Стратегия Adaptive Renko
Стратегия строит адаптивную Renko сетку, где размер кирпича определяется волатильностью рынка с помощью индикатора ATR (Average True Range). Сделка совершается всякий раз, когда цена проходит полный кирпич вверх или вниз.
Логика
- ATR рассчитывается по настраиваемому параметру
VolatilityPeriod. - Размер кирпича равен
ATR * Multiplier, но не может быть меньшеMinBrickSize. - Если цена поднимается выше предыдущего кирпича минимум на один кирпич, стратегия покупает (при необходимости закрывая короткие позиции).
- Если цена опускается ниже предыдущего кирпича минимум на один кирпич, стратегия продаёт (при необходимости закрывая длинные позиции).
Параметры
Volume– объём заявки.VolatilityPeriod– период расчёта ATR.Multiplier– коэффициент, применяемый к ATR.MinBrickSize– минимальный размер кирпича в ценовых единицах.CandleType– таймфрейм для расчёта ATR.
Таймфрейм
- По умолчанию: 4 часа.
using System;
using System.Linq;
using System.Collections.Generic;
using Ecng.Common;
using Ecng.Collections;
using Ecng.Serialization;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
/// <summary>
/// Strategy that trades on adaptive renko movements based on ATR volatility.
/// </summary>
public class AdaptiveRenkoStrategy : Strategy
{
private readonly StrategyParam<int> _volatilityPeriod;
private readonly StrategyParam<decimal> _multiplier;
private readonly StrategyParam<decimal> _minBrick;
private readonly StrategyParam<DataType> _candleType;
private readonly AverageTrueRange _atr = new();
private decimal _lastBrickPrice;
private bool _hasBrick;
public int VolatilityPeriod
{
get => _volatilityPeriod.Value;
set => _volatilityPeriod.Value = value;
}
public decimal Multiplier
{
get => _multiplier.Value;
set => _multiplier.Value = value;
}
public decimal MinBrickSize
{
get => _minBrick.Value;
set => _minBrick.Value = value;
}
public DataType CandleType
{
get => _candleType.Value;
set => _candleType.Value = value;
}
public AdaptiveRenkoStrategy()
{
_volatilityPeriod = Param(nameof(VolatilityPeriod), 10)
.SetGreaterThanZero()
.SetDisplay("Volatility Period", "ATR calculation period", "Indicator")
.SetOptimize(5, 20, 1);
_multiplier = Param(nameof(Multiplier), 1m)
.SetGreaterThanZero()
.SetDisplay("Multiplier", "ATR multiplier", "Indicator")
.SetOptimize(0.5m, 2m, 0.5m);
_minBrick = Param(nameof(MinBrickSize), 2m)
.SetGreaterThanZero()
.SetDisplay("Min Brick", "Minimum brick size", "Indicator")
.SetOptimize(1m, 5m, 1m);
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(4).TimeFrame())
.SetDisplay("Candle Type", "Time frame for ATR calculation", "General");
}
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_atr.Length = VolatilityPeriod;
_atr.Reset();
_lastBrickPrice = 0m;
_hasBrick = false;
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_atr.Length = VolatilityPeriod;
var subscription = SubscribeCandles(CandleType);
subscription
.Bind(_atr, ProcessCandle)
.Start();
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawOwnTrades(area);
}
StartProtection(null, null);
}
private void ProcessCandle(ICandleMessage candle, decimal atr)
{
if (candle.State != CandleStates.Finished)
return;
var brick = Math.Max(atr * Multiplier, MinBrickSize);
if (!_hasBrick)
{
_lastBrickPrice = candle.ClosePrice;
_hasBrick = true;
return;
}
var diff = candle.ClosePrice - _lastBrickPrice;
if (diff >= brick)
{
if (Position <= 0)
{
if (Position < 0) BuyMarket();
BuyMarket();
}
_lastBrickPrice = candle.ClosePrice;
}
else if (diff <= -brick)
{
if (Position >= 0)
{
if (Position > 0) SellMarket();
SellMarket();
}
_lastBrickPrice = candle.ClosePrice;
}
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")
from System import TimeSpan, Math
from StockSharp.Messages import DataType, CandleStates
from StockSharp.Algo.Indicators import AverageTrueRange
from StockSharp.Algo.Strategies import Strategy
class adaptive_renko_strategy(Strategy):
def __init__(self):
super(adaptive_renko_strategy, self).__init__()
self._volatility_period = self.Param("VolatilityPeriod", 10) \
.SetGreaterThanZero() \
.SetDisplay("Volatility Period", "ATR calculation period", "Indicator") \
.SetOptimize(5, 20, 1)
self._multiplier = self.Param("Multiplier", 1.0) \
.SetGreaterThanZero() \
.SetDisplay("Multiplier", "ATR multiplier", "Indicator") \
.SetOptimize(0.5, 2.0, 0.5)
self._min_brick = self.Param("MinBrickSize", 2.0) \
.SetGreaterThanZero() \
.SetDisplay("Min Brick", "Minimum brick size", "Indicator") \
.SetOptimize(1.0, 5.0, 1.0)
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))) \
.SetDisplay("Candle Type", "Time frame for ATR calculation", "General")
self._last_brick_price = 0.0
self._has_brick = False
@property
def volatility_period(self):
return self._volatility_period.Value
@property
def multiplier(self):
return self._multiplier.Value
@property
def min_brick_size(self):
return self._min_brick.Value
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(adaptive_renko_strategy, self).OnReseted()
self._last_brick_price = 0.0
self._has_brick = False
def OnStarted2(self, time):
super(adaptive_renko_strategy, self).OnStarted2(time)
atr = AverageTrueRange()
atr.Length = self.volatility_period
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(atr, self.process_candle).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawOwnTrades(area)
self.StartProtection(None, None)
def process_candle(self, candle, atr):
if candle.State != CandleStates.Finished:
return
atr_val = float(atr)
brick = max(atr_val * float(self.multiplier), float(self.min_brick_size))
if not self._has_brick:
self._last_brick_price = float(candle.ClosePrice)
self._has_brick = True
return
diff = float(candle.ClosePrice) - self._last_brick_price
if diff >= brick:
if self.Position <= 0:
if self.Position < 0:
self.BuyMarket()
self.BuyMarket()
self._last_brick_price = float(candle.ClosePrice)
elif diff <= -brick:
if self.Position >= 0:
if self.Position > 0:
self.SellMarket()
self.SellMarket()
self._last_brick_price = float(candle.ClosePrice)
def CreateClone(self):
return adaptive_renko_strategy()