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 = 2
CandleType = TimeSpan.FromMinutes(5)
StopLossPercent = 2
Avg and StdDev are the average and the standard deviation of the last AveragePeriod volume values, the current one included, and MA is the simple moving average of the last AveragePeriod closes. The stop is a fixed StopLossPercent of the entry price, watched between candles as well; 0 disables it. An entry signal against an open position reverses it.
- Filters:
- Category: Mean Reversion
- Direction: Both
- Indicators: Volume
- Stops: Yes
- Complexity: Intermediate
- Timeframe: Intraday
- Seasonality: No
- Neural networks: No
- Divergence: No
- Risk Level: Medium
using System;
using System.Collections.Generic;
using System.Linq;
using Ecng.Common;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
/// <summary>
/// Volume Mean Reversion strategy.
/// The bands lie DeviationMultiplier standard deviations around the average of the last AveragePeriod volume values, the current one included.
/// volume below the lower band with the close below the AveragePeriod simple moving average goes long and volume above the upper band with the close above it goes short,
/// reversing an opposite position. A long closes once volume is back above its average and a short once it is back below it, and a percent stop limits the loss.
/// </summary>
public class VolumeMeanReversionStrategy : Strategy
{
private readonly StrategyParam<int> _averagePeriod;
private readonly StrategyParam<decimal> _deviationMultiplier;
private readonly StrategyParam<decimal> _stopLossPercent;
private readonly StrategyParam<DataType> _candleType;
private readonly Queue<decimal> _values = [];
/// <summary>
/// Values of volume the average and the standard deviation span.
/// </summary>
public int AveragePeriod
{
get => _averagePeriod.Value;
set => _averagePeriod.Value = value;
}
/// <summary>
/// Standard deviations between the average and a band.
/// </summary>
public decimal DeviationMultiplier
{
get => _deviationMultiplier.Value;
set => _deviationMultiplier.Value = value;
}
/// <summary>
/// Stop loss percentage from entry price.
/// </summary>
public decimal StopLossPercent
{
get => _stopLossPercent.Value;
set => _stopLossPercent.Value = value;
}
/// <summary>
/// Candle type.
/// </summary>
public DataType CandleType
{
get => _candleType.Value;
set => _candleType.Value = value;
}
/// <summary>
/// Constructor.
/// </summary>
public VolumeMeanReversionStrategy()
{
_averagePeriod = Param(nameof(AveragePeriod), 20)
.SetGreaterThanZero()
.SetDisplay("Average Period", "Values of volume the average and the standard deviation span", "Indicators");
_deviationMultiplier = Param(nameof(DeviationMultiplier), 2m)
.SetGreaterThanZero()
.SetDisplay("Multiplier", "Standard deviations between the average and a band", "Indicators");
_stopLossPercent = Param(nameof(StopLossPercent), 2m)
.SetNotNegative()
.SetDisplay("Stop Loss %", "Stop loss percentage from entry price", "Risk");
_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();
_values.Clear();
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_values.Clear();
var sma = new SimpleMovingAverage { Length = AveragePeriod };
var subscription = SubscribeCandles(CandleType);
subscription
.BindEx(sma, ProcessCandle)
.Start();
StartProtection(new Unit(), new Unit(StopLossPercent, UnitTypes.Percent), useMarketOrders: true, isLocalStop: true);
// The stop has to see prices between candles, not only at their close.
foreach (var field in new[] { Level1Fields.BestBidPrice, Level1Fields.BestAskPrice })
{
var quotes = new Subscription(DataType.Level1, Security);
quotes.MarketData.BuildField = field;
SubscribeLevel1(quotes).Bind(ObserveProtectionQuote).Start();
}
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawIndicator(area, sma);
DrawOwnTrades(area);
}
}
private void ObserveProtectionQuote(Level1ChangeMessage quote)
{
// The high-level handler activates native protection before this callback, also between signal bars.
}
private void ProcessCandle(ICandleMessage candle, IIndicatorValue smaValue)
{
if (candle.State != CandleStates.Finished)
return;
var value = candle.TotalVolume;
_values.Enqueue(value);
if (_values.Count > AveragePeriod)
_values.Dequeue();
if (_values.Count < AveragePeriod || !smaValue.IsFormed)
return;
if (!IsFormedAndOnlineAndAllowTrading())
return;
var mean = _values.Average();
var deviation = (decimal)Math.Sqrt((double)_values.Average(v => (v - mean) * (v - mean)));
var upper = mean + DeviationMultiplier * deviation;
var lower = mean - DeviationMultiplier * deviation;
var close = candle.ClosePrice;
var ma = smaValue.GetValue<decimal>();
if (value < lower && close < ma && Position <= 0)
BuyMarket(Volume + Math.Abs(Position));
else if (value > upper && close > ma && Position >= 0)
SellMarket(Volume + Math.Abs(Position));
else if (Position > 0 && value > mean)
SellMarket(Position);
else if (Position < 0 && value < mean)
BuyMarket(-Position);
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")
clr.AddReference("StockSharp.BusinessEntities")
from System import TimeSpan, Decimal, Math
from StockSharp.Messages import DataType, CandleStates, Unit, UnitTypes, Level1Fields
from StockSharp.BusinessEntities import Subscription
from StockSharp.Algo.Indicators import SimpleMovingAverage
from StockSharp.Algo.Strategies import Strategy
class volume_mean_reversion_strategy(Strategy):
"""
Volume Mean Reversion strategy.
The bands lie DeviationMultiplier standard deviations around the average of the last AveragePeriod volume values, the current one included.
volume below the lower band with the close below the AveragePeriod simple moving average goes long and volume above the upper band with the close above it goes short,
reversing an opposite position. A long closes once volume is back above its average and a short once it is back below it, and a percent stop limits the loss.
"""
def __init__(self):
super(volume_mean_reversion_strategy, self).__init__()
self._average_period = self.Param("AveragePeriod", 20).SetGreaterThanZero().SetDisplay("Average Period", "Values of volume the average and the standard deviation span", "Indicators")
self._deviation_multiplier = self.Param("DeviationMultiplier", 2.0).SetGreaterThanZero().SetDisplay("Multiplier", "Standard deviations between the average and a band", "Indicators")
self._stop_loss_percent = self.Param("StopLossPercent", 2.0).SetNotNegative().SetDisplay("Stop Loss %", "Stop loss percentage from entry price", "Risk")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(5))).SetDisplay("Candle Type", "Type of candles to use", "General")
self._reset_state()
@property
def candle_type(self):
return self._candle_type.Value
def _reset_state(self):
self._values = []
def OnReseted(self):
super(volume_mean_reversion_strategy, self).OnReseted()
self._reset_state()
def OnStarted2(self, time):
super(volume_mean_reversion_strategy, self).OnStarted2(time)
self._reset_state()
sma = SimpleMovingAverage()
sma.Length = self._average_period.Value
subscription = self.SubscribeCandles(self.candle_type)
subscription.BindEx(sma, self._process_candle).Start()
self.StartProtection(Unit(), Unit(Decimal(self._stop_loss_percent.Value), UnitTypes.Percent), useMarketOrders=True, isLocalStop=True)
# The stop has to see prices between candles, not only at their close.
for field in (Level1Fields.BestBidPrice, Level1Fields.BestAskPrice):
quotes = Subscription(DataType.Level1, self.Security)
quotes.MarketData.BuildField = field
self.SubscribeLevel1(quotes).Bind(self._observe_protection_quote).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawIndicator(area, sma)
self.DrawOwnTrades(area)
def _observe_protection_quote(self, quote):
# The high-level handler activates native protection before the callback, including between bars.
pass
def _process_candle(self, candle, sma_value):
if candle.State != CandleStates.Finished:
return
value = candle.TotalVolume
period = self._average_period.Value
self._values.append(value)
if len(self._values) > period:
self._values.pop(0)
if len(self._values) < period or not sma_value.IsFormed:
return
if not self.IsFormedAndOnlineAndAllowTrading():
return
total = Decimal(0)
for item in self._values:
total += item
mean = total / Decimal(period)
squares = Decimal(0)
for item in self._values:
squares += (item - mean) * (item - mean)
deviation = Decimal(Math.Sqrt(Decimal.ToDouble(squares / Decimal(period))))
multiplier = Decimal(self._deviation_multiplier.Value)
upper = mean + multiplier * deviation
lower = mean - multiplier * deviation
close = candle.ClosePrice
ma = sma_value.GetValue[Decimal](None)
if value < lower and close < ma and self.Position <= 0:
self.BuyMarket(self.Volume + abs(self.Position))
elif value > upper and close > ma and self.Position >= 0:
self.SellMarket(self.Volume + abs(self.Position))
elif self.Position > 0 and value > mean:
self.SellMarket(self.Position)
elif self.Position < 0 and value < mean:
self.BuyMarket(-self.Position)
def CreateClone(self):
return volume_mean_reversion_strategy()