Nirvaman Imax-Strategie

using System;

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

namespace StockSharp.Samples.Strategies;

/// <summary>
/// Nirvaman Imax: Dual EMA crossover with trend filter and timed exit.
/// Fast EMA crosses slow EMA for direction, filter EMA confirms trend.
/// </summary>
public class NirvamanImaxStrategy : Strategy
{
	private readonly StrategyParam<DataType> _candleType;
	private readonly StrategyParam<int> _fastLength;
	private readonly StrategyParam<int> _slowLength;
	private readonly StrategyParam<int> _filterLength;
	private readonly StrategyParam<int> _atrLength;

	private decimal _prevFast;
	private decimal _prevSlow;
	private decimal _entryPrice;

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

		_fastLength = Param(nameof(FastLength), 10)
			.SetDisplay("Fast EMA", "Fast EMA period.", "Indicators");

		_slowLength = Param(nameof(SlowLength), 21)
			.SetDisplay("Slow EMA", "Slow EMA period.", "Indicators");

		_filterLength = Param(nameof(FilterLength), 50)
			.SetDisplay("Filter EMA", "Trend filter EMA period.", "Indicators");

		_atrLength = Param(nameof(AtrLength), 14)
			.SetDisplay("ATR Length", "ATR period for stops.", "Indicators");
	}

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

	public int FastLength
	{
		get => _fastLength.Value;
		set => _fastLength.Value = value;
	}

	public int SlowLength
	{
		get => _slowLength.Value;
		set => _slowLength.Value = value;
	}

	public int FilterLength
	{
		get => _filterLength.Value;
		set => _filterLength.Value = value;
	}

	public int AtrLength
	{
		get => _atrLength.Value;
		set => _atrLength.Value = value;
	}

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

		_prevFast = 0;
		_prevSlow = 0;
		_entryPrice = 0;
	}

		protected override void OnStarted2(DateTime time)
	{
		base.OnStarted2(time);

		_prevFast = 0;
		_prevSlow = 0;
		_entryPrice = 0;

		var fast = new ExponentialMovingAverage { Length = FastLength };
		var slow = new ExponentialMovingAverage { Length = SlowLength };
		var filter = new ExponentialMovingAverage { Length = FilterLength };
		var atr = new AverageTrueRange { Length = AtrLength };

		var subscription = SubscribeCandles(CandleType);
		subscription
			.Bind(fast, slow, filter, atr, ProcessCandle)
			.Start();

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

	private void ProcessCandle(ICandleMessage candle, decimal fastVal, decimal slowVal, decimal filterVal, decimal atrVal)
	{
		if (candle.State != CandleStates.Finished)
			return;

		if (_prevFast == 0 || _prevSlow == 0 || atrVal <= 0)
		{
			_prevFast = fastVal;
			_prevSlow = slowVal;
			return;
		}

		var close = candle.ClosePrice;

		// Exit management
		if (Position > 0)
		{
			if (close <= _entryPrice - atrVal * 2m || close >= _entryPrice + atrVal * 3m)
			{
				SellMarket();
				_entryPrice = 0;
			}
			else if (_prevFast >= _prevSlow && fastVal < slowVal)
			{
				SellMarket();
				_entryPrice = 0;
			}
		}
		else if (Position < 0)
		{
			if (close >= _entryPrice + atrVal * 2m || close <= _entryPrice - atrVal * 3m)
			{
				BuyMarket();
				_entryPrice = 0;
			}
			else if (_prevFast <= _prevSlow && fastVal > slowVal)
			{
				BuyMarket();
				_entryPrice = 0;
			}
		}

		// Entry: EMA crossover confirmed by filter EMA trend
		if (Position == 0)
		{
			if (_prevFast <= _prevSlow && fastVal > slowVal && close > filterVal)
			{
				_entryPrice = close;
				BuyMarket();
			}
			else if (_prevFast >= _prevSlow && fastVal < slowVal && close < filterVal)
			{
				_entryPrice = close;
				SellMarket();
			}
		}

		_prevFast = fastVal;
		_prevSlow = slowVal;
	}
}

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
from StockSharp.Algo.Indicators import ExponentialMovingAverage, AverageTrueRange

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

        self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))) \
            .SetDisplay("Candle Type", "Timeframe", "General")
        self._fast_length = self.Param("FastLength", 10) \
            .SetDisplay("Fast EMA", "Fast EMA period", "Indicators")
        self._slow_length = self.Param("SlowLength", 21) \
            .SetDisplay("Slow EMA", "Slow EMA period", "Indicators")
        self._filter_length = self.Param("FilterLength", 50) \
            .SetDisplay("Filter EMA", "Trend filter EMA period", "Indicators")
        self._atr_length = self.Param("AtrLength", 14) \
            .SetDisplay("ATR Length", "ATR period for stops", "Indicators")

        self._prev_fast = 0.0
        self._prev_slow = 0.0
        self._entry_price = 0.0

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

    @property
    def FastLength(self):
        return self._fast_length.Value

    @property
    def SlowLength(self):
        return self._slow_length.Value

    @property
    def FilterLength(self):
        return self._filter_length.Value

    @property
    def AtrLength(self):
        return self._atr_length.Value

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

        self._prev_fast = 0.0
        self._prev_slow = 0.0
        self._entry_price = 0.0

        self._fast = ExponentialMovingAverage()
        self._fast.Length = self.FastLength
        self._slow = ExponentialMovingAverage()
        self._slow.Length = self.SlowLength
        self._filter = ExponentialMovingAverage()
        self._filter.Length = self.FilterLength
        self._atr = AverageTrueRange()
        self._atr.Length = self.AtrLength

        subscription = self.SubscribeCandles(self.CandleType)
        subscription.Bind(self._fast, self._slow, self._filter, self._atr, self.ProcessCandle).Start()

    def ProcessCandle(self, candle, fast_val, slow_val, filter_val, atr_val):
        if candle.State != CandleStates.Finished:
            return

        fv = float(fast_val)
        sv = float(slow_val)
        flv = float(filter_val)
        av = float(atr_val)

        if self._prev_fast == 0 or self._prev_slow == 0 or av <= 0:
            self._prev_fast = fv
            self._prev_slow = sv
            return

        close = float(candle.ClosePrice)

        # Exit management
        if self.Position > 0:
            if close <= self._entry_price - av * 2.0 or close >= self._entry_price + av * 3.0:
                self.SellMarket()
                self._entry_price = 0.0
            elif self._prev_fast >= self._prev_slow and fv < sv:
                self.SellMarket()
                self._entry_price = 0.0
        elif self.Position < 0:
            if close >= self._entry_price + av * 2.0 or close <= self._entry_price - av * 3.0:
                self.BuyMarket()
                self._entry_price = 0.0
            elif self._prev_fast <= self._prev_slow and fv > sv:
                self.BuyMarket()
                self._entry_price = 0.0

        # Entry: EMA crossover confirmed by filter EMA trend
        if self.Position == 0:
            if self._prev_fast <= self._prev_slow and fv > sv and close > flv:
                self._entry_price = close
                self.BuyMarket()
            elif self._prev_fast >= self._prev_slow and fv < sv and close < flv:
                self._entry_price = close
                self.SellMarket()

        self._prev_fast = fv
        self._prev_slow = sv

    def OnReseted(self):
        super(nirvaman_imax_strategy, self).OnReseted()
        self._prev_fast = 0.0
        self._prev_slow = 0.0
        self._entry_price = 0.0

    def CreateClone(self):
        return nirvaman_imax_strategy()