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Estrategia de Rompimiento por Distancia Parabolic SAR

La estrategia de Rompimiento por Distancia Parabolic SAR observa el Parabolic en busca de expansiones rápidas. Cuando las lecturas saltan más allá de su rango reciente, el precio a menudo inicia un nuevo movimiento.

Las pruebas indican un rendimiento anual promedio de aproximadamente 118%. Funciona mejor en el mercado de acciones.

Una posición se abre una vez que el indicador perfora una banda derivada de datos recientes y un multiplicador de desviación. Son posibles operaciones largas y cortas con un stop adjunto.

Este sistema es adecuado para operadores de momentum que buscan rompimientos tempranos. Las operaciones se cierran cuando el Parabolic vuelve hacia la media. Los valores predeterminados comienzan con Acceleration = 0.02m.

Detalles

  • Criterios de entrada: El indicador supera el promedio por el multiplicador de desviación.
  • Largo/Corto: Ambos direcciones.
  • Criterios de salida: El indicador revierte al promedio.
  • Stops: Sí.
  • Valores predeterminados:
    • Acceleration = 0.02m
    • MaxAcceleration = 0.2m
    • LookbackPeriod = 20
    • DeviationMultiplier = 2m
    • CandleType = TimeSpan.FromMinutes(5)
  • Filtros:
    • Categoría: Ruptura
    • Dirección: Ambos
    • Indicadores: Parabolic
    • Stops: Sí
    • Complejidad: Intermedio
    • Marco temporal: Corto plazo
    • Estacionalidad: No
    • Redes neuronales: No
    • Divergencia: No
    • Nivel de riesgo: Medio
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 enters positions when the distance between price and Parabolic SAR
/// exceeds the average distance plus a multiple of standard deviation
/// </summary>
public class ParabolicSarDistanceBreakoutStrategy : Strategy
{
	private readonly StrategyParam<decimal> _acceleration;
	private readonly StrategyParam<decimal> _maxAcceleration;
	private readonly StrategyParam<int> _lookbackPeriod;
	private readonly StrategyParam<decimal> _deviationMultiplier;
	private readonly StrategyParam<DataType> _candleType;

	private ParabolicSar _parabolicSar;
	
	private decimal _avgDistanceLong;
	private decimal _stdDevDistanceLong;
	private decimal _avgDistanceShort;
	private decimal _stdDevDistanceShort;
	
	private decimal _lastLongDistance;
	private decimal _lastShortDistance;
	private int _samplesCount;

	/// <summary>
	/// Initial acceleration factor for Parabolic SAR
	/// </summary>
	public decimal Acceleration
	{
		get => _acceleration.Value;
		set => _acceleration.Value = value;
	}

	/// <summary>
	/// Maximum acceleration factor for Parabolic SAR
	/// </summary>
	public decimal MaxAcceleration
	{
		get => _maxAcceleration.Value;
		set => _maxAcceleration.Value = value;
	}

	/// <summary>
	/// Lookback period for distance statistics calculation
	/// </summary>
	public int LookbackPeriod
	{
		get => _lookbackPeriod.Value;
		set => _lookbackPeriod.Value = value;
	}

	/// <summary>
	/// Standard deviation multiplier for breakout detection
	/// </summary>
	public decimal DeviationMultiplier
	{
		get => _deviationMultiplier.Value;
		set => _deviationMultiplier.Value = value;
	}

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

	/// <summary>
	/// Constructor
	/// </summary>
	public ParabolicSarDistanceBreakoutStrategy()
	{
		_acceleration = Param(nameof(Acceleration), 0.02m)
			.SetGreaterThanZero()
			.SetDisplay("Acceleration", "Initial acceleration factor for Parabolic SAR", "Indicator Parameters")
			
			.SetOptimize(0.01m, 0.05m, 0.01m);

		_maxAcceleration = Param(nameof(MaxAcceleration), 0.2m)
			.SetGreaterThanZero()
			.SetDisplay("Max Acceleration", "Maximum acceleration factor for Parabolic SAR", "Indicator Parameters")
			
			.SetOptimize(0.1m, 0.5m, 0.1m);

		_lookbackPeriod = Param(nameof(LookbackPeriod), 20)
			.SetGreaterThanZero()
			.SetDisplay("Lookback Period", "Period for statistical calculations", "Strategy Parameters")
			
			.SetOptimize(10, 50, 5);

		_deviationMultiplier = Param(nameof(DeviationMultiplier), 2m)
			.SetGreaterThanZero()
			.SetDisplay("Deviation Multiplier", "Standard deviation multiplier for breakout detection", "Strategy Parameters")
			
			.SetOptimize(1m, 3m, 0.5m);

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

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

	/// <inheritdoc />
	protected override void OnReseted()
	{
		base.OnReseted();
		_avgDistanceLong = 0;
		_stdDevDistanceLong = 0;
		_avgDistanceShort = 0;
		_stdDevDistanceShort = 0;
		_lastLongDistance = 0;
		_lastShortDistance = 0;
		_samplesCount = 0;
	}

	/// <inheritdoc />
	protected override void OnStarted2(DateTime time)
	{
		_parabolicSar = new ParabolicSar
		{
			Acceleration = Acceleration,
			AccelerationMax = MaxAcceleration
		};


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

		// Setup chart visualization if available
		var area = CreateChartArea();
		if (area != null)
		{
			DrawCandles(area, subscription);
			DrawIndicator(area, _parabolicSar);
			DrawOwnTrades(area);
		}

		// Set up position protection using the dynamic Parabolic SAR
		StartProtection(
			takeProfit: null, // We'll handle exits via strategy logic
			stopLoss: null,   // The dynamic SAR will act as our stop
			isStopTrailing: true
		);

		base.OnStarted2(time);
	}

	private void ProcessCandle(ICandleMessage candle, decimal sarValue)
	{
		// Skip unfinished candles
		if (candle.State != CandleStates.Finished)
			return;

		// Check if strategy is ready for trading
		if (!IsFormedAndOnlineAndAllowTrading())
			return;

		// Calculate distances
		decimal longDistance = 0;
		decimal shortDistance = 0;
		
		// If SAR is below price, it's in uptrend
		if (sarValue < candle.ClosePrice)
			longDistance = candle.ClosePrice - sarValue;
		// If SAR is above price, it's in downtrend
		else if (sarValue > candle.ClosePrice)
			shortDistance = sarValue - candle.ClosePrice;
		
		// Update statistics
		UpdateDistanceStatistics(longDistance, shortDistance);
		
		// Trading logic
		if (_samplesCount >= LookbackPeriod)
		{
			// Long signal: distance exceeds average + k*stddev and we don't have a long position
			if (longDistance > 0 && 
				longDistance > _avgDistanceLong + DeviationMultiplier * _stdDevDistanceLong && 
				Position <= 0)
			{
				// Cancel existing orders
				CancelActiveOrders();
				
				// Enter long position
				var volume = Volume + Math.Abs(Position);
				BuyMarket(volume);
				
				LogInfo($"Long signal: Distance {longDistance} > Avg {_avgDistanceLong} + {DeviationMultiplier}*StdDev {_stdDevDistanceLong}");
			}
			// Short signal: distance exceeds average + k*stddev and we don't have a short position
			else if (shortDistance > 0 && 
					 shortDistance > _avgDistanceShort + DeviationMultiplier * _stdDevDistanceShort && 
					 Position >= 0)
			{
				// Cancel existing orders
				CancelActiveOrders();
				
				// Enter short position
				var volume = Volume + Math.Abs(Position);
				SellMarket(volume);
				
				LogInfo($"Short signal: Distance {shortDistance} > Avg {_avgDistanceShort} + {DeviationMultiplier}*StdDev {_stdDevDistanceShort}");
			}
			
			// Exit conditions - when price crosses SAR
			if (Position > 0 && candle.ClosePrice < sarValue)
			{
				// Exit long position
				SellMarket(Math.Abs(Position));
				LogInfo($"Exit long: Price {candle.ClosePrice} crossed below SAR {sarValue}");
			}
			else if (Position < 0 && candle.ClosePrice > sarValue)
			{
				// Exit short position
				BuyMarket(Math.Abs(Position));
				LogInfo($"Exit short: Price {candle.ClosePrice} crossed above SAR {sarValue}");
			}
		}
		
		// Store current distances for next update
		_lastLongDistance = longDistance;
		_lastShortDistance = shortDistance;
	}
	
	private void UpdateDistanceStatistics(decimal longDistance, decimal shortDistance)
	{
		_samplesCount++;
		
		// Simple calculation of running average and standard deviation
		if (_samplesCount == 1)
		{
			// Initialize with first values
			_avgDistanceLong = longDistance;
			_avgDistanceShort = shortDistance;
			_stdDevDistanceLong = 0;
			_stdDevDistanceShort = 0;
		}
		else
		{
			// Update running average
			decimal oldAvgLong = _avgDistanceLong;
			decimal oldAvgShort = _avgDistanceShort;
			
			_avgDistanceLong = oldAvgLong + (longDistance - oldAvgLong) / _samplesCount;
			_avgDistanceShort = oldAvgShort + (shortDistance - oldAvgShort) / _samplesCount;
			
			// Update running standard deviation using Welford's algorithm
			if (_samplesCount > 1)
			{
				_stdDevDistanceLong = (1 - 1.0m / (_samplesCount - 1)) * _stdDevDistanceLong + 
									   _samplesCount * ((_avgDistanceLong - oldAvgLong) * (_avgDistanceLong - oldAvgLong));
				
				_stdDevDistanceShort = (1 - 1.0m / (_samplesCount - 1)) * _stdDevDistanceShort + 
										_samplesCount * ((_avgDistanceShort - oldAvgShort) * (_avgDistanceShort - oldAvgShort));
			}
			
			// We only need last LookbackPeriod samples
			if (_samplesCount > LookbackPeriod)
			{
				_samplesCount = LookbackPeriod;
			}
		}
		
		// Calculate square root for final standard deviation
		_stdDevDistanceLong = (decimal)Math.Sqrt((double)_stdDevDistanceLong / _samplesCount);
		_stdDevDistanceShort = (decimal)Math.Sqrt((double)_stdDevDistanceShort / _samplesCount);
	}
}