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Burg Extrapolator Forecast Strategy

Overview

The Burg Extrapolator Strategy is a StockSharp port of the MetaTrader 4 expert advisor "Burg Extrapolator". The original system fits a Burg autoregressive (AR) model to a sliding window of open prices (or their momentum/ROC transforms) and projects a path of future prices. Trading decisions are derived from the most extreme forecast values: if the predicted excursion in one direction is large enough the strategy either stacks new positions or liquidates exposure in the opposite direction. The conversion keeps the same modelling blocks while mapping position management and money management to StockSharp primitives.

Trading Logic

  1. Data preparation
    • Build a rolling history of PastBars + 1 open prices for the selected CandleType.
    • Optionally transform the data into logarithmic momentum (default) or percentage rate of change before feeding it to the AR model. Raw prices are centered by their moving average to mirror the MT4 code.
  2. Burg linear prediction
    • Estimate reflection coefficients up to the order PastBars * ModelOrder using the Burg algorithm.
    • Generate a sequence of future values (PastBars steps ahead in practice) by recursively expanding the AR model. Transforms are inverted back to price space so that all forecasts operate in absolute price units.
  3. Signal detection
    • Walk through the forecast path and record the highest and lowest predicted price before another extreme appears. The distance between the first extreme and the other side of the forecast range is compared with MaxLoss and MinProfit thresholds (converted to absolute price by multiplying with the instrument PriceStep).
    • A sufficiently large upswing triggers OpenSignal = 1 while a large downswing yields OpenSignal = -1. If the opposing extreme appears first the logic sets CloseSignal to exit current exposure even if no fresh entry is planned.
  4. Order management
    • Protective exits (stop-loss, take-profit, and optional trailing-stop) run before any new signal is executed. The trailing-stop reuses the best price since the last entry and closes the position when the price retraces by TrailingStop points, matching the MT4 behaviour of moving the protective order.
    • If a signal asks to close exposure in the opposite direction the strategy sends a market order sized to flatten the current net position.
    • Entry signals stack additional market orders in the indicated direction until MaxTrades is reached. Order volume scales linearly with the number of active trades using the factor 1 + existingTrades * MaxRisk, a StockSharp-friendly replacement for the original margin-based sizing routine.

Indicators and Data

  • Candle subscription defined by CandleType (default 30-minute time frame).
  • Internal Burg autoregressive model (implemented without external indicators).
  • Optional logarithmic momentum and percentage rate of change transforms.

Parameters

Name Default Description
CandleType 30-minute candles Primary timeframe processed by the strategy.
MaxRisk 0.5 Risk multiplier used when stacking multiple trades.
MaxTrades 5 Maximum number of simultaneous trades per direction.
MinProfit 160 Minimum predicted profit (in points) required to open new trades.
MaxLoss 130 Maximum tolerated forecasted loss (in points) before closing trades.
TakeProfit 0 Optional fixed take-profit distance in points (0 disables it).
StopLoss 180 Optional fixed stop-loss distance in points (0 disables it).
TrailingStop 10 Trailing stop distance in points, active only when StopLoss > 0.
PastBars 200 Number of historical candles used by the Burg model.
ModelOrder 0.37 Fraction of PastBars converted into the Burg order.
UseMomentum true Apply logarithmic momentum transform to input data.
UseRateOfChange false Apply percentage rate of change (ignored when momentum is enabled).

All parameters are StrategyParam<T> instances and can be optimised or adjusted in the StockSharp Designer.

Implementation Notes

  • The Burg algorithm is implemented directly in C# and keeps the same recursion as the MT4 version. All computations are executed in double precision while the final forecasts are converted back to decimal before signal checks.
  • The original EA could rely on MetaTrader account information to size positions. In StockSharp the money management block is replaced with a deterministic scaling rule based on Volume and MaxRisk. Set Volume to the desired base lot and the strategy will scale subsequent entries proportionally.
  • Protective logic closes positions with explicit market orders instead of modifying broker-side stops; this matches StockSharp's high-level API design and prevents stale state when running in simulation.
  • The forecast arrays are re-created whenever PastBars or ModelOrder change so on-the-fly parameter edits immediately affect the AR model without restarting the strategy.
  • To visualise the behaviour you can attach a chart in Designer: the strategy already draws candles and executed trades on the default area. Extending the sample with custom series (e.g., forecast path) is straightforward if desired.
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>
/// Burg extrapolator strategy converted from MetaTrader 4 implementation.
/// Predicts the future price path with Burg linear prediction coefficients and trades on forecasted extremes.
/// </summary>
public class BurgExtrapolatorForecastStrategy : Strategy
{
	private readonly StrategyParam<DataType> _candleType;
	private readonly StrategyParam<decimal> _maxRisk;
	private readonly StrategyParam<int> _maxTrades;
	private readonly StrategyParam<int> _minProfit;
	private readonly StrategyParam<int> _maxLoss;
	private readonly StrategyParam<int> _takeProfit;
	private readonly StrategyParam<int> _stopLoss;
	private readonly StrategyParam<int> _trailingStop;
	private readonly StrategyParam<int> _pastBars;
	private readonly StrategyParam<decimal> _modelOrder;
	private readonly StrategyParam<bool> _useMomentum;
	private readonly StrategyParam<bool> _useRateOfChange;

	private readonly List<decimal> _openHistory = new();

	private double[] _samples = Array.Empty<double>();
	private double[] _coefficients = Array.Empty<double>();
	private double[] _predictions = Array.Empty<double>();

	private int _np;
	private int _no;
	private int _nf;

	private double _averagePrice;
	private bool _isFirstRun = true;

	private decimal? _longEntryPrice;
	private decimal? _shortEntryPrice;
	private decimal? _longHigh;
	private decimal? _shortLow;

	/// <summary>
/// Initializes a new instance of the <see cref="BurgExtrapolatorForecastStrategy"/> class.
/// </summary>
public BurgExtrapolatorForecastStrategy()
	{
		_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(5).TimeFrame())
			.SetDisplay("Candle Type", "Primary timeframe used for forecasting", "General");

		_maxRisk = Param(nameof(MaxRisk), 0.5m)
			.SetGreaterThanZero()
			.SetDisplay("Max Risk", "Risk factor controlling position scaling", "Money Management");

		_maxTrades = Param(nameof(MaxTrades), 5)
			.SetGreaterThanZero()
			.SetDisplay("Max Trades", "Maximum stacked trades per direction", "Money Management");

		_minProfit = Param(nameof(MinProfit), 160)
			.SetGreaterThanZero()
			.SetDisplay("Min Profit", "Forecasted profit in points required to open trades", "Signals");

		_maxLoss = Param(nameof(MaxLoss), 130)
			.SetGreaterThanZero()
			.SetDisplay("Max Loss", "Forecasted adverse excursion closing existing trades", "Signals");

		_takeProfit = Param(nameof(TakeProfit), 0)
			.SetNotNegative()
			.SetDisplay("Take Profit", "Optional fixed take profit in points", "Protection")
			;

		_stopLoss = Param(nameof(StopLoss), 180)
			.SetNotNegative()
			.SetDisplay("Stop Loss", "Optional fixed stop loss in points", "Protection")
			;

		_trailingStop = Param(nameof(TrailingStop), 10)
			.SetNotNegative()
			.SetDisplay("Trailing Stop", "Trailing distance in points (requires stop loss)", "Protection")
			;

		_pastBars = Param(nameof(PastBars), 200)
			.SetGreaterThanZero()
			.SetDisplay("Past Bars", "History length used for Burg model", "Forecast");

		_modelOrder = Param(nameof(ModelOrder), 0.37m)
			.SetGreaterThanZero()
			.SetDisplay("Model Order", "Fraction of past bars used as Burg order", "Forecast");

		_useMomentum = Param(nameof(UseMomentum), true)
			.SetDisplay("Use Momentum", "Use logarithmic momentum instead of raw prices", "Forecast");

		_useRateOfChange = Param(nameof(UseRateOfChange), false)
			.SetDisplay("Use ROC", "Use percentage rate of change instead of raw prices", "Forecast");
	}

	/// <summary>
	/// Type of candles processed by the strategy.
	/// </summary>
	public DataType CandleType
	{
		get => _candleType.Value;
		set => _candleType.Value = value;
	}

	/// <summary>
	/// Risk factor used when stacking positions.
	/// </summary>
	public decimal MaxRisk
	{
		get => _maxRisk.Value;
		set => _maxRisk.Value = value;
	}

	/// <summary>
	/// Maximum number of trades allowed in one direction.
	/// </summary>
	public int MaxTrades
	{
		get => _maxTrades.Value;
		set => _maxTrades.Value = value;
	}

	/// <summary>
	/// Minimum profit in points predicted by the Burg model to initiate new trades.
	/// </summary>
	public int MinProfit
	{
		get => _minProfit.Value;
		set => _minProfit.Value = value;
	}

	/// <summary>
	/// Maximum loss in points predicted by the Burg model before closing positions.
	/// </summary>
	public int MaxLoss
	{
		get => _maxLoss.Value;
		set => _maxLoss.Value = value;
	}

	/// <summary>
	/// Optional take profit expressed in points.
	/// </summary>
	public int TakeProfit
	{
		get => _takeProfit.Value;
		set => _takeProfit.Value = value;
	}

	/// <summary>
	/// Optional stop loss expressed in points.
	/// </summary>
	public int StopLoss
	{
		get => _stopLoss.Value;
		set => _stopLoss.Value = value;
	}

	/// <summary>
	/// Trailing stop distance in points.
	/// </summary>
	public int TrailingStop
	{
		get => _trailingStop.Value;
		set => _trailingStop.Value = value;
	}

	/// <summary>
	/// Number of historical candles used by the Burg predictor.
	/// </summary>
	public int PastBars
	{
		get => _pastBars.Value;
		set => _pastBars.Value = value;
	}

	/// <summary>
	/// Fraction of <see cref="PastBars"/> used as Burg model order.
	/// </summary>
	public decimal ModelOrder
	{
		get => _modelOrder.Value;
		set => _modelOrder.Value = value;
	}

	/// <summary>
	/// Use logarithmic momentum transformation instead of raw prices.
	/// </summary>
	public bool UseMomentum
	{
		get => _useMomentum.Value;
		set => _useMomentum.Value = value;
	}

	/// <summary>
	/// Use percentage rate of change transformation instead of raw prices.
	/// </summary>
	public bool UseRateOfChange
	{
		get => _useRateOfChange.Value;
		set => _useRateOfChange.Value = value;
	}

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

	/// <inheritdoc />
	protected override void OnReseted()
	{
		base.OnReseted();

		_openHistory.Clear();
		_samples = Array.Empty<double>();
		_coefficients = Array.Empty<double>();
		_predictions = Array.Empty<double>();
		_np = 0;
		_no = 0;
		_nf = 0;
		_averagePrice = 0.0;
		_isFirstRun = true;
		ResetLongState();
		ResetShortState();
	}

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

		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;

		AddOpenPrice(candle.OpenPrice);

		if (!EnsureModel())
			return;

		TrimHistory();

		if (_openHistory.Count < _np + 1)
			return;

		if (!UpdateSamples())
			return;

		var predictionCount = ComputePredictions();
		if (predictionCount <= 0)
			return;

		var (openSignal, closeSignal) = EvaluateSignals(predictionCount);

		if (ManageProtection(candle))
		{
			// Position has been closed by protective logic, wait for the next candle to re-evaluate.
			return;
		}

		HandleSignalClosures(openSignal, closeSignal);

		if (openSignal == 1)
		{
			TryOpenLong(candle);
		}
		else if (openSignal == -1)
		{
			TryOpenShort(candle);
		}
	}

	private void AddOpenPrice(decimal openPrice)
	{
		_openHistory.Add(openPrice);
	}

	private bool EnsureModel()
	{
		var np = PastBars;
		if (np < 3)
			return false;

		var modelOrder = ModelOrder;
		var no = (int)(modelOrder * np);
		if (no < 1)
			no = 1;
		if (no >= np - 1)
			no = np - 2;

		var nf = np - no - 1;
		if (nf < 1)
			nf = 1;

		var predictionLength = nf + 1;

		if (_np != np || _no != no || _nf != nf || _predictions.Length != predictionLength)
		{
			_np = np;
			_no = no;
			_nf = nf;
			_samples = new double[np];
			_coefficients = new double[no + 1];
			_predictions = new double[predictionLength];
			_averagePrice = 0.0;
			_isFirstRun = true;
		}

		return true;
	}

	private void TrimHistory()
	{
		var maxHistory = _np + 1;
		while (_openHistory.Count > maxHistory)
		{
			_openHistory.RemoveAt(0);
		}
	}

	private bool UpdateSamples()
	{
		if (_np <= 0)
			return false;

		var useMomentum = UseMomentum;
		var useRoc = !useMomentum && UseRateOfChange;

		if (useMomentum || useRoc)
		{
			if (!_isFirstRun)
			{
				for (var i = 0; i < _np - 1; i++)
					_samples[i] = _samples[i + 1];

				var current = GetOpen(0);
				var previous = GetOpen(1);
				if (previous == 0m)
					return false;

				var ratio = (double)(current / previous);
				_samples[_np - 1] = useMomentum ? Math.Log(ratio) : ratio - 1.0;
			}
			else
			{
				for (var i = 0; i < _np; i++)
				{
					var current = GetOpen(i);
					var previous = GetOpen(i + 1);
					if (previous == 0m)
						return false;

					var ratio = (double)(current / previous);
					_samples[_np - 1 - i] = useMomentum ? Math.Log(ratio) : ratio - 1.0;
				}

				_averagePrice = 0.0;
				_isFirstRun = false;
			}
		}
		else
		{
			if (_isFirstRun)
			{
				double sum = 0.0;
				for (var i = 0; i < _np; i++)
					sum += (double)GetOpen(i);

				_averagePrice = sum / _np;

				for (var i = 0; i < _np; i++)
				{
					var open = (double)GetOpen(i);
					_samples[_np - 1 - i] = open - _averagePrice;
				}

				_isFirstRun = false;
			}
			else
			{
				var newest = (double)GetOpen(0);
				var leaving = (double)GetOpen(_np);
				_averagePrice += (newest - leaving) / _np;

				for (var i = 0; i < _np; i++)
				{
					var open = (double)GetOpen(i);
					_samples[_np - 1 - i] = open - _averagePrice;
				}
			}
		}

		return true;
	}

	private int ComputePredictions()
	{
		Array.Clear(_coefficients, 0, _coefficients.Length);
		Array.Clear(_predictions, 0, _predictions.Length);

		double den = 0.0;
		for (var i = 0; i < _np; i++)
		{
			var value = _samples[i];
			den += value * value;
		}

		den *= 2.0;

		var df = new double[_np];
		var db = new double[_np];

		for (var i = 0; i < _np; i++)
		{
			var value = _samples[i];
			df[i] = value;
			db[i] = value;
		}

		double r = 0.0;

		for (var k = 1; k <= _no; k++)
		{
			double num = 0.0;
			for (var i = k; i < _np; i++)
				num += df[i] * db[i - 1];

			var denominator = (1.0 - r * r) * den - df[k - 1] * df[k - 1] - db[_np - 1] * db[_np - 1];
			if (Math.Abs(denominator) < 1e-12)
				return 0;

			r = -2.0 * num / denominator;
			_coefficients[k] = r;

			var half = k / 2;
			for (var i = 1; i <= half; i++)
			{
				var ki = k - i;
				var tmp = _coefficients[i];
				_coefficients[i] += r * _coefficients[ki];
				if (i != ki)
					_coefficients[ki] += r * tmp;
			}

			if (k < _no)
			{
				for (var i = _np - 1; i >= k; i--)
				{
					var tmp = df[i];
					df[i] += r * db[i - 1];
					db[i] = db[i - 1] + r * tmp;
				}
			}

			den = denominator;
		}

		for (var n = _np - 1; n < _np + _nf; n++)
		{
			double sum = 0.0;
			for (var i = 1; i <= _no; i++)
			{
				if (n - i < _np)
					sum -= _coefficients[i] * _samples[n - i];
				else
					sum -= _coefficients[i] * _predictions[n - i - _np + 1];
			}

			var index = n - _np + 1;
			if (index < _predictions.Length)
				_predictions[index] = sum;
		}

		var useMomentum = UseMomentum;
		var useRoc = !useMomentum && UseRateOfChange;

		if (useMomentum || useRoc)
		{
			var startPrice = (double)GetOpen(0);
			_predictions[0] = startPrice;

			for (var i = 1; i < _predictions.Length; i++)
			{
				_predictions[i] = useMomentum
					? _predictions[i - 1] * Math.Exp(_predictions[i])
					: _predictions[i - 1] * (1.0 + _predictions[i]);
			}
		}
		else
		{
			for (var i = 0; i < _predictions.Length; i++)
				_predictions[i] += _averagePrice;
		}

		return _predictions.Length;
	}

	private (int openSignal, int closeSignal) EvaluateSignals(int predictionCount)
	{
		if (predictionCount == 0)
			return (0, 0);

		var step = Security?.PriceStep ?? 1m;
		var maxLossDelta = MaxLoss * step;
		var minProfitDelta = MinProfit * step;

		var ymax = (decimal)_predictions[0];
		var ymin = ymax;
		var imax = 0;
		var imin = 0;
		var openSignal = 0;
		var closeSignal = 0;

		var limit = Math.Min(_np, predictionCount);

		for (var i = 1; i < limit; i++)
		{
			var value = (decimal)_predictions[i];

			if (value > ymax && openSignal == 0)
			{
				ymax = value;
				imax = i;

				if (imin == 0 && ymax - ymin >= maxLossDelta)
					closeSignal = 1;

				if (imin == 0 && ymax - ymin >= minProfitDelta)
					openSignal = 1;
			}

			if (value < ymin && openSignal == 0)
			{
				ymin = value;
				imin = i;

				if (imax == 0 && ymax - ymin >= maxLossDelta)
					closeSignal = -1;

				if (imax == 0 && ymax - ymin >= minProfitDelta)
					openSignal = -1;
			}
		}

		return (openSignal, closeSignal);
	}

	private bool ManageProtection(ICandleMessage candle)
	{
		var step = Security?.PriceStep ?? 1m;
		var stopDistance = StopLoss * step;
		var takeDistance = TakeProfit * step;
		var trailingDistance = TrailingStop * step;

		if (Position > 0)
		{
			_longEntryPrice ??= candle.ClosePrice;
			_longHigh = _longHigh.HasValue ? Math.Max(_longHigh.Value, candle.HighPrice) : candle.HighPrice;

			if (StopLoss > 0 && _longEntryPrice.HasValue && candle.LowPrice <= _longEntryPrice.Value - stopDistance)
			{
				SellMarket(Position);
				ResetLongState();
				return true;
			}

			if (TakeProfit > 0 && _longEntryPrice.HasValue && candle.HighPrice >= _longEntryPrice.Value + takeDistance)
			{
				SellMarket(Position);
				ResetLongState();
				return true;
			}

			if (TrailingStop > 0 && StopLoss > 0 && _longHigh.HasValue && candle.LowPrice <= _longHigh.Value - trailingDistance)
			{
				SellMarket(Position);
				ResetLongState();
				return true;
			}
		}
		else
		{
			ResetLongState();
		}

		if (Position < 0)
		{
			_shortEntryPrice ??= candle.ClosePrice;
			_shortLow = _shortLow.HasValue ? Math.Min(_shortLow.Value, candle.LowPrice) : candle.LowPrice;

			if (StopLoss > 0 && _shortEntryPrice.HasValue && candle.HighPrice >= _shortEntryPrice.Value + stopDistance)
			{
				BuyMarket(-Position);
				ResetShortState();
				return true;
			}

			if (TakeProfit > 0 && _shortEntryPrice.HasValue && candle.LowPrice <= _shortEntryPrice.Value - takeDistance)
			{
				BuyMarket(-Position);
				ResetShortState();
				return true;
			}

			if (TrailingStop > 0 && StopLoss > 0 && _shortLow.HasValue && candle.HighPrice >= _shortLow.Value + trailingDistance)
			{
				BuyMarket(-Position);
				ResetShortState();
				return true;
			}
		}
		else
		{
			ResetShortState();
		}

		return false;
	}

	private void HandleSignalClosures(int openSignal, int closeSignal)
	{
		if (Position > 0 && (closeSignal == -1 || openSignal == -1))
		{
			SellMarket(Position);
			ResetLongState();
		}
		else if (Position < 0 && (closeSignal == 1 || openSignal == 1))
		{
			BuyMarket(-Position);
			ResetShortState();
		}
	}

	private void TryOpenLong(ICandleMessage candle)
	{
		var baseVolume = Volume;
		if (baseVolume <= 0m)
			return;

		var tradeCount = GetTradeCount(baseVolume);
		if (tradeCount >= MaxTrades)
			return;

		var orderVolume = CalculateOrderVolume(baseVolume, tradeCount);
		if (orderVolume <= 0m)
			return;

		BuyMarket(orderVolume);
		_longEntryPrice = candle.ClosePrice;
		_longHigh = candle.ClosePrice;
		ResetShortState();
	}

	private void TryOpenShort(ICandleMessage candle)
	{
		var baseVolume = Volume;
		if (baseVolume <= 0m)
			return;

		var tradeCount = GetTradeCount(baseVolume);
		if (tradeCount >= MaxTrades)
			return;

		var orderVolume = CalculateOrderVolume(baseVolume, tradeCount);
		if (orderVolume <= 0m)
			return;

		SellMarket(orderVolume);
		_shortEntryPrice = candle.ClosePrice;
		_shortLow = candle.ClosePrice;
		ResetLongState();
	}

	private int GetTradeCount(decimal baseVolume)
	{
		if (baseVolume <= 0m)
			return 0;

		var trades = Math.Abs(Position) / baseVolume;
		return (int)Math.Ceiling((double)(trades - 1e-8m));
	}

	private decimal CalculateOrderVolume(decimal baseVolume, int existingTrades)
	{
		var multiplier = 1m + existingTrades * MaxRisk;
		if (multiplier <= 0m)
			return 0m;

		return baseVolume * multiplier;
	}

	private decimal GetOpen(int shift)
	{
		var index = _openHistory.Count - 1 - shift;
		return index >= 0 && index < _openHistory.Count ? _openHistory[index] : 0m;
	}

	private void ResetLongState()
	{
		_longEntryPrice = null;
		_longHigh = null;
	}

	private void ResetShortState()
	{
		_shortEntryPrice = null;
		_shortLow = null;
	}
}