日本語 JA
GitHub で見る

Trendline Bounce Strategy

Markets often respect trendlines drawn across prior swing highs or lows. This strategy automatically fits regression lines to recent price action and looks for candles that bounce from those lines in the direction of the dominant trend.

Testing indicates an average annual return of about 124%. It performs best in the forex market.

Recent candles are stored to calculate upward or downward sloping support and resistance lines. When price nears a trendline and a candle confirms the bounce while staying on the correct side of a moving average, the system enters a trade. The stop is set using a percentage of price and an exit occurs on a cross of the moving average.

By only trading in the prevailing direction and waiting for a clear reaction at support or resistance, the method attempts to capture continuation moves without chasing breakouts.

Details

  • Entry Criteria: Price touches calculated trendline and candle closes in trend direction above/below MA.
  • Long/Short: Both.
  • Exit Criteria: Price crossing moving average or stop-loss.
  • Stops: Yes, percentage based.
  • Default Values:
    • TrendlinePeriod = 20
    • MAPeriod = 20
    • BounceThresholdPercent = 0.5
    • CandleType = 5 minute
    • StopLossPercent = 2
  • Filters:
    • Category: Trend following
    • Direction: Both
    • Indicators: MA, Trendlines
    • Stops: Yes
    • Complexity: Advanced
    • Timeframe: Intraday
    • Seasonality: No
    • Neural networks: No
    • Divergence: No
    • Risk level: Medium
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>
/// Trendline Bounce strategy.
/// Calculates linear regression of recent lows (support) and highs (resistance).
/// Buys on bounce off support trendline, sells on bounce off resistance.
/// Uses SMA for exit signals.
/// </summary>
public class TrendlineBounceStrategy : Strategy
{
	private readonly StrategyParam<int> _trendlinePeriod;
	private readonly StrategyParam<int> _maPeriod;
	private readonly StrategyParam<DataType> _candleType;
	private readonly StrategyParam<int> _cooldownBars;

	private readonly List<decimal> _highs = new();
	private readonly List<decimal> _lows = new();
	private int _cooldown;

	/// <summary>
	/// Trendline period.
	/// </summary>
	public int TrendlinePeriod
	{
		get => _trendlinePeriod.Value;
		set => _trendlinePeriod.Value = value;
	}

	/// <summary>
	/// MA Period.
	/// </summary>
	public int MAPeriod
	{
		get => _maPeriod.Value;
		set => _maPeriod.Value = value;
	}

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

	/// <summary>
	/// Cooldown bars.
	/// </summary>
	public int CooldownBars
	{
		get => _cooldownBars.Value;
		set => _cooldownBars.Value = value;
	}

	/// <summary>
	/// Constructor.
	/// </summary>
	public TrendlineBounceStrategy()
	{
		_trendlinePeriod = Param(nameof(TrendlinePeriod), 20)
			.SetGreaterThanZero()
			.SetDisplay("Trendline Period", "Lookback for trendline", "Indicators");

		_maPeriod = Param(nameof(MAPeriod), 20)
			.SetGreaterThanZero()
			.SetDisplay("MA Period", "Period for SMA", "Indicators");

		_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(1).TimeFrame())
			.SetDisplay("Candle Type", "Type of candles to use", "General");

		_cooldownBars = Param(nameof(CooldownBars), 500)
			.SetRange(1, 1000)
			.SetDisplay("Cooldown Bars", "Bars to wait between trades", "General");
	}

	/// <inheritdoc />
	public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
	{
		return [(Security, CandleType)];
	}

	/// <inheritdoc />
	protected override void OnReseted()
	{
		base.OnReseted();
		_highs.Clear();
		_lows.Clear();
		_cooldown = default;
	}

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

		_highs.Clear();
		_lows.Clear();
		_cooldown = 0;

		var sma = new SimpleMovingAverage { Length = MAPeriod };

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

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

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

		_highs.Add(candle.HighPrice);
		_lows.Add(candle.LowPrice);

		if (_highs.Count > TrendlinePeriod)
		{
			_highs.RemoveAt(0);
			_lows.RemoveAt(0);
		}

		if (!IsFormedAndOnlineAndAllowTrading())
			return;

		if (_highs.Count < TrendlinePeriod)
			return;

		if (_cooldown > 0)
		{
			_cooldown--;
			return;
		}

		// Calculate linear regression for support (lows) and resistance (highs)
		var supportLevel = GetLinRegValue(_lows);
		var resistanceLevel = GetLinRegValue(_highs);
		var buffer = (resistanceLevel - supportLevel) * 0.05m;

		if (buffer <= 0)
			return;

		var isBullish = candle.ClosePrice > candle.OpenPrice;
		var isBearish = candle.ClosePrice < candle.OpenPrice;

		// Bounce off support (buy)
		if (Position == 0 && candle.LowPrice <= supportLevel + buffer && isBullish)
		{
			BuyMarket();
			_cooldown = CooldownBars;
		}
		// Bounce off resistance (sell)
		else if (Position == 0 && candle.HighPrice >= resistanceLevel - buffer && isBearish)
		{
			SellMarket();
			_cooldown = CooldownBars;
		}
		// Exit using SMA
		else if (Position > 0 && candle.ClosePrice < smaValue)
		{
			SellMarket();
			_cooldown = CooldownBars;
		}
		else if (Position < 0 && candle.ClosePrice > smaValue)
		{
			BuyMarket();
			_cooldown = CooldownBars;
		}
	}

	private static decimal GetLinRegValue(List<decimal> values)
	{
		var n = values.Count;
		if (n == 0) return 0;

		decimal sumX = 0, sumY = 0, sumXY = 0, sumX2 = 0;
		for (int i = 0; i < n; i++)
		{
			sumX += i;
			sumY += values[i];
			sumXY += i * values[i];
			sumX2 += i * i;
		}

		var denom = n * sumX2 - sumX * sumX;
		if (denom == 0) return sumY / n;

		var slope = (n * sumXY - sumX * sumY) / denom;
		var intercept = (sumY - slope * sumX) / n;

		return slope * (n - 1) + intercept;
	}
}