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Fuzzy Logic Strategy

Overview

The Fuzzy Logic strategy replicates the MT5 expert advisor Fuzzy logic (barabashkakvn's edition) using the high-level StockSharp API. The system measures trend strength and momentum exhaustion with Bill Williams oscillators and momentum indicators, converts those readings into fuzzy membership grades, and aggregates them into a single decision score between 0 and 1.

Trading actions are triggered when the fuzzy score crosses calibrated thresholds:

  • Decision > 0.75 – open a short position (strong exhaustion / overbought conditions).
  • Decision < 0.25 – open a long position (strong bullish reversal setup).

Positions are managed with fixed take-profit and stop-loss distances expressed in price steps. When a trailing stop distance is supplied, the protective stop is converted into a trailing one.

Indicator Stack

Component Purpose
Gator oscillator (built from Alligator lines) Measures the sum of jaw–teeth and teeth–lips spreads to gauge trend expansion or contraction.
Williams %R (14) Detects overbought / oversold levels.
Acceleration/Deceleration Oscillator (AC) Counts consecutive momentum shifts to estimate trend acceleration.
DeMarker (14) Confirms exhaustion through high/low comparisons. Implemented directly inside the strategy.
RSI (14) Tracks classic momentum swings.

Alligator lines are calculated with smoothed moving averages and shifted forward exactly as in the original expert advisor to reproduce the Gator oscillator. AC values are derived from the Awesome Oscillator (5/34 SMA difference) minus its 5-period moving average, providing identical readings to MT5's iAC indicator.

Trading Logic

  1. Each indicator value is mapped to five fuzzy membership sets (very bearish → very bullish). Piecewise-linear functions replicate the original MT5 arrays.
  2. The five membership groups are weighted (0.133, 0.133, 0.133, 0.268, 0.333) and aggregated into four summary bins.
  3. The fuzzy decision score is computed as Σ summary[x] * (0.2 * (x + 1) - 0.1), producing values in the [0, 1] range.
  4. Signals are evaluated once per finished candle. The strategy stays flat unless the decision breaches the entry thresholds.
  5. Order size relies on the Volume property (default 1). Protective stops are registered through StartProtection.

Risk Management

  • StopLossPoints – absolute distance (in price steps) for the protective stop. Used when TrailingStopPoints is zero.
  • TrailingStopPoints – if > 0, the stop-loss distance switches to this value and trailing mode is enabled.
  • TakeProfitPoints – absolute distance for the profit target.

Parameters

Parameter Description
CandleType Time frame / candle type used for calculations.
BuyThreshold Fuzzy score below which a long entry is opened. Default 0.25.
SellThreshold Fuzzy score above which a short entry is opened. Default 0.75.
StopLossPoints Stop-loss distance in instrument price steps. Default 60.
TakeProfitPoints Take-profit distance in price steps. Default 20.
TrailingStopPoints Trailing stop distance in price steps. Default 0 (disabled).
WilliamsPeriod Lookback for Williams %R. Default 14.
RsiPeriod Lookback for RSI. Default 14.
DeMarkerPeriod Lookback for the embedded DeMarker calculation. Default 14.

Implementation Notes

  • The DeMarker oscillator is implemented manually because StockSharp does not expose a built-in version. High and low deltas are queued to reproduce MT5 sums.
  • AC history stores the five most recent completed values so the fuzzy logic can check consecutive acceleration streaks just like iAC(..., shift) in MT5.
  • Alligator jaw/teeth/lips buffers introduce the same forward shift (8/5/3 bars) before deriving the Gator histogram values.
  • The strategy only opens a new position when Position == 0, respecting the single-position behavior of the original expert advisor.

Usage Steps

  1. Attach the strategy to a portfolio and security in Designer/Backtester.
  2. Configure the desired candle series via CandleType.
  3. Adjust thresholds or stop distances if needed.
  4. Start the strategy; it will trade automatically when the fuzzy score crosses the configured levels.
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>
/// Fuzzy logic strategy combining Bill Williams oscillators, RSI and DeMarker.
/// Opens short positions when the fuzzy score indicates exhaustion and
/// opens long positions during oversold momentum reversals.
/// </summary>
public class FuzzyLogicStrategy : Strategy
{
	private readonly StrategyParam<DataType> _candleType;
	private readonly StrategyParam<decimal> _buyThreshold;
	private readonly StrategyParam<decimal> _sellThreshold;
	private readonly StrategyParam<decimal> _stopLossPoints;
	private readonly StrategyParam<decimal> _takeProfitPoints;
	private readonly StrategyParam<decimal> _trailingStopPoints;
	private readonly StrategyParam<int> _williamsPeriod;
	private readonly StrategyParam<int> _rsiPeriod;
	private readonly StrategyParam<int> _deMarkerPeriod;

	private WilliamsR _williamsIndicator = null!;
	private RelativeStrengthIndex _rsiIndicator = null!;
	private readonly SmoothedMovingAverage _jaw = new() { Length = 13 };
	private readonly SmoothedMovingAverage _teeth = new() { Length = 8 };
	private readonly SmoothedMovingAverage _lips = new() { Length = 5 };
	private readonly SimpleMovingAverage _aoFast = new() { Length = 5 };
	private readonly SimpleMovingAverage _aoSlow = new() { Length = 34 };
	private readonly SimpleMovingAverage _acAverage = new() { Length = 5 };

	private readonly decimal?[] _jawBuffer = new decimal?[9];
	private readonly decimal?[] _teethBuffer = new decimal?[6];
	private readonly decimal?[] _lipsBuffer = new decimal?[4];
	private int _jawCount;
	private int _teethCount;
	private int _lipsCount;

	private readonly decimal[] _acHistory = new decimal[5];
	private int _acCount;

	private readonly Queue<decimal> _deMaxQueue = new();
	private readonly Queue<decimal> _deMinQueue = new();
	private decimal _deMaxSum;
	private decimal _deMinSum;
	private decimal? _previousHigh;
	private decimal? _previousLow;

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

	/// <summary>
	/// Decision value that triggers long entries.
	/// </summary>
	public decimal BuyThreshold
	{
		get => _buyThreshold.Value;
		set => _buyThreshold.Value = value;
	}

	/// <summary>
	/// Decision value that triggers short entries.
	/// </summary>
	public decimal SellThreshold
	{
		get => _sellThreshold.Value;
		set => _sellThreshold.Value = value;
	}

	/// <summary>
	/// Initial stop-loss distance in price steps.
	/// </summary>
	public decimal StopLossPoints
	{
		get => _stopLossPoints.Value;
		set => _stopLossPoints.Value = value;
	}

	/// <summary>
	/// Take-profit distance in price steps.
	/// </summary>
	public decimal TakeProfitPoints
	{
		get => _takeProfitPoints.Value;
		set => _takeProfitPoints.Value = value;
	}

	/// <summary>
	/// Trailing stop distance in price steps.
	/// </summary>
	public decimal TrailingStopPoints
	{
		get => _trailingStopPoints.Value;
		set => _trailingStopPoints.Value = value;
	}

	/// <summary>
	/// Williams %R lookback.
	/// </summary>
	public int WilliamsPeriod
	{
		get => _williamsPeriod.Value;
		set => _williamsPeriod.Value = value;
	}

	/// <summary>
	/// RSI lookback.
	/// </summary>
	public int RsiPeriod
	{
		get => _rsiPeriod.Value;
		set => _rsiPeriod.Value = value;
	}

	/// <summary>
	/// DeMarker oscillator lookback.
	/// </summary>
	public int DeMarkerPeriod
	{
		get => _deMarkerPeriod.Value;
		set => _deMarkerPeriod.Value = value;
	}

	/// <summary>
	/// Initialize <see cref="FuzzyLogicStrategy"/>.
	/// </summary>
	public FuzzyLogicStrategy()
	{
		_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(15).TimeFrame())
		.SetDisplay("Candle Type", "Type of candles to analyze", "General");

		_buyThreshold = Param(nameof(BuyThreshold), 0.15m)
		.SetDisplay("Buy Threshold", "Decision level for long entries", "Trading")
		.SetRange(0.1m, 0.5m)
		;

		_sellThreshold = Param(nameof(SellThreshold), 0.85m)
		.SetDisplay("Sell Threshold", "Decision level for short entries", "Trading")
		.SetRange(0.5m, 0.9m)
		;

		_stopLossPoints = Param(nameof(StopLossPoints), 60m)
		.SetDisplay("Stop Loss (points)", "Protective stop distance in price steps", "Risk");

		_takeProfitPoints = Param(nameof(TakeProfitPoints), 40m)
		.SetDisplay("Take Profit (points)", "Target distance in price steps", "Risk");

		_trailingStopPoints = Param(nameof(TrailingStopPoints), 0m)
		.SetDisplay("Trailing Stop (points)", "Trailing stop distance in price steps", "Risk");

		_williamsPeriod = Param(nameof(WilliamsPeriod), 14)
		.SetDisplay("Williams %R Period", "Lookback for Williams %R", "Indicators")
		;

		_rsiPeriod = Param(nameof(RsiPeriod), 14)
		.SetDisplay("RSI Period", "Lookback for RSI", "Indicators")
		;

		_deMarkerPeriod = Param(nameof(DeMarkerPeriod), 14)
		.SetDisplay("DeMarker Period", "Lookback for DeMarker", "Indicators")
		;

		Volume = 1;
	}

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

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

		Array.Clear(_jawBuffer);
		Array.Clear(_teethBuffer);
		Array.Clear(_lipsBuffer);
		_jawCount = 0;
		_teethCount = 0;
		_lipsCount = 0;

		Array.Clear(_acHistory);
		_acCount = 0;

		_deMaxQueue.Clear();
		_deMinQueue.Clear();
		_deMaxSum = 0m;
		_deMinSum = 0m;
		_previousHigh = null;
		_previousLow = null;

		_jaw.Reset();
		_teeth.Reset();
		_lips.Reset();
		_aoFast.Reset();
		_aoSlow.Reset();
		_acAverage.Reset();
	}

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

		_williamsIndicator = new WilliamsR { Length = WilliamsPeriod };
		_rsiIndicator = new RelativeStrengthIndex { Length = RsiPeriod };

		var subscription = SubscribeCandles(CandleType);
		subscription
		.BindEx(_williamsIndicator, _rsiIndicator, ProcessCandle)
		.Start();

		var step = Security?.PriceStep ?? 1m;
		var stopDistance = TrailingStopPoints > 0m ? TrailingStopPoints : StopLossPoints;
		var slUnit = stopDistance > 0m ? new Unit(stopDistance * step, UnitTypes.Absolute) : new Unit();
		var tpUnit = TakeProfitPoints > 0m ? new Unit(TakeProfitPoints * step, UnitTypes.Absolute) : new Unit();
		StartProtection(slUnit, tpUnit);

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

	private void ProcessCandle(ICandleMessage candle, IIndicatorValue wprValue, IIndicatorValue rsiValue)
	{
		// Work only with finished candles to avoid partial data.
		if (candle.State != CandleStates.Finished)
		return;

		var hl2 = (candle.HighPrice + candle.LowPrice) / 2m;

		var hl2Input = new DecimalIndicatorValue(_jaw, hl2, candle.OpenTime) { IsFinal = true };
		var jawValue = _jaw.Process(hl2Input);
		var teethValue = _teeth.Process(new DecimalIndicatorValue(_teeth, hl2, candle.OpenTime) { IsFinal = true });
		var lipsValue = _lips.Process(new DecimalIndicatorValue(_lips, hl2, candle.OpenTime) { IsFinal = true });
		var aoFastValue = _aoFast.Process(new DecimalIndicatorValue(_aoFast, hl2, candle.OpenTime) { IsFinal = true });
		var aoSlowValue = _aoSlow.Process(new DecimalIndicatorValue(_aoSlow, hl2, candle.OpenTime) { IsFinal = true });

		if (!jawValue.IsFinal || !teethValue.IsFinal || !lipsValue.IsFinal || !aoFastValue.IsFinal || !aoSlowValue.IsFinal)
		{
			UpdateDeMarker(candle);
			return;
		}

		var jawShifted = UpdateShiftBuffer(_jawBuffer, ref _jawCount, 8, jawValue.GetValue<decimal>());
		var teethShifted = UpdateShiftBuffer(_teethBuffer, ref _teethCount, 5, teethValue.GetValue<decimal>());
		var lipsShifted = UpdateShiftBuffer(_lipsBuffer, ref _lipsCount, 3, lipsValue.GetValue<decimal>());

		if (jawShifted is null || teethShifted is null || lipsShifted is null)
		{
			UpdateDeMarker(candle);
			return;
		}

		var ao = aoFastValue.GetValue<decimal>() - aoSlowValue.GetValue<decimal>();
		var acAverageValue = _acAverage.Process(new DecimalIndicatorValue(_acAverage, ao, candle.OpenTime) { IsFinal = true });
		if (!acAverageValue.IsFinal)
		{
			UpdateDeMarker(candle);
			return;
		}

		var ac = ao - acAverageValue.GetValue<decimal>();
		var deMarker = UpdateDeMarker(candle);
		if (deMarker is null)
		{
			UpdateAcHistory(ac);
			return;
		}

		if (!wprValue.IsFinal || !rsiValue.IsFinal)
		{
			UpdateAcHistory(ac);
			return;
		}

		if (_acCount < _acHistory.Length)
		{
			UpdateAcHistory(ac);
			return;
		}

		var sumGator = Math.Abs(jawShifted.Value - teethShifted.Value) + Math.Abs(teethShifted.Value - lipsShifted.Value);
		var wpr = wprValue.ToDecimal();
		var rsi = rsiValue.ToDecimal();
		var decision = CalculateDecision(sumGator, wpr, deMarker.Value, rsi);

		if (Position == 0)
		{
			if (decision > SellThreshold)
			{
				SellMarket();
			}
			else if (decision < BuyThreshold)
			{
				BuyMarket();
			}
		}

		UpdateAcHistory(ac);
	}

	private decimal? UpdateShiftBuffer(decimal?[] buffer, ref int filled, int shift, decimal value)
	{
		for (var i = 0; i < shift; i++)
		buffer[i] = buffer[i + 1];
		buffer[shift] = value;

		if (filled >= shift)
		return buffer[0];

		filled++;
		return null;
	}

	private decimal? UpdateDeMarker(ICandleMessage candle)
	{
		// Store previous extremes to compute DeMarker increments.
		if (_previousHigh is null || _previousLow is null)
		{
			_previousHigh = candle.HighPrice;
			_previousLow = candle.LowPrice;
			return null;
		}

		var deMax = Math.Max(candle.HighPrice - _previousHigh.Value, 0m);
		var deMin = Math.Max(_previousLow.Value - candle.LowPrice, 0m);

		_previousHigh = candle.HighPrice;
		_previousLow = candle.LowPrice;

		if (_deMaxQueue.Count == DeMarkerPeriod)
		{
			_deMaxSum -= _deMaxQueue.Dequeue();
			_deMinSum -= _deMinQueue.Dequeue();
		}

		_deMaxQueue.Enqueue(deMax);
		_deMinQueue.Enqueue(deMin);
		_deMaxSum += deMax;
		_deMinSum += deMin;

		if (_deMaxQueue.Count < DeMarkerPeriod)
		return null;

		var denominator = _deMaxSum + _deMinSum;
		return denominator == 0m ? 0m : _deMaxSum / denominator;
	}

	private void UpdateAcHistory(decimal ac)
	{
		for (var i = _acHistory.Length - 1; i > 0; i--)
		_acHistory[i] = _acHistory[i - 1];
		_acHistory[0] = ac;

		if (_acCount < _acHistory.Length)
		_acCount++;
	}

	private decimal CalculateDecision(decimal sumGator, decimal wpr, decimal deMarker, decimal rsi)
	{
		var rang = new decimal[5, 5];
		var summary = new decimal[5];

		var gatorLevels = new[] { 0.010m, 0.020m, 0.030m, 0.040m, 0.040m, 0.030m, 0.020m, 0.010m };
		var wprLevels = new[] { -95m, -90m, -80m, -75m, -25m, -20m, -10m, -5m };
		var acLevels = new[] { 5m, 4m, 3m, 2m, 2m, 3m, 4m, 5m };
		var deMarkerLevels = new[] { 0.15m, 0.20m, 0.25m, 0.30m, 0.70m, 0.75m, 0.80m, 0.85m };
		var rsiLevels = new[] { 25m, 30m, 35m, 40m, 60m, 65m, 70m, 75m };
		var weights = new[] { 0.133m, 0.133m, 0.133m, 0.268m, 0.333m };

		// 1) Gator oscillator membership.
		if (sumGator < gatorLevels[0])
		{
			rang[0, 0] = 0.5m;
			rang[0, 4] = 0.5m;
		}
		if (sumGator >= gatorLevels[0] && sumGator < gatorLevels[1])
		{
			var part = (sumGator - gatorLevels[0]) / (gatorLevels[1] - gatorLevels[0]);
			rang[0, 0] = (1m - part) / 2m;
			rang[0, 1] = (1m - rang[0, 0] * 2m) / 2m;
			rang[0, 4] = rang[0, 0];
			rang[0, 3] = rang[0, 1];
		}
		if (sumGator >= gatorLevels[1] && sumGator < gatorLevels[2])
		{
			rang[0, 1] = 0.5m;
			rang[0, 3] = 0.5m;
		}
		if (sumGator >= gatorLevels[2] && sumGator < gatorLevels[3])
		{
			var part = (sumGator - gatorLevels[2]) / (gatorLevels[3] - gatorLevels[2]);
			rang[0, 1] = (1m - part) / 2m;
			rang[0, 2] = 1m - rang[0, 1] * 2m;
			rang[0, 3] = rang[0, 1];
		}
		if (sumGator >= gatorLevels[3])
		rang[0, 2] = 1m;

		// 2) Williams %R membership.
		if (wpr < wprLevels[0])
		rang[1, 0] = 1m;
		if (wpr >= wprLevels[0] && wpr < wprLevels[1])
		{
			var part = (wpr - wprLevels[0]) / (wprLevels[1] - wprLevels[0]);
			rang[1, 0] = 1m - part;
			rang[1, 1] = 1m - rang[1, 0];
		}
		if (wpr >= wprLevels[1] && wpr < wprLevels[2])
		rang[1, 1] = 1m;
		if (wpr >= wprLevels[2] && wpr < wprLevels[3])
		{
			var part = (wpr - wprLevels[2]) / (wprLevels[3] - wprLevels[2]);
			rang[1, 1] = 1m - part;
			rang[1, 2] = 1m - rang[1, 1];
		}
		if (wpr >= wprLevels[3] && wpr < wprLevels[4])
		rang[1, 2] = 1m;
		if (wpr >= wprLevels[4] && wpr < wprLevels[5])
		{
			var part = (wpr - wprLevels[4]) / (wprLevels[5] - wprLevels[4]);
			rang[1, 2] = 1m - part;
			rang[1, 3] = 1m - rang[1, 2];
		}
		if (wpr >= wprLevels[5] && wpr < wprLevels[6])
		rang[1, 3] = 1m;
		if (wpr >= wprLevels[6] && wpr < wprLevels[7])
		{
			var part = (wpr - wprLevels[6]) / (wprLevels[7] - wprLevels[6]);
			rang[1, 3] = 1m - part;
			rang[1, 4] = 1m - rang[1, 3];
		}
		if (wpr >= wprLevels[7])
		rang[1, 4] = 1m;

		// 3) Acceleration/Deceleration oscillator sequences.
		var tempAcBuy = 0m;
		if (_acHistory[0] < _acHistory[1] && _acHistory[0] < 0m && _acHistory[1] < 0m)
		tempAcBuy = 2m;
		if (_acHistory[0] < _acHistory[1] && _acHistory[1] < _acHistory[2] &&
		_acHistory[0] < 0m && _acHistory[1] < 0m && _acHistory[2] < 0m)
		tempAcBuy = 3m;
		if (_acHistory[0] < _acHistory[1] && _acHistory[1] < _acHistory[2] &&
		_acHistory[2] < _acHistory[3] && _acHistory[0] < 0m && _acHistory[1] < 0m &&
		_acHistory[2] < 0m && _acHistory[3] < 0m)
		tempAcBuy = 4m;
		if (_acHistory[0] < _acHistory[1] && _acHistory[1] < _acHistory[2] &&
		_acHistory[2] < _acHistory[3] && _acHistory[3] < _acHistory[4] &&
		_acHistory[0] < 0m && _acHistory[1] < 0m && _acHistory[2] < 0m &&
		_acHistory[3] < 0m && _acHistory[4] < 0m)
		tempAcBuy = 5m;

		var tempAcSell = 0m;
		if (_acHistory[0] > _acHistory[1] && _acHistory[0] > 0m && _acHistory[1] > 0m)
		tempAcSell = 2m;
		if (_acHistory[0] > _acHistory[1] && _acHistory[1] > _acHistory[2] &&
		_acHistory[0] > 0m && _acHistory[1] > 0m && _acHistory[2] > 0m)
		tempAcSell = 3m;
		if (_acHistory[0] > _acHistory[1] && _acHistory[1] > _acHistory[2] &&
		_acHistory[2] > _acHistory[3] && _acHistory[0] > 0m && _acHistory[1] > 0m &&
		_acHistory[2] > 0m && _acHistory[3] > 0m)
		tempAcSell = 4m;
		if (_acHistory[0] > _acHistory[1] && _acHistory[1] > _acHistory[2] &&
		_acHistory[2] > _acHistory[3] && _acHistory[3] > _acHistory[4] &&
		_acHistory[0] > 0m && _acHistory[1] > 0m && _acHistory[2] > 0m &&
		_acHistory[3] > 0m && _acHistory[4] > 0m)
		tempAcSell = 5m;

		if (tempAcBuy == acLevels[0] || tempAcBuy == acLevels[1])
		rang[2, 0] = 1m;
		if (tempAcBuy == acLevels[2] || tempAcBuy == acLevels[3])
		rang[2, 1] = 1m;

		if (tempAcSell == acLevels[4] || tempAcSell == acLevels[5])
		rang[2, 3] = 1m;
		if (tempAcSell == acLevels[6] || tempAcSell == acLevels[7])
		rang[2, 4] = 1m;

		if (rang[2, 0] == 0m && rang[2, 1] == 0m && rang[2, 3] == 0m && rang[2, 4] == 0m)
		rang[2, 2] = 1m;

		// 4) DeMarker membership.
		if (deMarker < deMarkerLevels[0])
		rang[3, 0] = 1m;
		if (deMarker >= deMarkerLevels[0] && deMarker < deMarkerLevels[1])
		{
			var part = (deMarker - deMarkerLevels[0]) / (deMarkerLevels[1] - deMarkerLevels[0]);
			rang[3, 0] = 1m - part;
			rang[3, 1] = 1m - rang[3, 0];
		}
		if (deMarker >= deMarkerLevels[1] && deMarker < deMarkerLevels[2])
		rang[3, 1] = 1m;
		if (deMarker >= deMarkerLevels[2] && deMarker < deMarkerLevels[3])
		{
			var part = (deMarker - deMarkerLevels[2]) / (deMarkerLevels[3] - deMarkerLevels[2]);
			rang[3, 1] = 1m - part;
			rang[3, 2] = 1m - rang[3, 1];
		}
		if (deMarker >= deMarkerLevels[3] && deMarker < deMarkerLevels[4])
		rang[3, 2] = 1m;
		if (deMarker >= deMarkerLevels[4] && deMarker < deMarkerLevels[5])
		{
			var part = (deMarker - deMarkerLevels[4]) / (deMarkerLevels[5] - deMarkerLevels[4]);
			rang[3, 2] = 1m - part;
			rang[3, 3] = 1m - rang[3, 2];
		}
		if (deMarker >= deMarkerLevels[5] && deMarker < deMarkerLevels[6])
		rang[3, 3] = 1m;
		if (deMarker >= deMarkerLevels[6] && deMarker < deMarkerLevels[7])
		{
			var part = (deMarker - deMarkerLevels[6]) / (deMarkerLevels[7] - deMarkerLevels[6]);
			rang[3, 3] = 1m - part;
			rang[3, 4] = 1m - rang[3, 3];
		}
		if (deMarker >= deMarkerLevels[7])
		rang[3, 4] = 1m;

		// 5) RSI membership.
		if (rsi < rsiLevels[0])
		rang[4, 0] = 1m;
		if (rsi >= rsiLevels[0] && rsi < rsiLevels[1])
		{
			var part = (rsi - rsiLevels[0]) / (rsiLevels[1] - rsiLevels[0]);
			rang[4, 0] = 1m - part;
			rang[4, 1] = 1m - rang[4, 0];
		}
		if (rsi >= rsiLevels[1] && rsi < rsiLevels[2])
		rang[4, 1] = 1m;
		if (rsi >= rsiLevels[2] && rsi < rsiLevels[3])
		{
			var part = (rsi - rsiLevels[2]) / (rsiLevels[3] - rsiLevels[2]);
			rang[4, 1] = 1m - part;
			rang[4, 2] = 1m - rang[4, 1];
		}
		if (rsi >= rsiLevels[3] && rsi < rsiLevels[4])
		rang[4, 2] = 1m;
		if (rsi >= rsiLevels[4] && rsi < rsiLevels[5])
		{
			var part = (rsi - rsiLevels[4]) / (rsiLevels[5] - rsiLevels[4]);
			rang[4, 2] = 1m - part;
			rang[4, 3] = 1m - rang[4, 2];
		}
		if (rsi >= rsiLevels[5] && rsi < rsiLevels[6])
		rang[4, 3] = 1m;
		if (rsi >= rsiLevels[6] && rsi < rsiLevels[7])
		{
			var part = (rsi - rsiLevels[6]) / (rsiLevels[7] - rsiLevels[6]);
			rang[4, 3] = 1m - part;
			rang[4, 4] = 1m - rang[4, 3];
		}
		if (rsi >= rsiLevels[7])
		rang[4, 4] = 1m;

		for (var x = 0; x < 4; x++)
		{
			for (var y = 0; y < 4; y++)
			summary[x] += rang[y, x] * weights[x];
		}

		var decision = 0m;
		for (var x = 0; x < 4; x++)
		decision += summary[x] * (0.2m * (x + 1) - 0.1m);

		return decision;
	}
}