成交量枯竭策略
成交量的剧烈飙升常标志着行情的终结,因为交易者急于进出场。本策略将当前成交量与平均值比较以发现枯竭现象,结合蜡烛方向与均线过滤,寻找反转入场点。
测试表明年均收益约为 133%,该策略在加密市场表现最佳。
每根K线更新平均成交量。当新柱的成交量超过平均值的设定倍数,且蜡烛收盘方向与当前趋势相反时,系统入场交易,并以ATR为基础设定止损。
该策略预期在量能爆发后出现迅速反转,因此通常通过止损退出。
细节
- 入场条件:成交量较平均值激增,且蜡烛方向与趋势相反。
- 多/空:双向。
- 退出条件:止损。
- 止损:有,基于 ATR。
- 默认值:
VolumePeriod= 20VolumeMultiplier= 2.0MAPeriod= 20AtrMultiplier= 2 ATRCandleType= 5 分钟
- 过滤条件:
- 类别: 反转
- 方向: 双向
- 指标: 成交量, 均线, ATR
- 止损: 有
- 复杂度: 中等
- 时间框架: 日内
- 季节性: 无
- 神经网络: 无
- 背离: 无
- 风险级别: 中等
using System;
using System.Collections.Generic;
using Ecng.Common;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
/// <summary>
/// Volume Exhaustion strategy.
/// Looks for volume spikes (current volume much higher than previous) with directional candles.
/// High volume + bullish above SMA = buy.
/// High volume + bearish below SMA = sell.
/// Exits when price crosses SMA in opposite direction.
/// </summary>
public class VolumeExhaustionStrategy : Strategy
{
private readonly StrategyParam<int> _maPeriod;
private readonly StrategyParam<DataType> _candleType;
private readonly StrategyParam<int> _cooldownBars;
private decimal _prevVolume;
private int _cooldown;
/// <summary>
/// MA Period.
/// </summary>
public int MAPeriod
{
get => _maPeriod.Value;
set => _maPeriod.Value = value;
}
/// <summary>
/// Candle type.
/// </summary>
public DataType CandleType
{
get => _candleType.Value;
set => _candleType.Value = value;
}
/// <summary>
/// Cooldown bars.
/// </summary>
public int CooldownBars
{
get => _cooldownBars.Value;
set => _cooldownBars.Value = value;
}
/// <summary>
/// Constructor.
/// </summary>
public VolumeExhaustionStrategy()
{
_maPeriod = Param(nameof(MAPeriod), 20)
.SetGreaterThanZero()
.SetDisplay("MA Period", "Period for SMA", "Indicators");
_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(1).TimeFrame())
.SetDisplay("Candle Type", "Type of candles to use", "General");
_cooldownBars = Param(nameof(CooldownBars), 500)
.SetRange(1, 1000)
.SetDisplay("Cooldown Bars", "Bars to wait between trades", "General");
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_prevVolume = default;
_cooldown = default;
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_prevVolume = 0;
_cooldown = 0;
var sma = new SimpleMovingAverage { Length = MAPeriod };
var subscription = SubscribeCandles(CandleType);
subscription
.Bind(sma, ProcessCandle)
.Start();
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawIndicator(area, sma);
DrawOwnTrades(area);
}
}
private void ProcessCandle(ICandleMessage candle, decimal smaValue)
{
if (candle.State != CandleStates.Finished)
return;
if (!IsFormedAndOnlineAndAllowTrading())
{
_prevVolume = candle.TotalVolume;
return;
}
if (_prevVolume == 0)
{
_prevVolume = candle.TotalVolume;
return;
}
if (_cooldown > 0)
{
_cooldown--;
_prevVolume = candle.TotalVolume;
return;
}
// Volume spike: current volume significantly higher than previous
var volumeSpike = _prevVolume > 0 && candle.TotalVolume > _prevVolume * 1.5m;
var isBullish = candle.ClosePrice > candle.OpenPrice;
var isBearish = candle.ClosePrice < candle.OpenPrice;
if (Position == 0 && volumeSpike && isBullish && candle.ClosePrice > smaValue)
{
BuyMarket();
_cooldown = CooldownBars;
}
else if (Position == 0 && volumeSpike && isBearish && candle.ClosePrice < smaValue)
{
SellMarket();
_cooldown = CooldownBars;
}
else if (Position > 0 && candle.ClosePrice < smaValue)
{
SellMarket();
_cooldown = CooldownBars;
}
else if (Position < 0 && candle.ClosePrice > smaValue)
{
BuyMarket();
_cooldown = CooldownBars;
}
_prevVolume = candle.TotalVolume;
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")
from System import TimeSpan
from StockSharp.Messages import DataType, CandleStates
from StockSharp.Algo.Indicators import SimpleMovingAverage
from StockSharp.Algo.Strategies import Strategy
class volume_exhaustion_strategy(Strategy):
"""
Volume Exhaustion strategy.
Looks for volume spikes (current volume much higher than previous) with directional candles.
High volume + bullish above SMA = buy.
High volume + bearish below SMA = sell.
Exits when price crosses SMA in opposite direction.
"""
def __init__(self):
super(volume_exhaustion_strategy, self).__init__()
self._ma_period = self.Param("MAPeriod", 20).SetDisplay("MA Period", "Period for SMA", "Indicators")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(1))).SetDisplay("Candle Type", "Type of candles to use", "General")
self._cooldown_bars = self.Param("CooldownBars", 500).SetDisplay("Cooldown Bars", "Bars to wait between trades", "General")
self._prev_volume = 0.0
self._cooldown = 0
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(volume_exhaustion_strategy, self).OnReseted()
self._prev_volume = 0.0
self._cooldown = 0
def OnStarted2(self, time):
super(volume_exhaustion_strategy, self).OnStarted2(time)
self._prev_volume = 0.0
self._cooldown = 0
sma = SimpleMovingAverage()
sma.Length = self._ma_period.Value
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(sma, self._process_candle).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawIndicator(area, sma)
self.DrawOwnTrades(area)
def _process_candle(self, candle, sma_val):
if candle.State != CandleStates.Finished:
return
if not self.IsFormedAndOnlineAndAllowTrading():
self._prev_volume = float(candle.TotalVolume)
return
vol = float(candle.TotalVolume)
if self._prev_volume == 0:
self._prev_volume = vol
return
if self._cooldown > 0:
self._cooldown -= 1
self._prev_volume = vol
return
# Volume spike: current volume significantly higher than previous
volume_spike = self._prev_volume > 0 and vol > self._prev_volume * 1.5
is_bullish = candle.ClosePrice > candle.OpenPrice
is_bearish = candle.ClosePrice < candle.OpenPrice
close = float(candle.ClosePrice)
sv = float(sma_val)
cd = self._cooldown_bars.Value
if self.Position == 0 and volume_spike and is_bullish and close > sv:
self.BuyMarket()
self._cooldown = cd
elif self.Position == 0 and volume_spike and is_bearish and close < sv:
self.SellMarket()
self._cooldown = cd
elif self.Position > 0 and close < sv:
self.SellMarket()
self._cooldown = cd
elif self.Position < 0 and close > sv:
self.BuyMarket()
self._cooldown = cd
self._prev_volume = vol
def CreateClone(self):
return volume_exhaustion_strategy()