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= 20DeviationMultiplier= 2CandleType= TimeSpan.FromMinutes(5)StopLossPercent= 2 Avg和StdDev为最近AveragePeriod个成交量值(含当前值)的平均值和标准差,MA为最近AveragePeriod个收盘价的简单移动平均。止损为入场价的固定StopLossPercent百分比,在K线之间同样监控;设为0则关闭。与持仓方向相反的入场信号会反转持仓。
- 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
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()