中文 ZH
在 GitHub 上查看

自适应 Renko 策略

该策略构建一个自适应的 Renko 网格，其砖块大小根据 ATR（平均真实波幅） 指标衡量的市场波动性进行调整。当价格在任意方向移动一个完整砖块时执行交易。

逻辑

  • ATR 根据可配置的 VolatilityPeriod 计算。
  • 砖块大小等于 ATR * Multiplier，但不会小于 MinBrickSize。
  • 当价格向上突破前一个砖块至少一个砖块大小时，策略买入（如有需要，先平空仓）。
  • 当价格向下突破前一个砖块至少一个砖块大小时，策略卖出（如有需要，先平多仓）。

参数

  • Volume – 订单数量。
  • VolatilityPeriod – ATR 的计算周期。
  • Multiplier – ATR 的乘数。
  • MinBrickSize – 砖块的最小尺寸（价格单位）。
  • CandleType – 用于 ATR 计算的时间框架。

时间框架

  • 默认：4 小时。
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;
		}
	}
}