smoothedTrueRange - (_smoothedTrueRange / AdxPeriod) + trueRange;
		}

		_previousHigh = candle.HighPrice;
		_previousLow = candle.LowPrice;
		_previousClose = candle.ClosePrice;

		if (_adxSamples < AdxPeriod || _smoothedTrueRange <= 0m)
			return (0m, 0m, false);

		return (
			100m * _smoothedPlusDm / _smoothedTrueRange,
			100m * _smoothedMinusDm / _smoothedTrueRange,
			true);
	}
}

import clr

clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")

from System import TimeSpan, Math
from StockSharp.Messages import DataType, CandleStates, Unit, UnitTypes
from StockSharp.Algo.Indicators import SimpleMovingAverage, ParabolicSar
from StockSharp.Algo.Strategies import Strategy


class ma_sar_adx_bind_strategy(Strategy):
    def __init__(self):
        super(ma_sar_adx_bind_strategy, self).__init__()

        self._ma_period = self.Param("MaPeriod", 120)
        self._adx_period = self.Param("AdxPeriod", 18)
        self._sar_step = self.Param("SarStep", 0.02)
        self._sar_max = self.Param("SarMax", 0.1)
        self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(2)))

        self._previous_high = None
        self._previous_low = None
        self._previous_close = None
        self._smoothed_plus_dm = 0.0
        self._smoothed_minus_dm = 0.0
        self._smoothed_true_range = 0.0
        self._adx_samples = 0

    @property
    def MaPeriod(self):
        return self._ma_period.Value

    @MaPeriod.setter
    def MaPeriod(self, value):
        self._ma_period.Value = value

    @property
    def AdxPeriod(self):
        return self._adx_period.Value

    @AdxPeriod.setter
    def AdxPeriod(self, value):
        self._adx_period.Value = value

    @property
    def SarStep(self):
        return self._sar_step.Value

    @SarStep.setter
    def SarStep(self, value):
        self._sar_step.Value = value

    @property
    def SarMax(self):
        return self._sar_max.Value

    @SarMax.setter
    def SarMax(self, value):
        self._sar_max.Value = value

    @property
    def CandleType(self):
        return self._candle_type.Value

    @CandleType.setter
    def CandleType(self, value):
        self._candle_type.Value = value

    def OnStarted2(self, time):
        super(ma_sar_adx_bind_strategy, self).OnStarted2(time)

        self._previous_high = None
        self._previous_low = None
        self._previous_close = None
        self._smoothed_plus_dm = 0.0
        self._smoothed_minus_dm = 0.0
        self._smoothed_true_range = 0.0
        self._adx_samples = 0

        ma = SimpleMovingAverage()
        ma.Length = self.MaPeriod

        sar = ParabolicSar()
        sar.Acceleration = float(self.SarStep)
        sar.AccelerationStep = float(self.SarStep)
        sar.AccelerationMax = float(self.SarMax)

        subscription = self.SubscribeCandles(self.CandleType)
        subscription.Bind(ma, sar, self.ProcessCandle).Start()

    def ProcessCandle(self, candle, moving_average, sar):
        if candle.State != CandleStates.Finished:
            return

        ma_val = float(moving_average)
        sar_val = float(sar)

        plus_di, minus_di, is_ready = self._update_directional_movement(candle)
        if not is_ready:
            return

        close = float(candle.ClosePrice)

        # Exit conditions
        if self.Position > 0 and close < sar_val:
            self.SellMarket()
            return

        if self.Position < 0 and close > sar_val:
            self.BuyMarket()
            return

        # Entry conditions
        bullish_signal = close > ma_val and plus_di >= minus_di and close > sar_val
        bearish_signal = close < ma_val and plus_di <= minus_di and close < sar_val

        if bullish_signal and self.Position <= 0:
            self.BuyMarket()
            return

        if bearish_signal and self.Position >= 0:
            self.SellMarket()

    def _update_directional_movement(self, candle):
        high = float(candle.HighPrice)
        low = float(candle.LowPrice)
        close = float(candle.ClosePrice)

        if self._previous_high is None or self._previous_low is None or self._previous_close is None:
            self._previous_high = high
            self._previous_low = low
            self._previous_close = close
            return (0.0, 0.0, False)

        up_move = high - self._previous_high
        down_move = self._previous_low - low
        plus_dm = up_move if (up_move > down_move and up_move > 0.0) else 0.0
        minus_dm = down_move if (down_move > up_move and down_move > 0.0) else 0.0
        true_range = max(high - low, max(abs(high - self._previous_close), abs(low - self._previous_close)))

        adx_period = int(self.AdxPeriod)

        if self._adx_samples < adx_period:
            self._smoothed_plus_dm += plus_dm
            self._smoothed_minus_dm += minus_dm
            self._smoothed_true_range += true_range
            self._adx_samples += 1
        else:
            self._smoothed_plus_dm = self._smoothed_plus_dm - (self._smoothed_plus_dm / adx_period) + plus_dm
            self._smoothed_minus_dm = self._smoothed_minus_dm - (self._smoothed_minus_dm / adx_period) + minus_dm
            self._smoothed_true_range = self._smoothed_true_range - (self._smoothed_true_range / adx_period) + true_range

        self._previous_high = high
        self._previous_low = low
        self._previous_close = close

        if self._adx_samples < adx_period or self._smoothed_true_range <= 0.0:
            return (0.0, 0.0, False)

        return (
            100.0 * self._smoothed_plus_dm / self._smoothed_true_range,
            100.0 * self._smoothed_minus_dm / self._smoothed_true_range,
            True)

    def OnReseted(self):
        super(ma_sar_adx_bind_strategy, self).OnReseted()
        self._previous_high = None
        self._previous_low = None
        self._previous_close = None
        self._smoothed_plus_dm = 0.0
        self._smoothed_minus_dm = 0.0
        self._smoothed_true_range = 0.0
        self._adx_samples = 0

    def CreateClone(self):
        return ma_sar_adx_bind_strategy()