Стратегия Keltner Stochastic
Стратегия сочетает каналы Келтнера и осциллятор Стохастик. Позиции открываются, когда цена достигает границ канала Келтнера и Стохастик подтверждает перепроданность или перекупленность.
Тестирование показывает среднегодичную доходность около 163%. Стратегию лучше запускать на фондовом рынке.
Такой подход позволяет ловить развороты около полос Келтнера, пока осциллятор подтверждает смену импульса. Сигналы могут появляться в обоих направлениях, когда цена касается границы канала.
Для краткосрочных трейдеров, ищущих быстрые развороты, стратегия может быть полезна. Риск ограничивается стопом, основанным на ATR.
Подробности
- Условия входа:
- Лонг:
Close < LowerBand && StochK < StochOversold - Шорт:
Close > UpperBand && StochK > StochOverbought
- Лонг:
- Длинные/короткие: обе стороны
- Условия выхода:
- Лонг:
Close > EMA - Шорт:
Close < EMA
- Лонг:
- Стопы:
StopLossAtrATR от точки входа - Значения по умолчанию:
EmaPeriod= 20AtrPeriod= 14KeltnerMultiplier= 2.0mStochPeriod= 14StochK= 3StochD= 3StochOversold= 20mStochOverbought= 80mStopLossAtr= 2.0mCandleType= TimeSpan.FromMinutes(5).TimeFrame()
- Фильтры:
- Категория: Средняя обратная
- Направление: Оба
- Индикаторы: Канал Келтнера, Стохастик
- Стопы: Да
- Сложность: Средняя
- Таймфрейм: Среднесрочный
- Сезонность: Нет
- Нейросети: Нет
- Дивергенция: Нет
- Уровень риска: Средний
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>
/// Strategy that combines Keltner Channels (EMA + ATR) and manual Stochastic %K.
/// Enters when price reaches Keltner bands and Stochastic confirms oversold/overbought.
/// </summary>
public class KeltnerStochasticStrategy : Strategy
{
private readonly StrategyParam<DataType> _candleType;
private readonly StrategyParam<int> _emaPeriod;
private readonly StrategyParam<decimal> _keltnerMultiplier;
private readonly StrategyParam<decimal> _stochOversold;
private readonly StrategyParam<decimal> _stochOverbought;
private readonly StrategyParam<int> _cooldownBars;
private decimal _atrValue;
private int _cooldown;
private readonly List<decimal> _highs = new();
private readonly List<decimal> _lows = new();
private const int StochPeriod = 14;
/// <summary>
/// Candle type for strategy calculation.
/// </summary>
public DataType CandleType
{
get => _candleType.Value;
set => _candleType.Value = value;
}
/// <summary>
/// EMA period for Keltner Channel.
/// </summary>
public int EmaPeriod
{
get => _emaPeriod.Value;
set => _emaPeriod.Value = value;
}
/// <summary>
/// Keltner Channel multiplier.
/// </summary>
public decimal KeltnerMultiplier
{
get => _keltnerMultiplier.Value;
set => _keltnerMultiplier.Value = value;
}
/// <summary>
/// Stochastic oversold level.
/// </summary>
public decimal StochOversold
{
get => _stochOversold.Value;
set => _stochOversold.Value = value;
}
/// <summary>
/// Stochastic overbought level.
/// </summary>
public decimal StochOverbought
{
get => _stochOverbought.Value;
set => _stochOverbought.Value = value;
}
/// <summary>
/// Cooldown bars between trades.
/// </summary>
public int CooldownBars
{
get => _cooldownBars.Value;
set => _cooldownBars.Value = value;
}
/// <summary>
/// Strategy constructor.
/// </summary>
public KeltnerStochasticStrategy()
{
_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(5).TimeFrame())
.SetDisplay("Candle Type", "Type of candles to use", "General");
_emaPeriod = Param(nameof(EmaPeriod), 20)
.SetRange(10, 30)
.SetDisplay("EMA Period", "Period of the EMA for Keltner Channel", "Indicators");
_keltnerMultiplier = Param(nameof(KeltnerMultiplier), 2.0m)
.SetDisplay("Keltner Multiplier", "Multiplier for ATR in Keltner Channel", "Indicators");
_stochOversold = Param(nameof(StochOversold), 20m)
.SetDisplay("Stochastic Oversold", "Level considered oversold", "Indicators");
_stochOverbought = Param(nameof(StochOverbought), 80m)
.SetDisplay("Stochastic Overbought", "Level considered overbought", "Indicators");
_cooldownBars = Param(nameof(CooldownBars), 100)
.SetDisplay("Cooldown Bars", "Bars between trades", "General")
.SetRange(5, 500);
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_atrValue = 0;
_cooldown = 0;
_highs.Clear();
_lows.Clear();
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
var ema = new ExponentialMovingAverage { Length = EmaPeriod };
var atr = new AverageTrueRange { Length = 14 };
var subscription = SubscribeCandles(CandleType);
// Bind ATR to capture value
subscription.BindEx(atr, OnAtr);
// Bind EMA for main logic
subscription
.Bind(ema, ProcessCandle)
.Start();
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawIndicator(area, ema);
DrawOwnTrades(area);
}
}
private void OnAtr(ICandleMessage candle, IIndicatorValue atrValue)
{
if (atrValue.IsFormed)
_atrValue = atrValue.ToDecimal();
}
private void ProcessCandle(ICandleMessage candle, decimal emaValue)
{
if (candle.State != CandleStates.Finished)
return;
if (!IsFormedAndOnlineAndAllowTrading())
return;
if (_atrValue <= 0)
return;
// Track highs/lows for stochastic
_highs.Add(candle.HighPrice);
_lows.Add(candle.LowPrice);
var maxBuf = StochPeriod * 2;
if (_highs.Count > maxBuf)
{
_highs.RemoveRange(0, _highs.Count - maxBuf);
_lows.RemoveRange(0, _lows.Count - maxBuf);
}
if (_highs.Count < StochPeriod)
return;
// Manual Stochastic %K
var start = _highs.Count - StochPeriod;
var highestHigh = decimal.MinValue;
var lowestLow = decimal.MaxValue;
for (var i = start; i < _highs.Count; i++)
{
if (_highs[i] > highestHigh) highestHigh = _highs[i];
if (_lows[i] < lowestLow) lowestLow = _lows[i];
}
var diff = highestHigh - lowestLow;
if (diff == 0) return;
var stochK = 100m * (candle.ClosePrice - lowestLow) / diff;
// Keltner Channel
var upperBand = emaValue + (KeltnerMultiplier * _atrValue);
var lowerBand = emaValue - (KeltnerMultiplier * _atrValue);
var close = candle.ClosePrice;
if (_cooldown > 0)
{
_cooldown--;
return;
}
// Long: price below lower Keltner + Stochastic oversold
if (close < lowerBand && stochK < StochOversold && Position == 0)
{
BuyMarket();
_cooldown = CooldownBars;
}
// Short: price above upper Keltner + Stochastic overbought
else if (close > upperBand && stochK > StochOverbought && Position == 0)
{
SellMarket();
_cooldown = CooldownBars;
}
// Exit long: price above EMA
if (Position > 0 && close > emaValue)
{
SellMarket();
_cooldown = CooldownBars;
}
// Exit short: price below EMA
else if (Position < 0 && close < emaValue)
{
BuyMarket();
_cooldown = CooldownBars;
}
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")
from System import TimeSpan
from StockSharp.Messages import DataType, CandleStates
from StockSharp.Algo.Indicators import ExponentialMovingAverage, AverageTrueRange
from StockSharp.Algo.Strategies import Strategy
class keltner_stochastic_strategy(Strategy):
"""
Keltner Channel + manual Stochastic %K. Mean reversion at band extremes.
"""
def __init__(self):
super(keltner_stochastic_strategy, self).__init__()
self._ema_period = self.Param("EmaPeriod", 20).SetDisplay("EMA Period", "Keltner EMA period", "Indicators")
self._keltner_mult = self.Param("KeltnerMultiplier", 2.0).SetDisplay("Keltner Mult", "ATR multiplier", "Indicators")
self._stoch_oversold = self.Param("StochOversold", 20.0).SetDisplay("Stoch Oversold", "Oversold level", "Indicators")
self._stoch_overbought = self.Param("StochOverbought", 80.0).SetDisplay("Stoch Overbought", "Overbought level", "Indicators")
self._cooldown_bars = self.Param("CooldownBars", 100).SetDisplay("Cooldown", "Bars between trades", "General")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(5))).SetDisplay("Candle Type", "Timeframe", "General")
self._atr_value = 0.0
self._cooldown = 0
self._highs = []
self._lows = []
self._stoch_period = 14
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(keltner_stochastic_strategy, self).OnReseted()
self._atr_value = 0.0
self._cooldown = 0
self._highs = []
self._lows = []
def OnStarted2(self, time):
super(keltner_stochastic_strategy, self).OnStarted2(time)
ema = ExponentialMovingAverage()
ema.Length = self._ema_period.Value
atr = AverageTrueRange()
atr.Length = 14
subscription = self.SubscribeCandles(self.candle_type)
subscription.BindEx(atr, self._on_atr)
subscription.Bind(ema, self._process_candle).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawIndicator(area, ema)
self.DrawOwnTrades(area)
def _on_atr(self, candle, atr_val):
if atr_val.IsFinal:
self._atr_value = float(atr_val.Value)
def _process_candle(self, candle, ema_val):
if candle.State != CandleStates.Finished:
return
if self._atr_value <= 0:
return
high = float(candle.HighPrice)
low = float(candle.LowPrice)
close = float(candle.ClosePrice)
self._highs.append(high)
self._lows.append(low)
max_buf = self._stoch_period * 2
if len(self._highs) > max_buf:
self._highs = self._highs[-max_buf:]
self._lows = self._lows[-max_buf:]
if len(self._highs) < self._stoch_period:
return
recent_h = self._highs[-self._stoch_period:]
recent_l = self._lows[-self._stoch_period:]
hh = max(recent_h)
ll = min(recent_l)
diff = hh - ll
if diff == 0:
return
stoch_k = 100.0 * (close - ll) / diff
ema = float(ema_val)
upper = ema + self._keltner_mult.Value * self._atr_value
lower = ema - self._keltner_mult.Value * self._atr_value
if self._cooldown > 0:
self._cooldown -= 1
return
if close < lower and stoch_k < self._stoch_oversold.Value and self.Position == 0:
self.BuyMarket()
self._cooldown = self._cooldown_bars.Value
elif close > upper and stoch_k > self._stoch_overbought.Value and self.Position == 0:
self.SellMarket()
self._cooldown = self._cooldown_bars.Value
if self.Position > 0 and close > ema:
self.SellMarket()
self._cooldown = self._cooldown_bars.Value
elif self.Position < 0 and close < ema:
self.BuyMarket()
self._cooldown = self._cooldown_bars.Value
def CreateClone(self):
return keltner_stochastic_strategy()