ニューロ ニルヴァマン MQ4 攻略

using System;

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

namespace StockSharp.Samples.Strategies;

/// <summary>
/// NeuroNirvaman: Perceptron-inspired strategy using RSI momentum
/// with EMA trend filter and weighted signal scoring.
/// </summary>
public class NeuroNirvamanMq4Strategy : Strategy
{
	private readonly StrategyParam<DataType> _candleType;
	private readonly StrategyParam<int> _rsiLength;
	private readonly StrategyParam<int> _fastEmaLength;
	private readonly StrategyParam<int> _slowEmaLength;
	private readonly StrategyParam<int> _atrLength;

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

	public NeuroNirvamanMq4Strategy()
	{
		_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(5).TimeFrame())
			.SetDisplay("Candle Type", "Timeframe.", "General");

		_rsiLength = Param(nameof(RsiLength), 14)
			.SetDisplay("RSI Length", "RSI period.", "Indicators");

		_fastEmaLength = Param(nameof(FastEmaLength), 10)
			.SetDisplay("Fast EMA", "Fast EMA period.", "Indicators");

		_slowEmaLength = Param(nameof(SlowEmaLength), 30)
			.SetDisplay("Slow EMA", "Slow EMA period.", "Indicators");

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

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

	public int RsiLength
	{
		get => _rsiLength.Value;
		set => _rsiLength.Value = value;
	}

	public int FastEmaLength
	{
		get => _fastEmaLength.Value;
		set => _fastEmaLength.Value = value;
	}

	public int SlowEmaLength
	{
		get => _slowEmaLength.Value;
		set => _slowEmaLength.Value = value;
	}

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

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

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

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

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

		var rsi = new RelativeStrengthIndex { Length = RsiLength };
		var fast = new ExponentialMovingAverage { Length = FastEmaLength };
		var slow = new ExponentialMovingAverage { Length = SlowEmaLength };
		var atr = new AverageTrueRange { Length = AtrLength };

		var subscription = SubscribeCandles(CandleType);
		subscription
			.Bind(rsi, fast, slow, 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 rsiVal, decimal fastVal, decimal slowVal, decimal atrVal)
	{
		if (candle.State != CandleStates.Finished)
			return;

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

		var close = candle.ClosePrice;

		// Perceptron score: weighted RSI momentum + EMA trend alignment
		var rsiSignal = rsiVal > 50 ? 1m : -1m;
		var trendSignal = fastVal > slowVal ? 1m : -1m;
		var rsiAccel = rsiVal - _prevRsi > 0 ? 1m : -1m;
		var score = rsiSignal * 0.4m + trendSignal * 0.4m + rsiAccel * 0.2m;

		// Exit management
		if (Position > 0)
		{
			if (close <= _entryPrice - atrVal * 2m || close >= _entryPrice + atrVal * 3m || score < -0.5m)
			{
				SellMarket();
				_entryPrice = 0;
			}
		}
		else if (Position < 0)
		{
			if (close >= _entryPrice + atrVal * 2m || close <= _entryPrice - atrVal * 3m || score > 0.5m)
			{
				BuyMarket();
				_entryPrice = 0;
			}
		}

		// Entry: strong perceptron score with RSI crossover confirmation
		if (Position == 0)
		{
			if (score > 0.5m && _prevRsi <= 50 && rsiVal > 50)
			{
				_entryPrice = close;
				BuyMarket();
			}
			else if (score < -0.5m && _prevRsi >= 50 && rsiVal < 50)
			{
				_entryPrice = close;
				SellMarket();
			}
		}

		_prevRsi = rsiVal;
		_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.Indicators import RelativeStrengthIndex, ExponentialMovingAverage, AverageTrueRange
from StockSharp.Algo.Strategies import Strategy

class neuro_nirvaman_mq4_strategy(Strategy):
    def __init__(self):
        super(neuro_nirvaman_mq4_strategy, self).__init__()
        self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(5))).SetDisplay("Candle Type", "Timeframe.", "General")
        self._rsi_length = self.Param("RsiLength", 14).SetDisplay("RSI Length", "RSI period.", "Indicators")
        self._fast_ema_length = self.Param("FastEmaLength", 10).SetDisplay("Fast EMA", "Fast EMA period.", "Indicators")
        self._slow_ema_length = self.Param("SlowEmaLength", 30).SetDisplay("Slow EMA", "Slow EMA period.", "Indicators")
        self._atr_length = self.Param("AtrLength", 14).SetDisplay("ATR Length", "ATR period.", "Indicators")

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

    def OnReseted(self):
        super(neuro_nirvaman_mq4_strategy, self).OnReseted()
        self._prev_rsi = 0
        self._prev_fast = 0
        self._prev_slow = 0
        self._entry_price = 0

    def OnStarted2(self, time):
        super(neuro_nirvaman_mq4_strategy, self).OnStarted2(time)
        self._prev_rsi = 0
        self._prev_fast = 0
        self._prev_slow = 0
        self._entry_price = 0

        rsi = RelativeStrengthIndex()
        rsi.Length = self._rsi_length.Value
        fast = ExponentialMovingAverage()
        fast.Length = self._fast_ema_length.Value
        slow = ExponentialMovingAverage()
        slow.Length = self._slow_ema_length.Value
        atr = AverageTrueRange()
        atr.Length = self._atr_length.Value

        sub = self.SubscribeCandles(self.CandleType)
        sub.Bind(rsi, fast, slow, atr, self.OnProcess).Start()

        area = self.CreateChartArea()
        if area is not None:
            self.DrawCandles(area, sub)
            self.DrawIndicator(area, fast)
            self.DrawIndicator(area, slow)
            self.DrawOwnTrades(area)

    def OnProcess(self, candle, rsi_val, fast_val, slow_val, atr_val):
        if candle.State != CandleStates.Finished:
            return
        if self._prev_fast == 0 or self._prev_slow == 0 or self._prev_rsi == 0 or atr_val <= 0:
            self._prev_rsi = rsi_val
            self._prev_fast = fast_val
            self._prev_slow = slow_val
            return

        close = candle.ClosePrice
        rsi_signal = 1 if rsi_val > 50 else -1
        trend_signal = 1 if fast_val > slow_val else -1
        rsi_accel = 1 if (rsi_val - self._prev_rsi) > 0 else -1
        score = rsi_signal * 0.4 + trend_signal * 0.4 + rsi_accel * 0.2

        if self.Position > 0:
            if close <= self._entry_price - atr_val * 2 or close >= self._entry_price + atr_val * 3 or score < -0.5:
                self.SellMarket()
                self._entry_price = 0
        elif self.Position < 0:
            if close >= self._entry_price + atr_val * 2 or close <= self._entry_price - atr_val * 3 or score > 0.5:
                self.BuyMarket()
                self._entry_price = 0

        if self.Position == 0:
            if score > 0.5 and self._prev_rsi <= 50 and rsi_val > 50:
                self._entry_price = close
                self.BuyMarket()
            elif score < -0.5 and self._prev_rsi >= 50 and rsi_val < 50:
                self._entry_price = close
                self.SellMarket()

        self._prev_rsi = rsi_val
        self._prev_fast = fast_val
        self._prev_slow = slow_val

    def CreateClone(self):
        return neuro_nirvaman_mq4_strategy()