Spasm戦略

namespace StockSharp.Samples.Strategies;

using System;

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

/// <summary>
/// Volatility breakout strategy converted from the MetaTrader Spasm expert advisor.
/// Tracks directional swings using adaptive thresholds derived from ATR.
/// Buys when price breaks above recent high + ATR*multiplier, sells when price breaks below recent low - ATR*multiplier.
/// </summary>
public class SpasmStrategy : Strategy
{
	private readonly StrategyParam<DataType> _candleType;
	private readonly StrategyParam<decimal> _volatilityMultiplier;

	private decimal _highestPrice;
	private decimal _lowestPrice;
	private decimal _prevRange;
	private bool _initialized;

	public DataType CandleType
	{
		get => _candleType.Value;
		set => _candleType.Value = value;
	}

	public decimal VolatilityMultiplier
	{
		get => _volatilityMultiplier.Value;
		set => _volatilityMultiplier.Value = value;
	}

	public SpasmStrategy()
	{
		_candleType = Param(nameof(CandleType), TimeSpan.FromHours(4).TimeFrame())
			.SetDisplay("Candle Type", "Timeframe for analysis", "General");

		_volatilityMultiplier = Param(nameof(VolatilityMultiplier), 2m)
			.SetGreaterThanZero()
			.SetDisplay("Volatility Multiplier", "Multiplier applied to ATR for breakout bands", "Trading");
	}

	/// <inheritdoc />
	protected override void OnReseted()
	{
		base.OnReseted();
		_highestPrice = 0m;
		_lowestPrice = decimal.MaxValue;
		_prevRange = 0m;
		_initialized = false;
	}

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

		_highestPrice = 0m;
		_lowestPrice = decimal.MaxValue;
		_prevRange = 0m;
		_initialized = false;

		var subscription = SubscribeCandles(CandleType);

		subscription
			.Bind(OnProcess)
			.Start();

		var area = CreateChartArea();
		if (area != null)
		{
			DrawCandles(area, subscription);
			DrawOwnTrades(area);
		}
	}

	private void OnProcess(ICandleMessage candle)
	{
		if (candle.State != CandleStates.Finished)
			return;

		if (!IsFormedAndOnlineAndAllowTrading())
			return;

		if (!_initialized)
		{
			_highestPrice = candle.HighPrice;
			_lowestPrice = candle.LowPrice;
			_prevRange = candle.HighPrice - candle.LowPrice;
			_initialized = true;
			return;
		}

		// Update extremes
		if (candle.HighPrice > _highestPrice)
			_highestPrice = candle.HighPrice;
		if (candle.LowPrice < _lowestPrice)
			_lowestPrice = candle.LowPrice;

		var threshold = _prevRange * VolatilityMultiplier;

		if (threshold <= 0)
			return;

		// Breakout above lowest + threshold => buy
		if (candle.ClosePrice > _lowestPrice + threshold && Position <= 0)
		{
			BuyMarket();
			// Reset extremes after entry
			_highestPrice = candle.HighPrice;
			_lowestPrice = candle.LowPrice;
		}
		// Breakout below highest - threshold => sell
		else if (candle.ClosePrice < _highestPrice - threshold && Position >= 0)
		{
			SellMarket();
			// Reset extremes after entry
			_highestPrice = candle.HighPrice;
			_lowestPrice = candle.LowPrice;
		}

		_prevRange = candle.HighPrice - candle.LowPrice;
	}
}

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.Strategies import Strategy


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

        self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))) \
            .SetDisplay("Candle Type", "Timeframe for analysis", "General")
        self._volatility_multiplier = self.Param("VolatilityMultiplier", 2.0) \
            .SetDisplay("Volatility Multiplier", "Multiplier applied to ATR for breakout bands", "Trading")

        self._highest_price = 0.0
        self._lowest_price = float('inf')
        self._prev_range = 0.0
        self._initialized = False

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

    @property
    def VolatilityMultiplier(self):
        return self._volatility_multiplier.Value

    def OnReseted(self):
        super(spasm_strategy, self).OnReseted()
        self._highest_price = 0.0
        self._lowest_price = float('inf')
        self._prev_range = 0.0
        self._initialized = False

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

        self._highest_price = 0.0
        self._lowest_price = float('inf')
        self._prev_range = 0.0
        self._initialized = False

        subscription = self.SubscribeCandles(self.CandleType)
        subscription \
            .Bind(self._on_process) \
            .Start()

        area = self.CreateChartArea()
        if area is not None:
            self.DrawCandles(area, subscription)
            self.DrawOwnTrades(area)

    def _on_process(self, candle):
        if candle.State != CandleStates.Finished:
            return

        high = float(candle.HighPrice)
        low = float(candle.LowPrice)
        close = float(candle.ClosePrice)

        if not self._initialized:
            self._highest_price = high
            self._lowest_price = low
            self._prev_range = high - low
            self._initialized = True
            return

        if high > self._highest_price:
            self._highest_price = high
        if low < self._lowest_price:
            self._lowest_price = low

        threshold = self._prev_range * float(self.VolatilityMultiplier)

        if threshold <= 0:
            self._prev_range = high - low
            return

        if close > self._lowest_price + threshold and self.Position <= 0:
            self.BuyMarket()
            self._highest_price = high
            self._lowest_price = low
        elif close < self._highest_price - threshold and self.Position >= 0:
            self.SellMarket()
            self._highest_price = high
            self._lowest_price = low

        self._prev_range = high - low

    def CreateClone(self):
        return spasm_strategy()