ボラティリティ平均回帰戦略
このアプローチは市場ボラティリティの変動を中心に取引します。ATRが移動平均から大きく乖離した場合、ボラティリティが異常に高くなったか低くなったことを示し、回帰する可能性があります。
テストでは平均年間リターンが約73%であることが示されています。暗号資産市場で最も良いパフォーマンスを発揮します。
ATRが平均値からDeviationMultiplier倍の標準偏差を引いた値を下回り、価格が移動平均を下回るときにロングエントリーします。ATRが上部バンドを超え、価格が平均を上回るときにショートエントリーします。ATRが平均水準に戻ったらポジションを決済します。
このようなセットアップは、価格方向ではなくボラティリティの極端な状態に逆張りするトレーダーに適しています。ボラティリティが拡大し続けた場合に備えて保護的なストップロスを使用します。
詳細
- エントリー条件:
- ロング: ATR < Avg - DeviationMultiplier * StdDev && Close < MA
- ショート: ATR > Avg + DeviationMultiplier * StdDev && Close > MA
- ロング/ショート: 両方。
- エグジット条件:
- ロング: ATR > Avg のときに決済
- ショート: ATR < Avg のときに決済
- ストップ: あり、パーセントストップロス。
- デフォルト値:
AtrPeriod= 14AveragePeriod= 20DeviationMultiplier= 2StopLossPercent= 2CandleType= TimeSpan.FromMinutes(5) AvgとStdDevは現在値を含む直近AveragePeriod個のATRの平均と標準偏差です。MAは直近AveragePeriod本の終値の単純移動平均です。 ストップはエントリー価格の固定StopLossPercentで、ローソク足の間も監視されます。0で無効になります。 保有ポジションと逆方向のエントリーシグナルはドテンになります。
- フィルター:
- カテゴリ: 平均回帰
- 方向: 両方
- インジケーター: ATR
- ストップ: あり
- 複雑さ: 中級
- 時間軸: イントラデイ
- 季節性: いいえ
- ニューラルネットワーク: いいえ
- ダイバージェンス: いいえ
- リスクレベル: 中
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>
/// Volatility Mean Reversion strategy.
/// The bands lie DeviationMultiplier standard deviations around the average of the last AveragePeriod ATR values, the current one included.
/// ATR below the lower band with the close below the AveragePeriod simple moving average goes long and ATR above the upper band with the close above it goes short,
/// reversing an opposite position. A long closes once ATR is back above its average and a short once it is back below it, and a percent stop limits the loss.
/// </summary>
public class VolatilityMeanReversionStrategy : Strategy
{
private readonly StrategyParam<int> _atrPeriod;
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>
/// Period of ATR.
/// </summary>
public int AtrPeriod
{
get => _atrPeriod.Value;
set => _atrPeriod.Value = value;
}
/// <summary>
/// Values of ATR 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 VolatilityMeanReversionStrategy()
{
_atrPeriod = Param(nameof(AtrPeriod), 14)
.SetGreaterThanZero()
.SetDisplay("ATR Period", "Period of ATR", "Indicators");
_averagePeriod = Param(nameof(AveragePeriod), 20)
.SetGreaterThanZero()
.SetDisplay("Average Period", "Values of ATR 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 atr = new AverageTrueRange { Length = AtrPeriod };
var sma = new SimpleMovingAverage { Length = AveragePeriod };
var subscription = SubscribeCandles(CandleType);
subscription
.BindEx(atr, 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);
var oscillators = CreateChartArea();
if (oscillators != null)
{
DrawIndicator(oscillators, atr);
}
}
}
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 atrValue, IIndicatorValue smaValue)
{
if (candle.State != CandleStates.Finished)
return;
if (!smaValue.IsFormed)
return;
if (!atrValue.IsFormed)
return;
var value = atrValue.GetValue<decimal>();
_values.Enqueue(value);
if (_values.Count > AveragePeriod)
_values.Dequeue();
if (_values.Count < AveragePeriod)
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 AverageTrueRange, SimpleMovingAverage
from StockSharp.Algo.Strategies import Strategy
class volatility_mean_reversion_strategy(Strategy):
"""
Volatility Mean Reversion strategy.
The bands lie DeviationMultiplier standard deviations around the average of the last AveragePeriod ATR values, the current one included.
ATR below the lower band with the close below the AveragePeriod simple moving average goes long and ATR above the upper band with the close above it goes short,
reversing an opposite position. A long closes once ATR 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(volatility_mean_reversion_strategy, self).__init__()
self._atr_period = self.Param("AtrPeriod", 14).SetGreaterThanZero().SetDisplay("ATR Period", "Period of ATR", "Indicators")
self._average_period = self.Param("AveragePeriod", 20).SetGreaterThanZero().SetDisplay("Average Period", "Values of ATR 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(volatility_mean_reversion_strategy, self).OnReseted()
self._reset_state()
def OnStarted2(self, time):
super(volatility_mean_reversion_strategy, self).OnStarted2(time)
self._reset_state()
atr = AverageTrueRange()
atr.Length = self._atr_period.Value
sma = SimpleMovingAverage()
sma.Length = self._average_period.Value
subscription = self.SubscribeCandles(self.candle_type)
subscription.BindEx(atr, 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)
oscillators = self.CreateChartArea()
if oscillators is not None:
self.DrawIndicator(oscillators, atr)
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, atr_value, sma_value):
if candle.State != CandleStates.Finished:
return
if not sma_value.IsFormed:
return
if not atr_value.IsFormed:
return
value = atr_value.GetValue[Decimal](None)
period = self._average_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._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 volatility_mean_reversion_strategy()