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COSTAR戦略

COSTAR戦略は終値の線形回帰を構築し、残差の標準偏差を計測します。偏差にファクターを乗じた値を加減することで上限バンドと下限バンドを形成します。取引は極端な偏差に逆張りして行われ、価格が回帰線に戻ったときにイグジットします。

詳細

  • エントリー条件:
    • ロング: 価格が下限バンドを上抜け。
    • ショート: 価格が上限バンドを下抜け。
  • ロング/ショート: 両方。
  • エグジット条件:
    • 価格が回帰線を再度クロス。
  • ストップ: なし。
  • デフォルト値:
    • Length = 100
    • Multiplier = 1
  • フィルター:
    • カテゴリ: 平均回帰
    • 方向: 両方
    • インジケーター: Linear Regression, Standard Deviation
    • ストップ: いいえ
    • 複雑さ: 低
    • 時間軸: 任意
    • 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.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;

namespace StockSharp.Samples.Strategies;

/// <summary>
/// COSTAR strategy.
/// A least-squares line is fitted to the last Length closes and the standard deviation of its residuals, times Multiplier,
/// builds bands around the line's current value. A close crossing back above the lower band buys and a close crossing back
/// below the upper band sells short, reversing an opposite position. A long closes when the close crosses above the
/// regression line and a short when it crosses below it.
/// </summary>
public class CostarStrategy : Strategy
{
	private readonly StrategyParam<int> _length;
	private readonly StrategyParam<decimal> _multiplier;
	private readonly StrategyParam<DataType> _candleType;

	private readonly Queue<decimal> _closes = new();
	private decimal? _prevClose;
	private decimal? _prevLine;
	private decimal? _prevUpper;
	private decimal? _prevLower;

	/// <summary>
	/// Regression length.
	/// </summary>
	public int Length
	{
		get => _length.Value;
		set => _length.Value = value;
	}

	/// <summary>
	/// Residual deviation multiplier for the bands.
	/// </summary>
	public decimal Multiplier
	{
		get => _multiplier.Value;
		set => _multiplier.Value = value;
	}

	/// <summary>
	/// Candle type.
	/// </summary>
	public DataType CandleType
	{
		get => _candleType.Value;
		set => _candleType.Value = value;
	}

	/// <summary>
	/// Constructor.
	/// </summary>
	public CostarStrategy()
	{
		_length = Param(nameof(Length), 100)
			.SetRange(2, 10000)
			.SetDisplay("Length", "Regression length", "Indicators");

		_multiplier = Param(nameof(Multiplier), 1m)
			.SetGreaterThanZero()
			.SetDisplay("Multiplier", "Residual deviation multiplier for the bands", "Indicators");

		_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(1).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();
		ResetState();
	}

	private void ResetState()
	{
		_closes.Clear();
		_prevClose = null;
		_prevLine = null;
		_prevUpper = null;
		_prevLower = null;
	}

	/// <inheritdoc />
	protected override void OnStarted2(DateTime time)
	{
		base.OnStarted2(time);

		ResetState();

		var subscription = SubscribeCandles(CandleType);
		subscription
			.Bind(ProcessCandle)
			.Start();

		var area = CreateChartArea();
		if (area != null)
		{
			DrawCandles(area, subscription);
			DrawOwnTrades(area);
		}
	}

	private void ProcessCandle(ICandleMessage candle)
	{
		if (candle.State != CandleStates.Finished)
			return;

		var close = candle.ClosePrice;

		_closes.Enqueue(close);
		while (_closes.Count > Length)
			_closes.Dequeue();

		if (_closes.Count < Length)
		{
			_prevClose = close;
			return;
		}

		var (line, deviation) = CalculateRegression(_closes.ToArray());
		var upper = line + deviation * Multiplier;
		var lower = line - deviation * Multiplier;

		var prevClose = _prevClose;
		var prevLine = _prevLine;
		var prevUpper = _prevUpper;
		var prevLower = _prevLower;

		_prevClose = close;
		_prevLine = line;
		_prevUpper = upper;
		_prevLower = lower;

		if (prevClose is not decimal pc || prevLine is not decimal pl || prevUpper is not decimal pu || prevLower is not decimal plo)
			return;

		if (!IsFormedAndOnlineAndAllowTrading())
			return;

		var crossAboveLower = pc <= plo && close > lower;
		var crossBelowUpper = pc >= pu && close < upper;

		if (crossAboveLower && Position <= 0)
			BuyMarket(Volume + Math.Abs(Position));
		else if (crossBelowUpper && Position >= 0)
			SellMarket(Volume + Math.Abs(Position));
		else if (Position > 0 && pc <= pl && close > line)
			SellMarket(Position);
		else if (Position < 0 && pc >= pl && close < line)
			BuyMarket(-Position);
	}

	private static (decimal line, decimal deviation) CalculateRegression(decimal[] values)
	{
		var n = values.Length;
		double sumX = 0, sumY = 0, sumXy = 0, sumXx = 0;

		for (var i = 0; i < n; i++)
		{
			var y = (double)values[i];
			sumX += i;
			sumY += y;
			sumXy += i * y;
			sumXx += (double)i * i;
		}

		var denominator = n * sumXx - sumX * sumX;
		var slope = denominator == 0 ? 0 : (n * sumXy - sumX * sumY) / denominator;
		var intercept = (sumY - slope * sumX) / n;

		var sumSquares = 0.0;
		for (var i = 0; i < n; i++)
		{
			var residual = (double)values[i] - (intercept + slope * i);
			sumSquares += residual * residual;
		}

		var line = intercept + slope * (n - 1);
		return ((decimal)line, (decimal)Math.Sqrt(sumSquares / n));
	}
}