CCI 平均回帰戦略
Commodity Channel Index(CCI)は、価格が統計的平均からどれほど離れているかを測定します。この戦略は、CCIが自身の平均から大きく乖離したときにエントリーし、モメンタムが衰えたら急反発することを期待します。
テストでは年平均リターンは約151%を示しています。株式市場で最もよいパフォーマンスを発揮します。
CCIが平均からDeviationMultiplier倍の標準偏差を差し引いた値を下回ったときにロングトレードを行います。CCIが平均にそのマルチプライヤーを加えた値を上回ったときにショートトレードが建てられます。CCIが平均値を再び越えたときにポジションを決済します。
このシステムは逆張りのセットアップを好む短期トレーダーに適しています。パーセンテージ移動に基づくストップロスが、市場が素早く反転できない場合のリスクを制限するのに役立ちます。
詳細
- エントリー条件:
- ロング: CCI < Avg - DeviationMultiplier * StdDev
- ショート: CCI > Avg + DeviationMultiplier * StdDev
- ロング/ショート: 両方。
- エグジット条件:
- ロング: CCI > Avg のときに決済
- ショート: CCI < Avg のときに決済
- ストップ: あり、パーセンテージストップロス。
- デフォルト値:
CciPeriod= 20AveragePeriod= 20DeviationMultiplier= 2StopLossPercent= 2CandleType= TimeSpan.FromMinutes(5) AvgとStdDevは現在値を含む直近AveragePeriod個のCCIの平均と標準偏差です。 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: CCI
- ストップ: はい
- 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>
/// CCI Mean Reversion strategy.
/// The bands lie DeviationMultiplier standard deviations around the average of the last AveragePeriod CCI values, the current one included.
/// CCI below the lower band goes long and CCI above the upper band goes short,
/// reversing an opposite position. A long closes once CCI is back above its average and a short once it is back below it, and a percent stop limits the loss.
/// </summary>
public class CciMeanReversionStrategy : Strategy
{
private readonly StrategyParam<int> _cciPeriod;
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 CCI.
/// </summary>
public int CciPeriod
{
get => _cciPeriod.Value;
set => _cciPeriod.Value = value;
}
/// <summary>
/// Values of CCI 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 CciMeanReversionStrategy()
{
_cciPeriod = Param(nameof(CciPeriod), 20)
.SetGreaterThanZero()
.SetDisplay("CCI Period", "Period of CCI", "Indicators");
_averagePeriod = Param(nameof(AveragePeriod), 20)
.SetGreaterThanZero()
.SetDisplay("Average Period", "Values of CCI 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 cci = new CommodityChannelIndex { Length = CciPeriod };
var subscription = SubscribeCandles(CandleType);
subscription
.BindEx(cci, 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);
var oscillators = CreateChartArea();
if (oscillators != null)
{
DrawIndicator(oscillators, cci);
}
}
}
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 cciValue)
{
if (candle.State != CandleStates.Finished)
return;
if (!cciValue.IsFormed)
return;
var value = cciValue.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;
if (value < lower && Position <= 0)
BuyMarket(Volume + Math.Abs(Position));
else if (value > upper && 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 CommodityChannelIndex
from StockSharp.Algo.Strategies import Strategy
class cci_mean_reversion_strategy(Strategy):
"""
CCI Mean Reversion strategy.
The bands lie DeviationMultiplier standard deviations around the average of the last AveragePeriod CCI values, the current one included.
CCI below the lower band goes long and CCI above the upper band goes short,
reversing an opposite position. A long closes once CCI 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(cci_mean_reversion_strategy, self).__init__()
self._cci_period = self.Param("CciPeriod", 20).SetGreaterThanZero().SetDisplay("CCI Period", "Period of CCI", "Indicators")
self._average_period = self.Param("AveragePeriod", 20).SetGreaterThanZero().SetDisplay("Average Period", "Values of CCI 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(cci_mean_reversion_strategy, self).OnReseted()
self._reset_state()
def OnStarted2(self, time):
super(cci_mean_reversion_strategy, self).OnStarted2(time)
self._reset_state()
cci = CommodityChannelIndex()
cci.Length = self._cci_period.Value
subscription = self.SubscribeCandles(self.candle_type)
subscription.BindEx(cci, 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)
oscillators = self.CreateChartArea()
if oscillators is not None:
self.DrawIndicator(oscillators, cci)
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, cci_value):
if candle.State != CandleStates.Finished:
return
if not cci_value.IsFormed:
return
value = cci_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
if value < lower and self.Position <= 0:
self.BuyMarket(self.Volume + abs(self.Position))
elif value > upper 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 cci_mean_reversion_strategy()