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成交量均值回归策略

该策略关注成交量相对其历史均值的异常高低。巨大成交量峰值往往在活动恢复正常后回落，提供逆势交易机会。

测试表明年均收益约为 76%，该策略在外汇市场表现最佳。

当成交量低于均值减 DeviationMultiplier 倍标准差且价格在均线下方时做多；当成交量高于上轨并且价格位于均线之上时做空。成交量回到均值附近即平仓。

此方法适合关注放量后的衰减行情，百分比止损可避免成交量持续扩大时产生过大损失。

详细信息

  • 入场条件:
    • 做多: Volume < Avg - DeviationMultiplier * StdDev && Close < MA
    • 做空: Volume > Avg + DeviationMultiplier * StdDev && Close > MA
  • 多空方向: 双向
  • 退出条件:
    • 做多: Exit when volume > Avg
    • 做空: Exit when volume < Avg
  • 止损: 是
  • 默认值:
    • AveragePeriod = 20
    • DeviationMultiplier = 2m
    • CandleType = TimeSpan.FromMinutes(5)
    • StopLossPercent = 2m
  • 筛选条件:
    • 类别: 均值回归
    • 方向: 双向
    • 指标: Volume
    • 止损: 是
    • 复杂度: 中等
    • 时间框架: 日内
    • 季节性: 否
    • 神经网络: 否
    • 背离: 否
    • 风险等级: 中等
namespace StockSharp.Samples.Strategies;

using System;
using System.Collections.Generic;

using Ecng.Common;

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

/// <summary>
/// Volume Mean Reversion strategy.
/// This strategy enters positions when trading volume is significantly below or above its average value.
/// </summary>
public class VolumeMeanReversionStrategy : Strategy
{
	private readonly StrategyParam<int> _averagePeriod;
	private readonly StrategyParam<decimal> _deviationMultiplier;
	private readonly StrategyParam<DataType> _candleType;
	private readonly StrategyParam<decimal> _stopLossPercent;

	private decimal _avgVolume;
	private decimal _stdDevVolume;
	private decimal _sumVolume;
	private decimal _sumSquaresVolume;
	private int _count;
	private readonly Queue<decimal> _volumeValues = [];

	/// <summary>
	/// Period for calculating mean and standard deviation of Volume.
	/// </summary>
	public int AveragePeriod
	{
		get => _averagePeriod.Value;
		set => _averagePeriod.Value = value;
	}

	/// <summary>
	/// Deviation multiplier for entry signals.
	/// </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>
	/// Stop-loss percentage.
	/// </summary>
	public decimal StopLossPercent
	{
		get => _stopLossPercent.Value;
		set => _stopLossPercent.Value = value;
	}

	/// <summary>
	/// Constructor.
	/// </summary>
	public VolumeMeanReversionStrategy()
	{
		_averagePeriod = Param(nameof(AveragePeriod), 20)
			.SetGreaterThanZero()
			
			.SetOptimize(10, 50, 10)
			.SetDisplay("Average Period", "Period for calculating Volume average and standard deviation", "Settings");

		_deviationMultiplier = Param(nameof(DeviationMultiplier), 2m)
			.SetGreaterThanZero()
			
			.SetOptimize(1.5m, 3m, 0.5m)
			.SetDisplay("Deviation Multiplier", "Multiplier for standard deviation", "Settings");

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

		_stopLossPercent = Param(nameof(StopLossPercent), 2m)
			.SetGreaterThanZero()
			
			.SetOptimize(1m, 3m, 0.5m)
			.SetDisplay("Stop Loss %", "Stop loss as percentage of entry price", "Risk Management");
	}

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

		_avgVolume = 0;
		_stdDevVolume = 0;
		_sumVolume = 0;
		_sumSquaresVolume = 0;
		_count = 0;
		_volumeValues.Clear();
	}


	/// <inheritdoc />
	protected override void OnStarted2(DateTime time)
	{
		// Create Volume indicator (for visualization)
		var volume = new VolumeIndicator();

		// Create subscription
		var subscription = SubscribeCandles(CandleType);
		subscription
			.Bind(ProcessCandle)
			.Start();

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

			// Create additional area for volume
			var volumeArea = CreateChartArea();
			if (volumeArea != null)
				DrawIndicator(volumeArea, volume);
		}

		// Enable position protection
		StartProtection(
			takeProfit: new Unit(0m), // We'll manage exits ourselves based on Volume
			stopLoss: new Unit(StopLossPercent, UnitTypes.Percent)
		);

		base.OnStarted2(time);
	}

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

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

		// Extract Volume value (for candles, this is TotalVolume)
		var currentVolume = candle.TotalVolume;

		// Update Volume statistics
		UpdateVolumeStatistics(currentVolume);

		// If we don't have enough data yet for statistics
		if (_count < AveragePeriod)
			return;

		// For volume-based strategies, price direction is important
		var priceDirection = candle.ClosePrice > candle.OpenPrice ? Sides.Buy : Sides.Sell;

		// Check for entry conditions
		if (Position == 0)
		{
			// Volume is significantly below average - expecting a return to average trading activity
			if (currentVolume < _avgVolume - DeviationMultiplier * _stdDevVolume)
			{
				// In low volume environments, we might look for potential market accumulation
				// and follow the small price movement which could be institutional accumulation
				if (priceDirection == Sides.Buy)
				{
					BuyMarket(Volume);
					LogInfo($"Long entry: Volume = {currentVolume}, Avg = {_avgVolume}, StdDev = {_stdDevVolume}, Low volume with price up");
				}
				else
				{
					SellMarket(Volume);
					LogInfo($"Short entry: Volume = {currentVolume}, Avg = {_avgVolume}, StdDev = {_stdDevVolume}, Low volume with price down");
				}
			}
			// Volume is significantly above average - potential high volume climax
			else if (currentVolume > _avgVolume + DeviationMultiplier * _stdDevVolume)
			{
				// High volume often indicates climactic moves that might reverse
				// So we consider going against the price direction on high volume bars
				if (priceDirection == Sides.Sell)
				{
					BuyMarket(Volume);
					LogInfo($"Contrarian long entry: Volume = {currentVolume}, Avg = {_avgVolume}, StdDev = {_stdDevVolume}, High volume with price down");
				}
				else
				{
					SellMarket(Volume);
					LogInfo($"Contrarian short entry: Volume = {currentVolume}, Avg = {_avgVolume}, StdDev = {_stdDevVolume}, High volume with price up");
				}
			}
		}
		// Check for exit conditions
		else if (Position > 0) // Long position
		{
			// Exit long position when volume returns to average
			if (currentVolume > _avgVolume || (currentVolume > _avgVolume * 0.8m && priceDirection == Sides.Sell))
			{
				ClosePosition();
				LogInfo($"Long exit: Volume = {currentVolume}, Avg = {_avgVolume}");
			}
		}
		else if (Position < 0) // Short position
		{
			// Exit short position when volume returns to average
			if (currentVolume > _avgVolume || (currentVolume > _avgVolume * 0.8m && priceDirection == Sides.Buy))
			{
				ClosePosition();
				LogInfo($"Short exit: Volume = {currentVolume}, Avg = {_avgVolume}");
			}
		}
	}

	private void UpdateVolumeStatistics(decimal currentVolume)
	{
		// Add current value to the queue
		_volumeValues.Enqueue(currentVolume);
		_sumVolume += currentVolume;
		_sumSquaresVolume += currentVolume * currentVolume;
		_count++;

		// If queue is larger than period, remove oldest value
		if (_volumeValues.Count > AveragePeriod)
		{
			var oldestVolume = _volumeValues.Dequeue();
			_sumVolume -= oldestVolume;
			_sumSquaresVolume -= oldestVolume * oldestVolume;
			_count--;
		}

		// Calculate average and standard deviation
		if (_count > 0)
		{
			_avgVolume = _sumVolume / _count;
			
			if (_count > 1)
			{
				var variance = (_sumSquaresVolume - (_sumVolume * _sumVolume) / _count) / (_count - 1);
				_stdDevVolume = variance <= 0 ? 0 : (decimal)Math.Sqrt((double)variance);
			}
			else
			{
				_stdDevVolume = 0;
			}
		}
	}
}