Estratégia FuzzyLogic
Visão geral
A estratégia FuzzyLogic replica o consultor especialista do MT5 Fuzzy logic (edição de barabashkakvn) usando a API de alto nível do StockSharp. O sistema mede a força da tendência e o esgotamento do momentum com osciladores de Bill Williams e indicadores de momentum, converte essas leituras em graus de pertinência difusa e as agrega em uma única pontuação de decisão entre 0 e 1.
As ações de trading são acionadas quando a pontuação difusa cruza limites calibrados:
- Decision > 0.75 – abrir uma posição vendida (forte esgotamento / condições de sobrecompra).
- Decision < 0.25 – abrir uma posição comprada (configuração de reversão altista forte).
As posições são gerenciadas com distâncias fixas de take-profit e stop-loss expressas em passos de preço. Quando uma distância de trailing stop é fornecida, o stop protetor é convertido em um trailing.
Conjunto de indicadores
| Componente | Finalidade |
|---|---|
| Oscilador Gator (construído a partir das linhas Alligator) | Mede a soma dos spreads mandíbula–dentes e dentes–lábios para avaliar a expansão ou contração da tendência. |
| Williams %R (14) | Detecta níveis de sobrecompra / sobrevenda. |
| Acceleration/Deceleration Oscillator (AC) | Conta mudanças consecutivas de momentum para estimar a aceleração da tendência. |
| DeMarker (14) | Confirma o esgotamento por meio de comparações de máximas/mínimas. Implementado diretamente dentro da estratégia. |
| RSI (14) | Rastreia oscilações clássicas de momentum. |
As linhas Alligator são calculadas com médias móveis suavizadas e deslocadas para frente exatamente como no consultor especialista original para reproduzir o oscilador Gator. Os valores de AC são derivados do Awesome Oscillator (diferença SMA 5/34) menos sua média móvel de 5 períodos, fornecendo leituras idênticas ao indicador iAC do MT5.
Lógica de trading
- O valor de cada indicador é mapeado para cinco conjuntos de pertinência difusa (muito baixista → muito altista). Funções lineares por partes replicam os arrays originais do MT5.
- Os cinco grupos de pertinência são ponderados (0.133, 0.133, 0.133, 0.268, 0.333) e agregados em quatro compartimentos de resumo.
- A pontuação de decisão difusa é calculada como
Σ summary[x] * (0.2 * (x + 1) - 0.1), produzindo valores no intervalo[0, 1]. - Os sinais são avaliados uma vez por vela fechada. A estratégia permanece sem posição a menos que a decisão ultrapasse os limites de entrada.
- O tamanho da ordem depende da propriedade
Volume(padrão 1). Os stops protetores são registrados por meio deStartProtection.
Gestão de risco
- StopLossPoints – distância absoluta (em passos de preço) para o stop protetor. Usado quando
TrailingStopPointsé zero. - TrailingStopPoints – se > 0, a distância do stop-loss muda para este valor e o modo trailing é ativado.
- TakeProfitPoints – distância absoluta para o alvo de lucro.
Parâmetros
| Parâmetro | Descrição |
|---|---|
CandleType |
Período / tipo de vela usado para cálculos. |
BuyThreshold |
Pontuação difusa abaixo da qual uma entrada comprada é aberta. Padrão 0.25. |
SellThreshold |
Pontuação difusa acima da qual uma entrada vendida é aberta. Padrão 0.75. |
StopLossPoints |
Distância do stop-loss em passos de preço do instrumento. Padrão 60. |
TakeProfitPoints |
Distância de take-profit em passos de preço. Padrão 20. |
TrailingStopPoints |
Distância do trailing stop em passos de preço. Padrão 0 (desativado). |
WilliamsPeriod |
Lookback para Williams %R. Padrão 14. |
RsiPeriod |
Lookback para RSI. Padrão 14. |
DeMarkerPeriod |
Lookback para o cálculo integrado de DeMarker. Padrão 14. |
Notas de implementação
- O oscilador DeMarker é implementado manualmente porque o StockSharp não expõe uma versão integrada. Os deltas de máximas e mínimas são enfileirados para reproduzir as somas do MT5.
- O histórico de AC armazena os cinco valores concluídos mais recentes para que a lógica difusa possa verificar sequências de aceleração consecutivas, assim como
iAC(..., shift)no MT5. - Os buffers de mandíbula/dentes/lábios do Alligator introduzem o mesmo deslocamento para frente (8/5/3 barras) antes de derivar os valores do histograma Gator.
- A estratégia só abre uma nova posição quando
Position == 0, respeitando o comportamento de posição única do consultor especialista original.
Passos de uso
- Vincule a estratégia a uma carteira e um ativo no Designer/Backtester.
- Configure a série de velas desejada via
CandleType. - Ajuste os limites ou as distâncias de stop se necessário.
- Inicie a estratégia; ela operará automaticamente quando a pontuação difusa cruzar os níveis configurados.
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;
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.BusinessEntities")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")
from System import TimeSpan, Math, Decimal
from StockSharp.Messages import DataType, CandleStates, Unit, UnitTypes
from StockSharp.Algo.Indicators import WilliamsR, RelativeStrengthIndex, SmoothedMovingAverage, SimpleMovingAverage
from StockSharp.Algo.Strategies import Strategy
from indicator_extensions import *
class fuzzy_logic_strategy(Strategy):
def __init__(self):
super(fuzzy_logic_strategy, self).__init__()
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(15)))
self._buy_threshold = self.Param("BuyThreshold", 0.15)
self._sell_threshold = self.Param("SellThreshold", 0.85)
self._stop_loss_points = self.Param("StopLossPoints", 60.0)
self._take_profit_points = self.Param("TakeProfitPoints", 40.0)
self._trailing_stop_points = self.Param("TrailingStopPoints", 0.0)
self._williams_period = self.Param("WilliamsPeriod", 14)
self._rsi_period = self.Param("RsiPeriod", 14)
self._demarker_period = self.Param("DeMarkerPeriod", 14)
self._jaw_buffer = [None] * 9
self._teeth_buffer = [None] * 6
self._lips_buffer = [None] * 4
self._jaw_count = 0
self._teeth_count = 0
self._lips_count = 0
self._ac_history = [0.0] * 5
self._ac_count = 0
self._de_max_queue = []
self._de_min_queue = []
self._de_max_sum = 0.0
self._de_min_sum = 0.0
self._previous_high = None
self._previous_low = None
@property
def CandleType(self):
return self._candle_type.Value
@CandleType.setter
def CandleType(self, value):
self._candle_type.Value = value
@property
def BuyThreshold(self):
return self._buy_threshold.Value
@BuyThreshold.setter
def BuyThreshold(self, value):
self._buy_threshold.Value = value
@property
def SellThreshold(self):
return self._sell_threshold.Value
@SellThreshold.setter
def SellThreshold(self, value):
self._sell_threshold.Value = value
@property
def StopLossPoints(self):
return self._stop_loss_points.Value
@StopLossPoints.setter
def StopLossPoints(self, value):
self._stop_loss_points.Value = value
@property
def TakeProfitPoints(self):
return self._take_profit_points.Value
@TakeProfitPoints.setter
def TakeProfitPoints(self, value):
self._take_profit_points.Value = value
@property
def TrailingStopPoints(self):
return self._trailing_stop_points.Value
@TrailingStopPoints.setter
def TrailingStopPoints(self, value):
self._trailing_stop_points.Value = value
@property
def WilliamsPeriod(self):
return self._williams_period.Value
@WilliamsPeriod.setter
def WilliamsPeriod(self, value):
self._williams_period.Value = value
@property
def RsiPeriod(self):
return self._rsi_period.Value
@RsiPeriod.setter
def RsiPeriod(self, value):
self._rsi_period.Value = value
@property
def DeMarkerPeriod(self):
return self._demarker_period.Value
@DeMarkerPeriod.setter
def DeMarkerPeriod(self, value):
self._demarker_period.Value = value
def OnStarted2(self, time):
super(fuzzy_logic_strategy, self).OnStarted2(time)
self._jaw_buffer = [None] * 9
self._teeth_buffer = [None] * 6
self._lips_buffer = [None] * 4
self._jaw_count = 0
self._teeth_count = 0
self._lips_count = 0
self._ac_history = [0.0] * 5
self._ac_count = 0
self._de_max_queue = []
self._de_min_queue = []
self._de_max_sum = 0.0
self._de_min_sum = 0.0
self._previous_high = None
self._previous_low = None
self._jaw = SmoothedMovingAverage()
self._jaw.Length = 13
self._teeth = SmoothedMovingAverage()
self._teeth.Length = 8
self._lips = SmoothedMovingAverage()
self._lips.Length = 5
self._ao_fast = SimpleMovingAverage()
self._ao_fast.Length = 5
self._ao_slow = SimpleMovingAverage()
self._ao_slow.Length = 34
self._ac_average = SimpleMovingAverage()
self._ac_average.Length = 5
self._williams = WilliamsR()
self._williams.Length = self.WilliamsPeriod
self._rsi = RelativeStrengthIndex()
self._rsi.Length = self.RsiPeriod
subscription = self.SubscribeCandles(self.CandleType)
subscription.BindEx(self._williams, self._rsi, self.ProcessCandle).Start()
step = float(self.Security.PriceStep) if self.Security is not None and self.Security.PriceStep is not None else 1.0
if step <= 0.0:
step = 1.0
stop_distance = float(self.TrailingStopPoints) if float(self.TrailingStopPoints) > 0.0 else float(self.StopLossPoints)
sl_unit = Unit(stop_distance * step, UnitTypes.Absolute) if stop_distance > 0.0 else Unit()
tp_unit = Unit(float(self.TakeProfitPoints) * step, UnitTypes.Absolute) if float(self.TakeProfitPoints) > 0.0 else Unit()
self.StartProtection(sl_unit, tp_unit)
def ProcessCandle(self, candle, wpr_value, rsi_value):
if candle.State != CandleStates.Finished:
return
high = float(candle.HighPrice)
low = float(candle.LowPrice)
hl2 = (high + low) / 2.0
jaw_result = process_float(self._jaw, Decimal(hl2), candle.OpenTime, True)
teeth_result = process_float(self._teeth, Decimal(hl2), candle.OpenTime, True)
lips_result = process_float(self._lips, Decimal(hl2), candle.OpenTime, True)
ao_fast_result = process_float(self._ao_fast, Decimal(hl2), candle.OpenTime, True)
ao_slow_result = process_float(self._ao_slow, Decimal(hl2), candle.OpenTime, True)
if not jaw_result.IsFinal or not teeth_result.IsFinal or not lips_result.IsFinal or not ao_fast_result.IsFinal or not ao_slow_result.IsFinal:
self._update_demarker(candle)
return
jaw_shifted = self._update_shift_buffer_jaw(float(jaw_result))
teeth_shifted = self._update_shift_buffer_teeth(float(teeth_result))
lips_shifted = self._update_shift_buffer_lips(float(lips_result))
if jaw_shifted is None or teeth_shifted is None or lips_shifted is None:
self._update_demarker(candle)
return
ao = float(ao_fast_result) - float(ao_slow_result)
ac_avg_result = process_float(self._ac_average, Decimal(ao), candle.OpenTime, True)
if not ac_avg_result.IsFinal:
self._update_demarker(candle)
return
ac = ao - float(ac_avg_result)
demarker = self._update_demarker(candle)
if demarker is None:
self._update_ac_history(ac)
return
if not wpr_value.IsFinal or not rsi_value.IsFinal:
self._update_ac_history(ac)
return
if self._ac_count < 5:
self._update_ac_history(ac)
return
sum_gator = abs(jaw_shifted - teeth_shifted) + abs(teeth_shifted - lips_shifted)
wpr = float(wpr_value)
rsi = float(rsi_value)
decision = self._calculate_decision(sum_gator, wpr, demarker, rsi)
if self.Position == 0:
if decision > float(self.SellThreshold):
self.SellMarket()
elif decision < float(self.BuyThreshold):
self.BuyMarket()
self._update_ac_history(ac)
def _update_shift_buffer_jaw(self, value):
shift = 8
for i in range(shift):
self._jaw_buffer[i] = self._jaw_buffer[i + 1]
self._jaw_buffer[shift] = value
if self._jaw_count >= shift:
return self._jaw_buffer[0]
self._jaw_count += 1
return None
def _update_shift_buffer_teeth(self, value):
shift = 5
for i in range(shift):
self._teeth_buffer[i] = self._teeth_buffer[i + 1]
self._teeth_buffer[shift] = value
if self._teeth_count >= shift:
return self._teeth_buffer[0]
self._teeth_count += 1
return None
def _update_shift_buffer_lips(self, value):
shift = 3
for i in range(shift):
self._lips_buffer[i] = self._lips_buffer[i + 1]
self._lips_buffer[shift] = value
if self._lips_count >= shift:
return self._lips_buffer[0]
self._lips_count += 1
return None
def _update_demarker(self, candle):
high = float(candle.HighPrice)
low = float(candle.LowPrice)
if self._previous_high is None or self._previous_low is None:
self._previous_high = high
self._previous_low = low
return None
de_max = max(high - self._previous_high, 0.0)
de_min = max(self._previous_low - low, 0.0)
self._previous_high = high
self._previous_low = low
period = int(self.DeMarkerPeriod)
if len(self._de_max_queue) == period:
self._de_max_sum -= self._de_max_queue.pop(0)
self._de_min_sum -= self._de_min_queue.pop(0)
self._de_max_queue.append(de_max)
self._de_min_queue.append(de_min)
self._de_max_sum += de_max
self._de_min_sum += de_min
if len(self._de_max_queue) < period:
return None
denominator = self._de_max_sum + self._de_min_sum
if denominator == 0.0:
return 0.0
return self._de_max_sum / denominator
def _update_ac_history(self, ac):
for i in range(len(self._ac_history) - 1, 0, -1):
self._ac_history[i] = self._ac_history[i - 1]
self._ac_history[0] = ac
if self._ac_count < len(self._ac_history):
self._ac_count += 1
def _calculate_decision(self, sum_gator, wpr, demarker, rsi):
rang = [[0.0] * 5 for _ in range(5)]
summary = [0.0] * 5
gator_levels = [0.010, 0.020, 0.030, 0.040, 0.040, 0.030, 0.020, 0.010]
wpr_levels = [-95.0, -90.0, -80.0, -75.0, -25.0, -20.0, -10.0, -5.0]
ac_levels = [5.0, 4.0, 3.0, 2.0, 2.0, 3.0, 4.0, 5.0]
demarker_levels = [0.15, 0.20, 0.25, 0.30, 0.70, 0.75, 0.80, 0.85]
rsi_levels = [25.0, 30.0, 35.0, 40.0, 60.0, 65.0, 70.0, 75.0]
weights = [0.133, 0.133, 0.133, 0.268, 0.333]
# 1) Gator oscillator membership
if sum_gator < gator_levels[0]:
rang[0][0] = 0.5
rang[0][4] = 0.5
if sum_gator >= gator_levels[0] and sum_gator < gator_levels[1]:
part = (sum_gator - gator_levels[0]) / (gator_levels[1] - gator_levels[0])
rang[0][0] = (1.0 - part) / 2.0
rang[0][1] = (1.0 - rang[0][0] * 2.0) / 2.0
rang[0][4] = rang[0][0]
rang[0][3] = rang[0][1]
if sum_gator >= gator_levels[1] and sum_gator < gator_levels[2]:
rang[0][1] = 0.5
rang[0][3] = 0.5
if sum_gator >= gator_levels[2] and sum_gator < gator_levels[3]:
part = (sum_gator - gator_levels[2]) / (gator_levels[3] - gator_levels[2])
rang[0][1] = (1.0 - part) / 2.0
rang[0][2] = 1.0 - rang[0][1] * 2.0
rang[0][3] = rang[0][1]
if sum_gator >= gator_levels[3]:
rang[0][2] = 1.0
# 2) Williams %R membership
if wpr < wpr_levels[0]:
rang[1][0] = 1.0
if wpr >= wpr_levels[0] and wpr < wpr_levels[1]:
part = (wpr - wpr_levels[0]) / (wpr_levels[1] - wpr_levels[0])
rang[1][0] = 1.0 - part
rang[1][1] = 1.0 - rang[1][0]
if wpr >= wpr_levels[1] and wpr < wpr_levels[2]:
rang[1][1] = 1.0
if wpr >= wpr_levels[2] and wpr < wpr_levels[3]:
part = (wpr - wpr_levels[2]) / (wpr_levels[3] - wpr_levels[2])
rang[1][1] = 1.0 - part
rang[1][2] = 1.0 - rang[1][1]
if wpr >= wpr_levels[3] and wpr < wpr_levels[4]:
rang[1][2] = 1.0
if wpr >= wpr_levels[4] and wpr < wpr_levels[5]:
part = (wpr - wpr_levels[4]) / (wpr_levels[5] - wpr_levels[4])
rang[1][2] = 1.0 - part
rang[1][3] = 1.0 - rang[1][2]
if wpr >= wpr_levels[5] and wpr < wpr_levels[6]:
rang[1][3] = 1.0
if wpr >= wpr_levels[6] and wpr < wpr_levels[7]:
part = (wpr - wpr_levels[6]) / (wpr_levels[7] - wpr_levels[6])
rang[1][3] = 1.0 - part
rang[1][4] = 1.0 - rang[1][3]
if wpr >= wpr_levels[7]:
rang[1][4] = 1.0
# 3) Acceleration/Deceleration oscillator sequences
h = self._ac_history
temp_ac_buy = 0.0
if h[0] < h[1] and h[0] < 0.0 and h[1] < 0.0:
temp_ac_buy = 2.0
if h[0] < h[1] and h[1] < h[2] and h[0] < 0.0 and h[1] < 0.0 and h[2] < 0.0:
temp_ac_buy = 3.0
if h[0] < h[1] and h[1] < h[2] and h[2] < h[3] and h[0] < 0.0 and h[1] < 0.0 and h[2] < 0.0 and h[3] < 0.0:
temp_ac_buy = 4.0
if h[0] < h[1] and h[1] < h[2] and h[2] < h[3] and h[3] < h[4] and h[0] < 0.0 and h[1] < 0.0 and h[2] < 0.0 and h[3] < 0.0 and h[4] < 0.0:
temp_ac_buy = 5.0
temp_ac_sell = 0.0
if h[0] > h[1] and h[0] > 0.0 and h[1] > 0.0:
temp_ac_sell = 2.0
if h[0] > h[1] and h[1] > h[2] and h[0] > 0.0 and h[1] > 0.0 and h[2] > 0.0:
temp_ac_sell = 3.0
if h[0] > h[1] and h[1] > h[2] and h[2] > h[3] and h[0] > 0.0 and h[1] > 0.0 and h[2] > 0.0 and h[3] > 0.0:
temp_ac_sell = 4.0
if h[0] > h[1] and h[1] > h[2] and h[2] > h[3] and h[3] > h[4] and h[0] > 0.0 and h[1] > 0.0 and h[2] > 0.0 and h[3] > 0.0 and h[4] > 0.0:
temp_ac_sell = 5.0
if temp_ac_buy == ac_levels[0] or temp_ac_buy == ac_levels[1]:
rang[2][0] = 1.0
if temp_ac_buy == ac_levels[2] or temp_ac_buy == ac_levels[3]:
rang[2][1] = 1.0
if temp_ac_sell == ac_levels[4] or temp_ac_sell == ac_levels[5]:
rang[2][3] = 1.0
if temp_ac_sell == ac_levels[6] or temp_ac_sell == ac_levels[7]:
rang[2][4] = 1.0
if rang[2][0] == 0.0 and rang[2][1] == 0.0 and rang[2][3] == 0.0 and rang[2][4] == 0.0:
rang[2][2] = 1.0
# 4) DeMarker membership
if demarker < demarker_levels[0]:
rang[3][0] = 1.0
if demarker >= demarker_levels[0] and demarker < demarker_levels[1]:
part = (demarker - demarker_levels[0]) / (demarker_levels[1] - demarker_levels[0])
rang[3][0] = 1.0 - part
rang[3][1] = 1.0 - rang[3][0]
if demarker >= demarker_levels[1] and demarker < demarker_levels[2]:
rang[3][1] = 1.0
if demarker >= demarker_levels[2] and demarker < demarker_levels[3]:
part = (demarker - demarker_levels[2]) / (demarker_levels[3] - demarker_levels[2])
rang[3][1] = 1.0 - part
rang[3][2] = 1.0 - rang[3][1]
if demarker >= demarker_levels[3] and demarker < demarker_levels[4]:
rang[3][2] = 1.0
if demarker >= demarker_levels[4] and demarker < demarker_levels[5]:
part = (demarker - demarker_levels[4]) / (demarker_levels[5] - demarker_levels[4])
rang[3][2] = 1.0 - part
rang[3][3] = 1.0 - rang[3][2]
if demarker >= demarker_levels[5] and demarker < demarker_levels[6]:
rang[3][3] = 1.0
if demarker >= demarker_levels[6] and demarker < demarker_levels[7]:
part = (demarker - demarker_levels[6]) / (demarker_levels[7] - demarker_levels[6])
rang[3][3] = 1.0 - part
rang[3][4] = 1.0 - rang[3][3]
if demarker >= demarker_levels[7]:
rang[3][4] = 1.0
# 5) RSI membership
if rsi < rsi_levels[0]:
rang[4][0] = 1.0
if rsi >= rsi_levels[0] and rsi < rsi_levels[1]:
part = (rsi - rsi_levels[0]) / (rsi_levels[1] - rsi_levels[0])
rang[4][0] = 1.0 - part
rang[4][1] = 1.0 - rang[4][0]
if rsi >= rsi_levels[1] and rsi < rsi_levels[2]:
rang[4][1] = 1.0
if rsi >= rsi_levels[2] and rsi < rsi_levels[3]:
part = (rsi - rsi_levels[2]) / (rsi_levels[3] - rsi_levels[2])
rang[4][1] = 1.0 - part
rang[4][2] = 1.0 - rang[4][1]
if rsi >= rsi_levels[3] and rsi < rsi_levels[4]:
rang[4][2] = 1.0
if rsi >= rsi_levels[4] and rsi < rsi_levels[5]:
part = (rsi - rsi_levels[4]) / (rsi_levels[5] - rsi_levels[4])
rang[4][2] = 1.0 - part
rang[4][3] = 1.0 - rang[4][2]
if rsi >= rsi_levels[5] and rsi < rsi_levels[6]:
rang[4][3] = 1.0
if rsi >= rsi_levels[6] and rsi < rsi_levels[7]:
part = (rsi - rsi_levels[6]) / (rsi_levels[7] - rsi_levels[6])
rang[4][3] = 1.0 - part
rang[4][4] = 1.0 - rang[4][3]
if rsi >= rsi_levels[7]:
rang[4][4] = 1.0
for x in range(4):
for y in range(4):
summary[x] += rang[y][x] * weights[x]
decision = 0.0
for x in range(4):
decision += summary[x] * (0.2 * (x + 1) - 0.1)
return decision
def OnReseted(self):
super(fuzzy_logic_strategy, self).OnReseted()
self._jaw_buffer = [None] * 9
self._teeth_buffer = [None] * 6
self._lips_buffer = [None] * 4
self._jaw_count = 0
self._teeth_count = 0
self._lips_count = 0
self._ac_history = [0.0] * 5
self._ac_count = 0
self._de_max_queue = []
self._de_min_queue = []
self._de_max_sum = 0.0
self._de_min_sum = 0.0
self._previous_high = None
self._previous_low = None
def CreateClone(self):
return fuzzy_logic_strategy()