English EN
View on GitHub

Volume Mean Reversion Strategy

This system looks for unusually high or low trading volume relative to its historical average. Significant volume spikes often revert as activity normalizes, offering potential fade trades.

Testing indicates an average annual return of about 76%. It performs best in the forex market.

A long entry is made when volume drops below the average minus DeviationMultiplier times the standard deviation and price is below the moving average. A short entry occurs when volume rises above the upper band with price above the average. Trades exit once volume returns toward its mean level.

The strategy benefits traders who watch for exhaustion after volume surges. A percentage stop-loss guards against scenarios where volume keeps expanding in the same direction.

Details

  • Entry Criteria:
    • Long: Volume < Avg - DeviationMultiplier * StdDev && Close < MA
    • Short: Volume > Avg + DeviationMultiplier * StdDev && Close > MA
  • Long/Short: Both sides.
  • Exit Criteria:
    • Long: Exit when volume > Avg
    • Short: Exit when volume < Avg
  • Stops: Yes, percent stop-loss.
  • Default Values:
    • AveragePeriod = 20
    • DeviationMultiplier = 2m
    • CandleType = TimeSpan.FromMinutes(5)
    • StopLossPercent = 2m
  • Filters:
    • Category: Mean Reversion
    • Direction: Both
    • Indicators: Volume
    • Stops: Yes
    • Complexity: Intermediate
    • Timeframe: Intraday
    • Seasonality: No
    • Neural networks: No
    • Divergence: No
    • Risk Level: Medium
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;
			}
		}
	}
}