OBV平均回帰戦略
On Balance Volume(OBV)は累積出来高フローを追跡し、買い手と売り手のどちらが優勢かを判断します。この戦略はOBVが平均から大きく乖離するのを待ち、典型的な水準への回帰を予測して取引します。
テストでは平均年間リターンが約79%であることが示されています。株式市場で最も良いパフォーマンスを発揮します。
OBVがその平均値からMultiplier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買いシグナルが発生します。OBVが上部バンドを超え、価格が平均を上回るときに売りシグナルが生成されます。OBVが平均線を再び交差したらポジションを決済します。
このアプローチは価格行動に加えて出来高フローを考慮するトレーダーに有益です。出来高が加速し続ける状況に対処するため、設定されたパーセンテージにストップを置きます。
詳細
- エントリー条件:
- ロング: OBV < Avg - Multiplier * StdDev && Close < MA
- ショート: OBV > Avg + Multiplier * StdDev && Close > MA
- ロング/ショート: 両方。
- エグジット条件:
- ロング: OBV > Avg のときに決済
- ショート: OBV < 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:
AveragePeriod= 20Multiplier= 2StopLossPercent= 2CandleType= TimeSpan.FromMinutes(5) AvgとStdDevは現在値を含む直近AveragePeriod個のOBV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: OBV
- 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>
/// OBV Mean Reversion strategy.
/// The bands lie Multiplier standard deviations around the average of the last AveragePeriod OBV values, the current one included.
/// OBV below the lower band with the close below the AveragePeriod simple moving average goes long and OBV above the upper band with the close above it goes short,
/// reversing an opposite position. A long closes once OBV is back above its average and a short once it is back below it, and a percent stop limits the loss.
/// </summary>
public class ObvMeanReversionStrategy : Strategy
{
private readonly StrategyParam<int> _averagePeriod;
private readonly StrategyParam<decimal> _multiplier;
private readonly StrategyParam<decimal> _stopLossPercent;
private readonly StrategyParam<DataType> _candleType;
private readonly Queue<decimal> _values = [];
/// <summary>
/// Values of OBV 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 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 ObvMeanReversionStrategy()
{
_averagePeriod = Param(nameof(AveragePeriod), 20)
.SetGreaterThanZero()
.SetDisplay("Average Period", "Values of OBV 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 obv = new OnBalanceVolume();
var sma = new SimpleMovingAverage { Length = AveragePeriod };
var subscription = SubscribeCandles(CandleType);
subscription
.BindEx(obv, 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, obv);
}
}
}
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 obvValue, IIndicatorValue smaValue)
{
if (candle.State != CandleStates.Finished)
return;
if (!smaValue.IsFormed)
return;
if (!obvValue.IsFormed)
return;
var value = obvValue.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 + Multiplier * deviation;
var lower = mean - Multiplier * 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 OnBalanceVolume, SimpleMovingAverage
from StockSharp.Algo.Strategies import Strategy
class obv_mean_reversion_strategy(Strategy):
"""
OBV Mean Reversion strategy.
The bands lie Multiplier standard deviations around the average of the last AveragePeriod OBV values, the current one included.
OBV below the lower band with the close below the AveragePeriod simple moving average goes long and OBV above the upper band with the close above it goes short,
reversing an opposite position. A long closes once OBV 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(obv_mean_reversion_strategy, self).__init__()
self._average_period = self.Param("AveragePeriod", 20).SetGreaterThanZero().SetDisplay("Average Period", "Values of OBV 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(obv_mean_reversion_strategy, self).OnReseted()
self._reset_state()
def OnStarted2(self, time):
super(obv_mean_reversion_strategy, self).OnStarted2(time)
self._reset_state()
obv = OnBalanceVolume()
sma = SimpleMovingAverage()
sma.Length = self._average_period.Value
subscription = self.SubscribeCandles(self.candle_type)
subscription.BindEx(obv, 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, obv)
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, obv_value, sma_value):
if candle.State != CandleStates.Finished:
return
if not sma_value.IsFormed:
return
if not obv_value.IsFormed:
return
value = obv_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._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 obv_mean_reversion_strategy()