Vwap Stochastic 戦略
VWAPとストキャスティクスインジケーターを組み合わせた戦略。価格がVWAPを下回り、Stochasticが売られすぎのときに買い。価格がVWAPを上回り、Stochasticが買われすぎのときに売り。
テストでは年平均リターン約187%を示しています。株式市場で最もパフォーマンスが高いです。
VWAPは平均取引レベルを示し、Stochasticは買われすぎまたは売られすぎの状態を示します。ロングはVWAP下方で上昇するオシレーターとともに発動し、ショートはVWAP上方で下降するオシレーターとともに発動します。
イントラデイの価値水準を観察するデイトレーダーはこのスタイルから恩恵を受けることができます。ストップはエントリー価格から一定割合の位置に設定されます。
詳細
- エントリー条件:
- ロング:
Close < VWAP && StochK < OversoldLevel - ショート:
Close > VWAP && StochK > OverboughtLevel
- ロング:
- ロング/ショート: 両方
- エグジット条件:
- ロング:
Close > VWAP - ショート:
Close < VWAP
- ロング:
- ストップ:
StopLossPercentを使用したパーセントベース - デフォルト値:
StochPeriod= 14StochKPeriod= 3OverboughtLevel= 80mOversoldLevel= 20mStopLossPercent= 2mCandleType= TimeSpan.FromMinutes(5).TimeFrame() 市場は24時間取引のため、セッションVWAPはUTCの毎日リセットされ、各足の典型価格を出来高で加重します。ルール中のStochKは%Kで、StochPeriod本のストキャスティクスをStochKPeriod本で平滑化した値です。%Dはルールに関与しないため設定はありません。 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: VWAP, Stochastic Oscillator
- ストップ: はい
- 複雑さ: 中級
- 時間軸: 中期
- 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 Ecng.Common;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
/// <summary>
/// VWAP Stochastic strategy.
/// The market trades around the clock, so the session VWAP restarts with each UTC day and weighs each candle's typical price by its volume.
/// A close below VWAP with %K below OversoldLevel goes long and a close above VWAP with %K above OverboughtLevel goes short, reversing
/// an opposite position; %K is the stochastic over StochPeriod candles smoothed over StochKPeriod candles. A long closes above VWAP
/// and a short below it, and a percent stop limits the loss.
/// </summary>
public class VwapStochasticStrategy : Strategy
{
private readonly StrategyParam<int> _stochPeriod;
private readonly StrategyParam<int> _stochKPeriod;
private readonly StrategyParam<decimal> _overboughtLevel;
private readonly StrategyParam<decimal> _oversoldLevel;
private readonly StrategyParam<decimal> _stopLossPercent;
private readonly StrategyParam<DataType> _candleType;
private DateTime? _day;
private decimal _cumulativePriceVolume;
private decimal _cumulativeVolume;
/// <summary>
/// Lookback period of the raw stochastic.
/// </summary>
public int StochPeriod
{
get => _stochPeriod.Value;
set => _stochPeriod.Value = value;
}
/// <summary>
/// Smoothing period of %K.
/// </summary>
public int StochKPeriod
{
get => _stochKPeriod.Value;
set => _stochKPeriod.Value = value;
}
/// <summary>
/// %K level for shorts.
/// </summary>
public decimal OverboughtLevel
{
get => _overboughtLevel.Value;
set => _overboughtLevel.Value = value;
}
/// <summary>
/// %K level for longs.
/// </summary>
public decimal OversoldLevel
{
get => _oversoldLevel.Value;
set => _oversoldLevel.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 VwapStochasticStrategy()
{
_stochPeriod = Param(nameof(StochPeriod), 14)
.SetGreaterThanZero()
.SetDisplay("Stochastic Period", "Lookback period of the raw stochastic", "Stochastic");
_stochKPeriod = Param(nameof(StochKPeriod), 3)
.SetGreaterThanZero()
.SetDisplay("Stochastic %K", "Smoothing period of %K", "Stochastic");
_overboughtLevel = Param(nameof(OverboughtLevel), 80m)
.SetDisplay("Overbought Level", "%K level for shorts", "Stochastic");
_oversoldLevel = Param(nameof(OversoldLevel), 20m)
.SetDisplay("Oversold Level", "%K level for longs", "Stochastic");
_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();
_day = null;
_cumulativePriceVolume = 0;
_cumulativeVolume = 0;
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_day = null;
_cumulativePriceVolume = 0;
_cumulativeVolume = 0;
// The D line of the core oscillator is the smoothed %K.
var stochastic = new StochasticOscillator
{
K = { Length = StochPeriod },
D = { Length = StochKPeriod },
};
var subscription = SubscribeCandles(CandleType);
subscription
.BindEx(stochastic, 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, stochastic);
}
}
}
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 stochasticValue)
{
if (candle.State != CandleStates.Finished)
return;
var day = candle.OpenTime.Date;
if (_day != day)
{
_day = day;
_cumulativePriceVolume = 0;
_cumulativeVolume = 0;
}
var typicalPrice = (candle.HighPrice + candle.LowPrice + candle.ClosePrice) / 3;
_cumulativePriceVolume += typicalPrice * candle.TotalVolume;
_cumulativeVolume += candle.TotalVolume;
if (!stochasticValue.IsFormed || _cumulativeVolume <= 0)
return;
if (stochasticValue is not IStochasticOscillatorValue { D: decimal k })
return;
if (!IsFormedAndOnlineAndAllowTrading())
return;
var vwap = _cumulativePriceVolume / _cumulativeVolume;
var close = candle.ClosePrice;
if (close < vwap && k < OversoldLevel && Position <= 0)
BuyMarket(Volume + Math.Abs(Position));
else if (close > vwap && k > OverboughtLevel && Position >= 0)
SellMarket(Volume + Math.Abs(Position));
else if (Position > 0 && close > vwap)
SellMarket(Position);
else if (Position < 0 && close < vwap)
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
from StockSharp.Messages import DataType, CandleStates, Unit, UnitTypes, Level1Fields
from StockSharp.BusinessEntities import Subscription
from StockSharp.Algo.Indicators import StochasticOscillator
from StockSharp.Algo.Strategies import Strategy
class vwap_stochastic_strategy(Strategy):
"""
VWAP Stochastic strategy.
The market trades around the clock, so the session VWAP restarts with each UTC day and weighs each candle's typical price by its volume.
A close below VWAP with %K below OversoldLevel goes long and a close above VWAP with %K above OverboughtLevel goes short, reversing
an opposite position; %K is the stochastic over StochPeriod candles smoothed over StochKPeriod candles. A long closes above VWAP
and a short below it, and a percent stop limits the loss.
"""
def __init__(self):
super(vwap_stochastic_strategy, self).__init__()
self._stoch_period = self.Param("StochPeriod", 14).SetGreaterThanZero().SetDisplay("Stochastic Period", "Lookback period of the raw stochastic", "Stochastic")
self._stoch_k_period = self.Param("StochKPeriod", 3).SetGreaterThanZero().SetDisplay("Stochastic %K", "Smoothing period of %K", "Stochastic")
self._overbought_level = self.Param("OverboughtLevel", 80.0).SetDisplay("Overbought Level", "%K level for shorts", "Stochastic")
self._oversold_level = self.Param("OversoldLevel", 20.0).SetDisplay("Oversold Level", "%K level for longs", "Stochastic")
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._day = None
self._cumulative_price_volume = Decimal(0)
self._cumulative_volume = Decimal(0)
def OnReseted(self):
super(vwap_stochastic_strategy, self).OnReseted()
self._reset_state()
def OnStarted2(self, time):
super(vwap_stochastic_strategy, self).OnStarted2(time)
self._reset_state()
# The D line of the core oscillator is the smoothed %K.
stochastic = StochasticOscillator()
stochastic.K.Length = self._stoch_period.Value
stochastic.D.Length = self._stoch_k_period.Value
subscription = self.SubscribeCandles(self.candle_type)
subscription.BindEx(stochastic, 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, stochastic)
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, stochastic_value):
if candle.State != CandleStates.Finished:
return
day = candle.OpenTime.Date
if self._day is None or self._day != day:
self._day = day
self._cumulative_price_volume = Decimal(0)
self._cumulative_volume = Decimal(0)
typical_price = (candle.HighPrice + candle.LowPrice + candle.ClosePrice) / Decimal(3)
self._cumulative_price_volume += typical_price * candle.TotalVolume
self._cumulative_volume += candle.TotalVolume
if not stochastic_value.IsFormed or self._cumulative_volume <= 0 or stochastic_value.D is None:
return
if not self.IsFormedAndOnlineAndAllowTrading():
return
vwap = self._cumulative_price_volume / self._cumulative_volume
k = stochastic_value.D
close = candle.ClosePrice
if close < vwap and k < Decimal(self._oversold_level.Value) and self.Position <= 0:
self.BuyMarket(self.Volume + abs(self.Position))
elif close > vwap and k > Decimal(self._overbought_level.Value) and self.Position >= 0:
self.SellMarket(self.Volume + abs(self.Position))
elif self.Position > 0 and close > vwap:
self.SellMarket(self.Position)
elif self.Position < 0 and close < vwap:
self.BuyMarket(-self.Position)
def CreateClone(self):
return vwap_stochastic_strategy()