成交量突破策略
本策略观察成交量的快速扩张。当读数远高于平均水平时,价格往往酝酿新的走势。
测试表明年均收益约为 103%,该策略在股票市场表现最佳。
当成交量突破依据历史数据及偏差倍数构建的通道时进场,可做多或做空,并配合止损。成交量回到均值附近即离场。
适合寻求早期突破的动量交易者。
详细信息
- 入场条件: Indicator exceeds average by deviation multiplier.
- Long/Short: 双向 directions.
- 退出条件: Indicator reverts to average.
- 止损: 是
- 默认值:
AvgPeriod= 20Multiplier= 2CandleType= TimeSpan.FromMinutes(5)StopLossPercent= 2 Avg和StdDev为最近AvgPeriod个成交量值(含当前值)的平均值和标准差。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。通道为平均值加Multiplier倍标准差:成交量在阳线上突破通道时做多,在阴线上突破时做空;成交量回落到平均值以下时平仓。与持仓方向相反的入场信号会反转持仓。
- 筛选条件:
- 类别: 突破
- 方向: 双向
- 指标: Volume
- 止损: 是
- 复杂度: 中等
- 时间框架: 短期
- 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 Breakout strategy.
/// The bands lie Multiplier standard deviations around the average of the last AvgPeriod volume values, the current one included.
/// volume above the upper band on a rising candle goes long and on a falling candle goes short, reversing an opposite position.
/// A position closes once volume falls back below its average, and a percent stop limits the loss.
/// </summary>
public class VolumeBreakoutStrategy : Strategy
{
private readonly StrategyParam<int> _avgPeriod;
private readonly StrategyParam<decimal> _multiplier;
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 AvgPeriod
{
get => _avgPeriod.Value;
set => _avgPeriod.Value = value;
}
/// <summary>
/// Standard deviations between the average and a band.
/// </summary>
public decimal Multiplier
{
get => _multiplier.Value;
set => _multiplier.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 VolumeBreakoutStrategy()
{
_avgPeriod = Param(nameof(AvgPeriod), 20)
.SetGreaterThanZero()
.SetDisplay("Average Period", "Values of volume the average and the standard deviation span", "Indicators");
_multiplier = Param(nameof(Multiplier), 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 subscription = SubscribeCandles(CandleType);
subscription
.Bind(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);
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)
{
if (candle.State != CandleStates.Finished)
return;
var value = candle.TotalVolume;
_values.Enqueue(value);
if (_values.Count > AvgPeriod)
_values.Dequeue();
if (_values.Count < AvgPeriod)
return;
if (!IsFormedAndOnlineAndAllowTrading())
return;
var mean = _values.Average();
var deviation = (decimal)Math.Sqrt((double)_values.Average(v => (v - mean) * (v - mean)));
var upper = mean + Multiplier * deviation;
if (value > upper && candle.ClosePrice > candle.OpenPrice && Position <= 0)
BuyMarket(Volume + Math.Abs(Position));
else if (value > upper && candle.ClosePrice < candle.OpenPrice && 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.Strategies import Strategy
class volume_breakout_strategy(Strategy):
"""
Volume Breakout strategy.
The bands lie Multiplier standard deviations around the average of the last AvgPeriod volume values, the current one included.
volume above the upper band on a rising candle goes long and on a falling candle goes short, reversing an opposite position.
A position closes once volume falls back below its average, and a percent stop limits the loss.
"""
def __init__(self):
super(volume_breakout_strategy, self).__init__()
self._avg_period = self.Param("AvgPeriod", 20).SetGreaterThanZero().SetDisplay("Average Period", "Values of volume the average and the standard deviation span", "Indicators")
self._multiplier = self.Param("Multiplier", 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_breakout_strategy, self).OnReseted()
self._reset_state()
def OnStarted2(self, time):
super(volume_breakout_strategy, self).OnStarted2(time)
self._reset_state()
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(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.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):
if candle.State != CandleStates.Finished:
return
value = candle.TotalVolume
period = self._avg_period.Value
self._values.append(value)
if len(self._values) > period:
self._values.pop(0)
if len(self._values) < period:
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._multiplier.Value)
upper = mean + multiplier * deviation
if value > upper and candle.ClosePrice > candle.OpenPrice and self.Position <= 0:
self.BuyMarket(self.Volume + abs(self.Position))
elif value > upper and candle.ClosePrice < candle.OpenPrice 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_breakout_strategy()