Esta estrategia reproduce la lógica central del experto MQL4 original "trade panel with autopilot". Agrega la dirección del precio en múltiples marcos temporales y abre o cierra una única posición según el sentimiento dominante del mercado.
La estrategia monitorea las dos últimas velas en ocho marcos temporales diferentes (M1, M5, M15, M30, H1, H4, D1, W1). Para cada marco temporal compara varios componentes de precio entre las dos velas más recientes:
Open
High
Low
(High + Low) / 2
Close
(High + Low + Close) / 3
(High + Low + Close + Close) / 4
Cada comparación contribuye a una puntuación de compra o venta. Las puntuaciones de todos los marcos temporales se suman y se convierten en porcentajes. Cuando el porcentaje de compra o venta cruza un umbral configurado, la estrategia entra en una posición. La posición existente se cierra si el porcentaje opuesto cae por debajo del umbral de cierre.
Parámetros
Autopilot — activa o desactiva el trading automático.
OpenThreshold — nivel de porcentaje requerido para abrir una nueva posición. Por defecto: 85.
CloseThreshold — nivel de porcentaje para cerrar una posición existente. Por defecto: 55.
LotFixed — volumen fijo de la orden cuando UseFixedLot está habilitado.
LotPercent — volumen como porcentaje del valor de la cartera cuando UseFixedLot está deshabilitado.
UseFixedLot — alterna entre volumen fijo y porcentual.
UseStopLoss — inicia la protección de la posición cuando está habilitado.
Lógica de trading
Suscribirse a las velas en todos los marcos temporales configurados.
Calcular las puntuaciones de compra/venta para cada nueva vela completada.
Sumar las puntuaciones por marcos temporales y calcular los porcentajes de compra/venta.
Si Autopilot está deshabilitado, la estrategia solo realiza seguimiento de las puntuaciones.
Si no hay posición abierta y el porcentaje de compra supera OpenThreshold, entrar en una posición larga. Si el porcentaje de venta supera el umbral, entrar en una posición corta.
Si existe una posición larga y el porcentaje de compra cae por debajo de CloseThreshold, salir de la posición. La misma lógica aplica para posiciones cortas usando el porcentaje de venta.
Notas
La estrategia mantiene como máximo una posición abierta a la vez.
La gestión opcional de stop-loss se activa mediante StartProtection() cuando UseStopLoss es verdadero.
using System;
using System.Collections.Generic;
using Ecng.Common;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
/// <summary>
/// Trade panel autopilot strategy v2.
/// Aggregates 7 price comparison metrics over rolling window.
/// Buys when buy percentage exceeds open threshold, sells on opposite.
/// </summary>
public class TradePanelAutopilotStrategy : Strategy
{
private readonly StrategyParam<decimal> _openThreshold;
private readonly StrategyParam<decimal> _closeThreshold;
private readonly StrategyParam<int> _windowSize;
private readonly StrategyParam<DataType> _candleType;
private readonly Queue<(int buy, int sell)> _signalWindow = new();
private ICandleMessage _prevCandle;
public decimal OpenThreshold { get => _openThreshold.Value; set => _openThreshold.Value = value; }
public decimal CloseThreshold { get => _closeThreshold.Value; set => _closeThreshold.Value = value; }
public int WindowSize { get => _windowSize.Value; set => _windowSize.Value = value; }
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public TradePanelAutopilotStrategy()
{
_openThreshold = Param(nameof(OpenThreshold), 65m)
.SetDisplay("Open %", "Threshold for new position", "General");
_closeThreshold = Param(nameof(CloseThreshold), 40m)
.SetDisplay("Close %", "Threshold for closing", "General");
_windowSize = Param(nameof(WindowSize), 8)
.SetGreaterThanZero()
.SetDisplay("Window Size", "Number of candles for signal aggregation", "General");
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(4).TimeFrame())
.SetDisplay("Candle Type", "Candle timeframe", "General");
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_prevCandle = null;
_signalWindow.Clear();
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_prevCandle = null;
_signalWindow.Clear();
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;
if (_prevCandle == null)
{
_prevCandle = candle;
return;
}
int buy = 0, sell = 0;
if (candle.OpenPrice > _prevCandle.OpenPrice) buy++; else sell++;
if (candle.HighPrice > _prevCandle.HighPrice) buy++; else sell++;
if (candle.LowPrice > _prevCandle.LowPrice) buy++; else sell++;
if (candle.ClosePrice > _prevCandle.ClosePrice) buy++; else sell++;
var hlCurr = (candle.HighPrice + candle.LowPrice) / 2m;
var hlPrev = (_prevCandle.HighPrice + _prevCandle.LowPrice) / 2m;
if (hlCurr > hlPrev) buy++; else sell++;
var hlcCurr = (candle.HighPrice + candle.LowPrice + candle.ClosePrice) / 3m;
var hlcPrev = (_prevCandle.HighPrice + _prevCandle.LowPrice + _prevCandle.ClosePrice) / 3m;
if (hlcCurr > hlcPrev) buy++; else sell++;
var hlccCurr = (candle.HighPrice + candle.LowPrice + 2m * candle.ClosePrice) / 4m;
var hlccPrev = (_prevCandle.HighPrice + _prevCandle.LowPrice + 2m * _prevCandle.ClosePrice) / 4m;
if (hlccCurr > hlccPrev) buy++; else sell++;
_signalWindow.Enqueue((buy, sell));
while (_signalWindow.Count > WindowSize)
_signalWindow.Dequeue();
_prevCandle = candle;
if (_signalWindow.Count < WindowSize)
return;
int totalBuy = 0, totalSell = 0;
foreach (var (b, s) in _signalWindow)
{
totalBuy += b;
totalSell += s;
}
var total = totalBuy + totalSell;
if (total == 0) return;
var buyPct = (decimal)totalBuy / total * 100m;
var sellPct = (decimal)totalSell / total * 100m;
if (Position > 0 && buyPct < CloseThreshold)
SellMarket();
else if (Position < 0 && sellPct < CloseThreshold)
BuyMarket();
if (Position == 0)
{
if (buyPct >= OpenThreshold)
BuyMarket();
else if (sellPct >= OpenThreshold)
SellMarket();
}
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")
from System import TimeSpan
from StockSharp.Messages import DataType, CandleStates
from StockSharp.Algo.Strategies import Strategy
class trade_panel_autopilot_strategy(Strategy):
def __init__(self):
super(trade_panel_autopilot_strategy, self).__init__()
self._open_threshold = self.Param("OpenThreshold", 65.0) \
.SetDisplay("Open %", "Threshold for new position", "General")
self._close_threshold = self.Param("CloseThreshold", 40.0) \
.SetDisplay("Close %", "Threshold for closing", "General")
self._window_size = self.Param("WindowSize", 8) \
.SetDisplay("Window Size", "Number of candles for signal aggregation", "General")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))) \
.SetDisplay("Candle Type", "Candle timeframe", "General")
self._signal_window = []
self._prev_candle = None
@property
def open_threshold(self):
return self._open_threshold.Value
@property
def close_threshold(self):
return self._close_threshold.Value
@property
def window_size(self):
return self._window_size.Value
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(trade_panel_autopilot_strategy, self).OnReseted()
self._prev_candle = None
self._signal_window = []
def OnStarted2(self, time):
super(trade_panel_autopilot_strategy, self).OnStarted2(time)
self._prev_candle = None
self._signal_window = []
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(self.process_candle).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawOwnTrades(area)
def process_candle(self, candle):
if candle.State != CandleStates.Finished:
return
if self._prev_candle is None:
self._prev_candle = candle
return
buy = 0
sell = 0
if float(candle.OpenPrice) > float(self._prev_candle.OpenPrice):
buy += 1
else:
sell += 1
if float(candle.HighPrice) > float(self._prev_candle.HighPrice):
buy += 1
else:
sell += 1
if float(candle.LowPrice) > float(self._prev_candle.LowPrice):
buy += 1
else:
sell += 1
if float(candle.ClosePrice) > float(self._prev_candle.ClosePrice):
buy += 1
else:
sell += 1
hl_curr = (float(candle.HighPrice) + float(candle.LowPrice)) / 2.0
hl_prev = (float(self._prev_candle.HighPrice) + float(self._prev_candle.LowPrice)) / 2.0
if hl_curr > hl_prev:
buy += 1
else:
sell += 1
hlc_curr = (float(candle.HighPrice) + float(candle.LowPrice) + float(candle.ClosePrice)) / 3.0
hlc_prev = (float(self._prev_candle.HighPrice) + float(self._prev_candle.LowPrice) + float(self._prev_candle.ClosePrice)) / 3.0
if hlc_curr > hlc_prev:
buy += 1
else:
sell += 1
hlcc_curr = (float(candle.HighPrice) + float(candle.LowPrice) + 2.0 * float(candle.ClosePrice)) / 4.0
hlcc_prev = (float(self._prev_candle.HighPrice) + float(self._prev_candle.LowPrice) + 2.0 * float(self._prev_candle.ClosePrice)) / 4.0
if hlcc_curr > hlcc_prev:
buy += 1
else:
sell += 1
self._signal_window.append((buy, sell))
ws = int(self.window_size)
while len(self._signal_window) > ws:
self._signal_window.pop(0)
self._prev_candle = candle
if len(self._signal_window) < ws:
return
total_buy = 0
total_sell = 0
for b, s in self._signal_window:
total_buy += b
total_sell += s
total = total_buy + total_sell
if total == 0:
return
buy_pct = float(total_buy) / float(total) * 100.0
sell_pct = float(total_sell) / float(total) * 100.0
close_threshold = float(self.close_threshold)
open_threshold = float(self.open_threshold)
if self.Position > 0 and buy_pct < close_threshold:
self.SellMarket()
elif self.Position < 0 and sell_pct < close_threshold:
self.BuyMarket()
if self.Position == 0:
if buy_pct >= open_threshold:
self.BuyMarket()
elif sell_pct >= open_threshold:
self.SellMarket()
def CreateClone(self):
return trade_panel_autopilot_strategy()