Estratégia do Consultor Especialista KDJ

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>
/// Strategy that replicates the MetaTrader KDJ Expert Advisor logic.
/// Uses the KDJ oscillator to detect momentum reversals and opens a single position with fixed take-profit and stop-loss levels.
/// </summary>
public class KdjExpertAdvisorStrategy : Strategy
{
	private readonly StrategyParam<int> _kdjPeriod;
	private readonly StrategyParam<int> _smoothK;
	private readonly StrategyParam<int> _smoothD;
	private readonly StrategyParam<int> _stopLossPips;
	private readonly StrategyParam<int> _takeProfitPips;
	private readonly StrategyParam<decimal> _orderVolume;
	private readonly StrategyParam<DataType> _candleType;

	private decimal? _previousK;
	private decimal? _previousKdc;
	private decimal _pipSize;

	/// <summary>
	/// Main lookback period used to calculate RSV for the KDJ oscillator.
	/// </summary>
	public int KdjPeriod
	{
		get => _kdjPeriod.Value;
		set => _kdjPeriod.Value = value;
	}

	/// <summary>
	/// Smoothing period applied to the %K line.
	/// </summary>
	public int SmoothK
	{
		get => _smoothK.Value;
		set => _smoothK.Value = value;
	}

	/// <summary>
	/// Smoothing period applied to the %D line.
	/// </summary>
	public int SmoothD
	{
		get => _smoothD.Value;
		set => _smoothD.Value = value;
	}

	/// <summary>
	/// Stop-loss distance expressed in pips.
	/// </summary>
	public int StopLossPips
	{
		get => _stopLossPips.Value;
		set => _stopLossPips.Value = value;
	}

	/// <summary>
	/// Take-profit distance expressed in pips.
	/// </summary>
	public int TakeProfitPips
	{
		get => _takeProfitPips.Value;
		set => _takeProfitPips.Value = value;
	}

	/// <summary>
	/// Volume applied to every market order.
	/// </summary>
	public decimal OrderVolume
	{
		get => _orderVolume.Value;
		set => _orderVolume.Value = value;
	}

	/// <summary>
	/// Candle type used for indicator calculations.
	/// </summary>
	public DataType CandleType
	{
		get => _candleType.Value;
		set => _candleType.Value = value;
	}

	/// <summary>
	/// Initializes a new instance of the <see cref="KdjExpertAdvisorStrategy"/> class.
	/// </summary>
	public KdjExpertAdvisorStrategy()
	{
		_kdjPeriod = Param(nameof(KdjPeriod), 30)
			.SetGreaterThanZero()
			.SetDisplay("KDJ Length", "Lookback period for KDJ RSV calculation", "KDJ")
			
			.SetOptimize(10, 60, 5);

		_smoothK = Param(nameof(SmoothK), 3)
			.SetGreaterThanZero()
			.SetDisplay("Smooth %K", "Smoothing length for %K", "KDJ")
			
			.SetOptimize(1, 10, 1);

		_smoothD = Param(nameof(SmoothD), 6)
			.SetGreaterThanZero()
			.SetDisplay("Smooth %D", "Smoothing length for %D", "KDJ")
			
			.SetOptimize(1, 15, 1);

		_stopLossPips = Param(nameof(StopLossPips), 250)
			.SetNotNegative()
			.SetDisplay("Stop Loss (pips)", "Protective stop distance in pips", "Risk")

			.SetOptimize(0, 1000, 50);

		_takeProfitPips = Param(nameof(TakeProfitPips), 450)
			.SetNotNegative()
			.SetDisplay("Take Profit (pips)", "Profit target distance in pips", "Risk")

			.SetOptimize(0, 1500, 50);

		_orderVolume = Param(nameof(OrderVolume), 1m)
			.SetGreaterThanZero()
			.SetDisplay("Order Volume", "Quantity used for entries", "Trading");

		_candleType = Param(nameof(CandleType), TimeSpan.FromHours(4).TimeFrame())
			.SetDisplay("Candle Type", "Timeframe for KDJ calculation", "Data");
	}

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

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

		_previousK = null;
		_previousKdc = null;
		_pipSize = 0m;
	}

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

		_pipSize = CalculatePipSize();

		var stopLossUnit = StopLossPips > 0 ? new Unit(StopLossPips * _pipSize, UnitTypes.Absolute) : null;
		var takeProfitUnit = TakeProfitPips > 0 ? new Unit(TakeProfitPips * _pipSize, UnitTypes.Absolute) : null;

		StartProtection(
			takeProfit: takeProfitUnit,
			stopLoss: stopLossUnit,
			useMarketOrders: true);

		var kdj = new StochasticOscillator
		{
			K = { Length = KdjPeriod },
			D = { Length = SmoothD }
		};

		var subscription = SubscribeCandles(CandleType);
		subscription
			.BindEx(kdj, ProcessCandle)
			.Start();

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

	private void ProcessCandle(ICandleMessage candle, IIndicatorValue kdjValue)
	{
		if (candle.State != CandleStates.Finished)
			return;

		var stochastic = (StochasticOscillatorValue)kdjValue;
		if (stochastic.K is not decimal k || stochastic.D is not decimal d)
			return;

		var kdc = k - d;

		var buySignal = false;
		var sellSignal = false;

		if (_previousKdc.HasValue)
		{
			buySignal |= _previousKdc.Value < 0m && kdc > 0m;
			sellSignal |= _previousKdc.Value > 0m && kdc < 0m;
		}

		if (_previousK.HasValue)
		{
			buySignal |= kdc > 0m && _previousK.Value < k;
			sellSignal |= kdc < 0m && _previousK.Value > k;
		}

		if (buySignal || sellSignal)
		{
			if (Position == 0)
			{
				if (buySignal)
				{
					LogInfo($"Buy signal at {candle.ClosePrice}: K={k:F2}, D={d:F2}, K-D={kdc:F2}");
					BuyMarket();
				}
				else if (sellSignal)
				{
					LogInfo($"Sell signal at {candle.ClosePrice}: K={k:F2}, D={d:F2}, K-D={kdc:F2}");
					SellMarket();
				}
			}
		}

		_previousK = k;
		_previousKdc = kdc;
	}

	private decimal CalculatePipSize()
	{
		var security = Security;
		if (security == null)
			return 1m;

		var step = security.PriceStep ?? 1m;
		var decimals = security.Decimals;
		var multiplier = (decimals == 3 || decimals == 5) ? 10m : 1m;

		return step * multiplier;
	}
}

import clr

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

from System import TimeSpan, Decimal
from StockSharp.Messages import DataType, CandleStates, Unit, UnitTypes
from StockSharp.Algo.Indicators import StochasticOscillator
from StockSharp.Algo.Strategies import Strategy

class kdj_expert_advisor_strategy(Strategy):
    """
    KDJ Expert Advisor: uses Stochastic Oscillator K/D crossover
    for momentum reversals with pip-based SL/TP via StartProtection.
    """

    def __init__(self):
        super(kdj_expert_advisor_strategy, self).__init__()
        self._kdj_period = self.Param("KdjPeriod", 30) \
            .SetDisplay("KDJ Length", "Lookback period for KDJ", "KDJ")
        self._smooth_d = self.Param("SmoothD", 6) \
            .SetDisplay("Smooth %D", "Smoothing for %D", "KDJ")
        self._stop_loss_pips = self.Param("StopLossPips", 250) \
            .SetDisplay("Stop Loss (pips)", "Stop distance in pips", "Risk")
        self._take_profit_pips = self.Param("TakeProfitPips", 450) \
            .SetDisplay("Take Profit (pips)", "Profit target in pips", "Risk")
        self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))) \
            .SetDisplay("Candle Type", "Timeframe for KDJ", "Data")

        self._prev_k = None
        self._prev_kdc = None

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

    def OnReseted(self):
        super(kdj_expert_advisor_strategy, self).OnReseted()
        self._prev_k = None
        self._prev_kdc = None

    def _calculate_pip_size(self):
        step = 1.0
        if self.Security is not None and self.Security.PriceStep is not None:
            step = float(self.Security.PriceStep)
        if step <= 0:
            step = 1.0
        decimals = 0
        if self.Security is not None and self.Security.Decimals is not None:
            decimals = int(self.Security.Decimals)
        multiplier = 10.0 if decimals in (3, 5) else 1.0
        return step * multiplier

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

        pip_size = self._calculate_pip_size()
        sl_pips = self._stop_loss_pips.Value
        tp_pips = self._take_profit_pips.Value

        tp_val = Decimal(float(tp_pips) * pip_size) if tp_pips > 0 else Decimal(0)
        sl_val = Decimal(float(sl_pips) * pip_size) if sl_pips > 0 else Decimal(0)
        tp_unit = Unit(tp_val, UnitTypes.Absolute) if tp_pips > 0 else Unit()
        sl_unit = Unit(sl_val, UnitTypes.Absolute) if sl_pips > 0 else Unit()
        self.StartProtection(tp_unit, sl_unit)

        kdj = StochasticOscillator()
        kdj.K.Length = self._kdj_period.Value
        kdj.D.Length = self._smooth_d.Value

        subscription = self.SubscribeCandles(self.candle_type)
        subscription.BindEx(kdj, self._process_candle).Start()

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

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

        k = kdj_value.K
        d = kdj_value.D
        if k is None or d is None:
            return

        k = float(k)
        d = float(d)
        kdc = k - d

        buy_signal = False
        sell_signal = False

        if self._prev_kdc is not None:
            if self._prev_kdc < 0 and kdc > 0:
                buy_signal = True
            if self._prev_kdc > 0 and kdc < 0:
                sell_signal = True

        if self._prev_k is not None:
            if kdc > 0 and self._prev_k < k:
                buy_signal = True
            if kdc < 0 and self._prev_k > k:
                sell_signal = True

        pos = float(self.Position)
        if abs(pos) < 0.0001:
            if buy_signal:
                self.BuyMarket()
            elif sell_signal:
                self.SellMarket()

        self._prev_k = k
        self._prev_kdc = kdc

    def CreateClone(self):
        return kdj_expert_advisor_strategy()