中文 ZH
在 GitHub 上查看

VWAP Behavioral Bias Filter

VWAP Behavioral Bias Filter 策略基于 VWAP Behavioral Bias Filter。

测试表明年均收益约为 124%，该策略在外汇市场表现最佳。

当 Behavioral confirms filtered entries 在日内（5m）数据上得到确认时触发信号，适合积极交易者。

止损依赖于 ATR 倍数以及 BiasThreshold, BiasWindowSize 等参数，可根据需要调整以平衡风险与收益。

详情

  • 入场条件：参见指标条件实现.
  • 多空方向：双向.
  • 退出条件：反向信号或止损逻辑.
  • 止损：是，基于指标计算.
  • 默认值:
    • BiasThreshold = 0.5m
    • BiasWindowSize = 20
    • StopLoss = 2m
    • CandleType = TimeSpan.FromMinutes(5).TimeFrame()
  • 过滤器:
    • 分类: 趋势跟随
    • 方向: 双向
    • 指标: Behavioral, Bias
    • 止损: 是
    • 复杂度: 中等
    • 时间框架: 日内 (5m)
    • 季节性: 否
    • 神经网络: 否
    • 背离: 否
    • 风险等级: 中等
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>
/// VWAP with Behavioral Bias Filter strategy.
/// Entry condition:
/// Long: Price < VWAP && Bias_Score < -Threshold (oversold with panic)
/// Short: Price > VWAP && Bias_Score > Threshold (overbought with euphoria)
/// Exit condition:
/// Long: Price > VWAP
/// Short: Price < VWAP
/// </summary>
public class VwapWithBehavioralBiasFilterStrategy : Strategy
{
	private static readonly object _biasSync = new();

	private readonly StrategyParam<decimal> _biasThreshold;
	private readonly StrategyParam<int> _biasWindowSize;
	private readonly StrategyParam<decimal> _stopLoss;
	private readonly StrategyParam<DataType> _candleType;

	private VolumeWeightedMovingAverage _vwap;
	private decimal _currentBiasScore;

	// Tracks recent price movements for bias calculation
	private readonly Queue<decimal> _recentPriceMovements = [];

	// Flags to track positions
	private bool _isLong;
	private bool _isShort;

	/// <summary>
	/// Behavioral bias threshold for entry signal.
	/// </summary>
	public decimal BiasThreshold
	{
		get => _biasThreshold.Value;
		set => _biasThreshold.Value = value;
	}

	/// <summary>
	/// Window size for behavioral bias calculation.
	/// </summary>
	public int BiasWindowSize
	{
		get => _biasWindowSize.Value;
		set => _biasWindowSize.Value = value;
	}

	/// <summary>
	/// Stop loss percentage.
	/// </summary>
	public decimal StopLoss
	{
		get => _stopLoss.Value;
		set => _stopLoss.Value = value;
	}

	/// <summary>
	/// Type of candles to use.
	/// </summary>
	public DataType CandleType
	{
		get => _candleType.Value;
		set => _candleType.Value = value;
	}

	/// <summary>
	/// Constructor with default parameters.
	/// </summary>
	public VwapWithBehavioralBiasFilterStrategy()
	{
		_biasThreshold = Param(nameof(BiasThreshold), 0.5m)
		.SetGreaterThanZero()
		.SetDisplay("Bias Threshold", "Threshold for behavioral bias", "Behavioral Settings")
		
		.SetOptimize(0.3m, 0.7m, 0.1m);

		_biasWindowSize = Param(nameof(BiasWindowSize), 20)
		.SetGreaterThanZero()
		.SetDisplay("Bias Window Size", "Window size for behavioral bias calculation", "Behavioral Settings")
		
		.SetOptimize(10, 30, 5);

		_stopLoss = Param(nameof(StopLoss), 2m)
		.SetGreaterThanZero()
		.SetDisplay("Stop Loss (%)", "Stop Loss percentage from entry price", "Risk Management")
		
		.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();

		_isLong = false;
		_isShort = false;
		_currentBiasScore = 0;
		_recentPriceMovements.Clear();
		_vwap = default;
	}

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

		// Initialize VWAP indicator
		_vwap = new();

		// Subscribe to candles and bind indicator
		var subscription = SubscribeCandles(CandleType);

		subscription
		.Bind(_vwap, ProcessCandle)
		.Start();

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

		// Enable position protection with stop-loss
		StartProtection(
		new Unit(0),  // No take profit
		new Unit(StopLoss, UnitTypes.Percent) // Stop-loss as percentage
		);
	}

	/// <summary>
	/// Process each candle and VWAP value.
	/// </summary>
	private void ProcessCandle(ICandleMessage candle, decimal vwapValue)
	{
		// Skip unfinished candles
		if (candle.State != CandleStates.Finished)
		return;

		// Check if strategy is ready to trade
		if (!IsFormedAndOnlineAndAllowTrading())
		return;

		// Update behavioral bias score
		UpdateBehavioralBias(candle);

		var price = candle.ClosePrice;
		var priceBelowVwap = price < vwapValue;
		var priceAboveVwap = price > vwapValue;

		// Trading logic

		// Entry conditions

		// Long entry: Price below VWAP and negative bias score (panic)
		if (priceBelowVwap && _currentBiasScore < -BiasThreshold && !_isLong && Position <= 0)
		{
			LogInfo($"Long signal: Price {price} < VWAP {vwapValue}, Bias {_currentBiasScore} < -Threshold {-BiasThreshold}");
			BuyMarket(Volume);
			_isLong = true;
			_isShort = false;
		}
		// Short entry: Price above VWAP and positive bias score (euphoria)
		else if (priceAboveVwap && _currentBiasScore > BiasThreshold && !_isShort && Position >= 0)
		{
			LogInfo($"Short signal: Price {price} > VWAP {vwapValue}, Bias {_currentBiasScore} > Threshold {BiasThreshold}");
			SellMarket(Volume);
			_isShort = true;
			_isLong = false;
		}

		// Exit conditions

		// Exit long: Price rises above VWAP
		if (_isLong && priceAboveVwap && Position > 0)
		{
			LogInfo($"Exit long: Price {price} > VWAP {vwapValue}");
			SellMarket(Math.Abs(Position));
			_isLong = false;
		}
		// Exit short: Price falls below VWAP
		else if (_isShort && priceBelowVwap && Position < 0)
		{
			LogInfo($"Exit short: Price {price} < VWAP {vwapValue}");
			BuyMarket(Math.Abs(Position));
			_isShort = false;
		}
	}

	/// <summary>
	/// Update behavioral bias score based on recent price movements.
	/// This is a simplified model of behavioral biases in markets.
	/// </summary>
	private void UpdateBehavioralBias(ICandleMessage candle)
	{
		lock (_biasSync)
		{
			// Calculate price movement %
			decimal priceChange = 0;
			if (candle.OpenPrice != 0)
			{
				priceChange = (candle.ClosePrice - candle.OpenPrice) / candle.OpenPrice * 100;
			}

			// Add to queue
			_recentPriceMovements.Enqueue(priceChange);

			// Maintain window size
			while (_recentPriceMovements.Count > BiasWindowSize)
			{
				_recentPriceMovements.Dequeue();
			}

			// Not enough data yet
			if (_recentPriceMovements.Count < 5)
			{
				_currentBiasScore = 0;
				return;
			}

			var movements = _recentPriceMovements.ToArray();

			// Calculate various components of bias score
			decimal recentMovement = 0;
			for (var i = Math.Max(0, movements.Length - 5); i < movements.Length; i++)
				recentMovement += movements[i];

			decimal sum = 0;
			decimal sumSquared = 0;

			foreach (var movement in movements)
			{
				sum += movement;
				sumSquared += movement * movement;
			}

			var avg = sum / movements.Length;
			var variance = (sumSquared / movements.Length) - (avg * avg);
			var volatility = (decimal)Math.Sqrt((double)Math.Max(0, variance));

			decimal previousMove = 0;
			int consecutiveSameDirection = 0;
			int maxConsecutive = 0;

			foreach (var movement in movements)
			{
				if (previousMove != 0 && Math.Sign(movement) == Math.Sign(previousMove))
				{
					consecutiveSameDirection++;
					maxConsecutive = Math.Max(maxConsecutive, consecutiveSameDirection);
				}
				else
				{
					consecutiveSameDirection = 0;
				}

				previousMove = movement;
			}

			decimal bodySize = Math.Abs(candle.ClosePrice - candle.OpenPrice);
			decimal totalSize = candle.HighPrice - candle.LowPrice;
			decimal bodyRatio = totalSize > 0 ? bodySize / totalSize : 0;

			_currentBiasScore = 0;
			_currentBiasScore += Math.Min(0.5m, Math.Max(-0.5m, recentMovement / 2));
			_currentBiasScore += Math.Sign(recentMovement) * Math.Min(0.3m, volatility / 10);
			_currentBiasScore += Math.Sign(recentMovement) * Math.Min(0.2m, maxConsecutive / 10.0m);

			if (candle.ClosePrice > candle.OpenPrice)
				_currentBiasScore += bodyRatio * 0.2m;
			else
				_currentBiasScore -= bodyRatio * 0.2m;

			_currentBiasScore = Math.Max(-1.0m, Math.Min(1.0m, _currentBiasScore));

			LogInfo($"Behavioral Bias: {_currentBiasScore}, Components: Momentum={recentMovement/2}, Volatility={volatility/10}, Herding={maxConsecutive/10.0m}, Candle={bodyRatio*0.2m}");
		}
	}
}