DT RSI EXP1 Strategy

using System;
using System.Collections.Generic;

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

namespace StockSharp.Samples.Strategies;

/// <summary>
/// DT RSI EXP1 strategy - RSI overbought/oversold with EMA trend filter.
/// Buys when RSI crosses above oversold level while above EMA trend.
/// Sells when RSI crosses below overbought level while below EMA trend.
/// </summary>
public class DtRsiExp1Strategy : Strategy
{
	private readonly StrategyParam<int> _rsiPeriod;
	private readonly StrategyParam<int> _emaPeriod;
	private readonly StrategyParam<decimal> _oversold;
	private readonly StrategyParam<decimal> _overbought;
	private readonly StrategyParam<DataType> _candleType;

	private decimal _prevRsi;
	private bool _hasPrev;

	public int RsiPeriod { get => _rsiPeriod.Value; set => _rsiPeriod.Value = value; }
	public int EmaPeriod { get => _emaPeriod.Value; set => _emaPeriod.Value = value; }
	public decimal Oversold { get => _oversold.Value; set => _oversold.Value = value; }
	public decimal Overbought { get => _overbought.Value; set => _overbought.Value = value; }
	public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }

	public DtRsiExp1Strategy()
	{
		_rsiPeriod = Param(nameof(RsiPeriod), 14)
			.SetDisplay("RSI Period", "RSI period", "Indicators");

		_emaPeriod = Param(nameof(EmaPeriod), 20)
			.SetDisplay("EMA Period", "EMA trend filter period", "Indicators");

		_oversold = Param(nameof(Oversold), 30m)
			.SetDisplay("Oversold", "RSI oversold level", "Indicators");

		_overbought = Param(nameof(Overbought), 70m)
			.SetDisplay("Overbought", "RSI overbought level", "Indicators");

		_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(5).TimeFrame())
			.SetDisplay("Candle Type", "Candle timeframe", "General");
	}

	public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities() => [(Security, CandleType)];
	protected override void OnReseted() { base.OnReseted(); _prevRsi = 0m; _hasPrev = false; }

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

		_hasPrev = false;

		var rsi = new RelativeStrengthIndex { Length = RsiPeriod };
		var ema = new ExponentialMovingAverage { Length = EmaPeriod };

		var subscription = SubscribeCandles(CandleType);
		subscription
			.Bind(rsi, ema, ProcessCandle)
			.Start();

		StartProtection(
			takeProfit: new Unit(2, UnitTypes.Percent),
			stopLoss: new Unit(1, UnitTypes.Percent)
		);
	}

	private void ProcessCandle(ICandleMessage candle, decimal rsi, decimal ema)
	{
		if (candle.State != CandleStates.Finished)
			return;

		var close = candle.ClosePrice;

		if (!_hasPrev)
		{
			_prevRsi = rsi;
			_hasPrev = true;
			return;
		}

		// RSI crosses above oversold + bullish trend
		if (_prevRsi <= Oversold && rsi > Oversold && close > ema && Position == 0)
		{
			BuyMarket();
		}
		// RSI crosses below overbought + bearish trend
		else if (_prevRsi >= Overbought && rsi < Overbought && close < ema && Position == 0)
		{
			SellMarket();
		}

		_prevRsi = rsi;
	}
}

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.Indicators import RelativeStrengthIndex, ExponentialMovingAverage
from StockSharp.Algo.Strategies import Strategy
from StockSharp.Messages import Unit, UnitTypes


class dt_rsi_exp1_strategy(Strategy):
    def __init__(self):
        super(dt_rsi_exp1_strategy, self).__init__()
        self._rsi_period = self.Param("RsiPeriod", 14) \
            .SetDisplay("RSI Period", "RSI period", "Indicators")
        self._ema_period = self.Param("EmaPeriod", 20) \
            .SetDisplay("EMA Period", "EMA trend filter period", "Indicators")
        self._oversold = self.Param("Oversold", 30.0) \
            .SetDisplay("Oversold", "RSI oversold level", "Indicators")
        self._overbought = self.Param("Overbought", 70.0) \
            .SetDisplay("Overbought", "RSI overbought level", "Indicators")
        self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(5))) \
            .SetDisplay("Candle Type", "Candle timeframe", "General")
        self._prev_rsi = 0.0
        self._has_prev = False

    @property
    def rsi_period(self):
        return self._rsi_period.Value

    @property
    def ema_period(self):
        return self._ema_period.Value

    @property
    def oversold(self):
        return self._oversold.Value

    @property
    def overbought(self):
        return self._overbought.Value

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

    def OnReseted(self):
        super(dt_rsi_exp1_strategy, self).OnReseted()
        self._prev_rsi = 0.0
        self._has_prev = False

    def OnStarted2(self, time):
        super(dt_rsi_exp1_strategy, self).OnStarted2(time)
        self._has_prev = False
        rsi = RelativeStrengthIndex()
        rsi.Length = self.rsi_period
        ema = ExponentialMovingAverage()
        ema.Length = self.ema_period
        subscription = self.SubscribeCandles(self.candle_type)
        subscription.Bind(rsi, ema, self.process_candle).Start()
        self.StartProtection(
            takeProfit=Unit(2, UnitTypes.Percent),
            stopLoss=Unit(1, UnitTypes.Percent)
        )

    def process_candle(self, candle, rsi, ema):
        if candle.State != CandleStates.Finished:
            return
        close = float(candle.ClosePrice)
        rsi_val = float(rsi)
        ema_val = float(ema)
        if not self._has_prev:
            self._prev_rsi = rsi_val
            self._has_prev = True
            return
        if self._prev_rsi <= self.oversold and rsi_val > self.oversold and close > ema_val and self.Position == 0:
            self.BuyMarket()
        elif self._prev_rsi >= self.overbought and rsi_val < self.overbought and close < ema_val and self.Position == 0:
            self.SellMarket()
        self._prev_rsi = rsi_val

    def CreateClone(self):
        return dt_rsi_exp1_strategy()