モメンタムブレイクアウト戦略
このブレイクアウトシステムは歴史的平均と比較してモメンタムの突然の急増を探します。モメンタムの読み取り値が平均を大きく超えると、価格が速い方向性のある動きを始める可能性があります。
テストでは平均年間リターンが約82%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。
モメンタムが平均値にMultiplier倍の標準偏差を足した値を上回ったときに買いエントリーします。モメンタムが平均値から同じ乗数を引いた値を下回ったときにショートを開始します。モメンタムが平均値に向かって戻ったらポジションを決済します。
速い動きを好むトレーダーは、力強いバーストを捉えるための明確なルールを評価するかもしれません。価格のパーセンテージに基づいたストップロスが失敗したブレイクアウトから保護します。
詳細
- エントリー条件:
- ロング: Momentum > Avg + Multiplier * StdDev
- ショート: Momentum < Avg - Multiplier * StdDev
- ロング/ショート: 両方。
- エグジット条件:
- ロング: Momentum < Avg のときに決済
- ショート: Momentum > 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:
MomentumPeriod= 14AveragePeriod= 20Multiplier= 2StopLossPercent= 2CandleType= TimeSpan.FromMinutes(5) AvgとStdDevは現在値を含む直近AveragePeriod個のモメンタム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: ブレイクアウト
- 方向: 両方
- インジケーター: Momentum
- 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>
/// Momentum Breakout strategy.
/// The bands lie Multiplier standard deviations around the average of the last AveragePeriod momentum values, the current one included.
/// momentum above the upper band goes long and momentum below the lower band goes short,
/// reversing an opposite position. A long closes once momentum is back below its average and a short once it is back above it, and a percent stop limits the loss.
/// </summary>
public class MomentumBreakoutStrategy : Strategy
{
private readonly StrategyParam<int> _momentumPeriod;
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>
/// Period of momentum.
/// </summary>
public int MomentumPeriod
{
get => _momentumPeriod.Value;
set => _momentumPeriod.Value = value;
}
/// <summary>
/// Values of momentum 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 MomentumBreakoutStrategy()
{
_momentumPeriod = Param(nameof(MomentumPeriod), 14)
.SetGreaterThanZero()
.SetDisplay("Momentum Period", "Period of momentum", "Indicators");
_averagePeriod = Param(nameof(AveragePeriod), 20)
.SetGreaterThanZero()
.SetDisplay("Average Period", "Values of momentum 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 momentum = new Momentum { Length = MomentumPeriod };
var subscription = SubscribeCandles(CandleType);
subscription
.BindEx(momentum, 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, momentum);
}
}
}
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 momentumValue)
{
if (candle.State != CandleStates.Finished)
return;
if (!momentumValue.IsFormed)
return;
var value = momentumValue.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;
if (value > upper && Position <= 0)
BuyMarket(Volume + Math.Abs(Position));
else if (value < lower && 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 Momentum
from StockSharp.Algo.Strategies import Strategy
class momentum_breakout_strategy(Strategy):
"""
Momentum Breakout strategy.
The bands lie Multiplier standard deviations around the average of the last AveragePeriod momentum values, the current one included.
momentum above the upper band goes long and momentum below the lower band goes short,
reversing an opposite position. A long closes once momentum is back below its average and a short once it is back above it, and a percent stop limits the loss.
"""
def __init__(self):
super(momentum_breakout_strategy, self).__init__()
self._momentum_period = self.Param("MomentumPeriod", 14).SetGreaterThanZero().SetDisplay("Momentum Period", "Period of momentum", "Indicators")
self._average_period = self.Param("AveragePeriod", 20).SetGreaterThanZero().SetDisplay("Average Period", "Values of momentum 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(momentum_breakout_strategy, self).OnReseted()
self._reset_state()
def OnStarted2(self, time):
super(momentum_breakout_strategy, self).OnStarted2(time)
self._reset_state()
momentum = Momentum()
momentum.Length = self._momentum_period.Value
subscription = self.SubscribeCandles(self.candle_type)
subscription.BindEx(momentum, 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, momentum)
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, momentum_value):
if candle.State != CandleStates.Finished:
return
if not momentum_value.IsFormed:
return
value = momentum_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
if value > upper and self.Position <= 0:
self.BuyMarket(self.Volume + abs(self.Position))
elif value < lower 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 momentum_breakout_strategy()