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zhutoutoutousan
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"""
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Backtesting Engine for MetaTrader5
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This module provides the core backtesting functionality using MT5 historical data.
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"""
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from datetime import datetime, timedelta
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from typing import Optional, Dict, Any, List
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import MetaTrader5 as mt5
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import pandas as pd
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import numpy as np
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from base_strategy import BaseStrategy
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class BacktestEngine:
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"""
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Main backtesting engine that runs strategies on historical data.
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"""
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def __init__(self, strategy: BaseStrategy, start_date: datetime, end_date: datetime):
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"""
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Initialize the backtesting engine.
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Args:
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strategy: Strategy instance to backtest
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start_date: Start date for backtesting
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end_date: End date for backtesting
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"""
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self.strategy = strategy
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self.start_date = start_date
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self.end_date = end_date
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# Initialize MT5 connection
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if not mt5.initialize():
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raise RuntimeError(f"MT5 initialization failed: {mt5.last_error()}")
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# Indicator handles
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self.indicator_handles = {}
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self.setup_indicators()
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def setup_indicators(self):
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"""Setup all required indicators for the strategy."""
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required_indicators = self.strategy.get_required_indicators()
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for indicator_name, params in required_indicators.items():
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handle = None
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if indicator_name.lower() == 'rsi':
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handle = mt5.iRSI(
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self.strategy.symbol,
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self.strategy.timeframe,
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params.get('period', 14),
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params.get('applied_price', mt5.PRICE_CLOSE)
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)
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elif indicator_name.lower() == 'ema':
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handle = mt5.iMA(
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self.strategy.symbol,
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self.strategy.timeframe,
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params.get('period', 50),
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0, # shift
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mt5.MODE_EMA,
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params.get('applied_price', mt5.PRICE_CLOSE)
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)
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elif indicator_name.lower() == 'sma':
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handle = mt5.iMA(
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self.strategy.symbol,
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self.strategy.timeframe,
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params.get('period', 50),
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0, # shift
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mt5.MODE_SMA,
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params.get('applied_price', mt5.PRICE_CLOSE)
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)
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elif indicator_name.lower() == 'atr':
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handle = mt5.iATR(
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self.strategy.symbol,
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self.strategy.timeframe,
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params.get('period', 14)
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)
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elif indicator_name.lower() == 'macd':
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handle = mt5.iMACD(
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self.strategy.symbol,
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self.strategy.timeframe,
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params.get('fast', 12),
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params.get('slow', 26),
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params.get('signal', 9),
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params.get('applied_price', mt5.PRICE_CLOSE)
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)
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if handle is not None and handle != mt5.INVALID_HANDLE:
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self.indicator_handles[indicator_name] = handle
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else:
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print(f"Warning: Failed to create {indicator_name} indicator")
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def get_indicator_values(self, indicator_name: str, count: int = 1) -> Optional[np.ndarray]:
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"""
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Get indicator values.
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Args:
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indicator_name: Name of the indicator
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count: Number of values to retrieve
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Returns:
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Array of indicator values or None
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"""
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if indicator_name not in self.indicator_handles:
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return None
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handle = self.indicator_handles[indicator_name]
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buffer = np.zeros(count, dtype=float)
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if indicator_name.lower() == 'macd':
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# MACD returns 3 buffers
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result = mt5.copy_buffer(handle, 0, 0, count) # Main line
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if result is None:
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return None
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return np.array(result)
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else:
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result = mt5.copy_buffer(handle, 0, 0, count)
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if result is None:
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return None
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return np.array(result)
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def get_bar_data(self, time: datetime) -> Optional[Dict[str, Any]]:
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"""
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Get bar data and indicator values for a specific time.
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Args:
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time: Bar time
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Returns:
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Dictionary with bar data and indicators
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"""
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# Get rates
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rates = mt5.copy_rates_from(
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self.strategy.symbol,
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self.strategy.timeframe,
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time,
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1
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)
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if rates is None or len(rates) == 0:
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return None
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rate = rates[0]
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# Get spread
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symbol_info = mt5.symbol_info(self.strategy.symbol)
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spread = symbol_info.spread if symbol_info else 0
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# Build bar data
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bar_data = {
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'time': datetime.fromtimestamp(rate['time']),
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'open': float(rate['open']),
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'high': float(rate['high']),
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'low': float(rate['low']),
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'close': float(rate['close']),
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'tick_volume': int(rate['tick_volume']),
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'spread': spread,
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'indicators': {}
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}
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# Get indicator values
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for indicator_name in self.indicator_handles.keys():
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values = self.get_indicator_values(indicator_name, 2)
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if values is not None and len(values) >= 1:
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bar_data['indicators'][indicator_name] = values[0]
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# Also add to top level for convenience
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bar_data[indicator_name.lower()] = values[0]
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return bar_data
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def run(self) -> Dict[str, Any]:
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"""
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Run the backtest.
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Returns:
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Dictionary with backtest results and performance metrics
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"""
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print(f"Starting backtest from {self.start_date} to {self.end_date}")
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print(f"Symbol: {self.strategy.symbol}, Timeframe: {self.strategy.timeframe}")
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# Get all bars in the date range
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rates = mt5.copy_rates_range(
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self.strategy.symbol,
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self.strategy.timeframe,
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self.start_date,
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self.end_date
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)
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if rates is None or len(rates) == 0:
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raise ValueError(f"No data available for {self.strategy.symbol} in the specified date range")
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print(f"Processing {len(rates)} bars...")
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# Process each bar
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processed_bars = 0
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for i, rate in enumerate(rates):
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bar_time = datetime.fromtimestamp(rate['time'])
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# Get full bar data with indicators
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bar_data = self.get_bar_data(bar_time)
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if bar_data is None:
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continue
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# Check stop loss/take profit on current position
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if self.strategy.position is not None:
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self.strategy.check_stop_loss_take_profit(bar_data['close'])
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# Call strategy on_bar method
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try:
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self.strategy.on_bar(bar_data)
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except Exception as e:
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print(f"Error in strategy on_bar at {bar_time}: {e}")
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continue
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# Update equity (unrealized P&L)
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if self.strategy.position is not None:
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if self.strategy.position['type'] == 'BUY':
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unrealized_pnl = (bar_data['close'] - self.strategy.position['open_price']) * \
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self.strategy.position['volume'] * 10000 * 10
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else:
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unrealized_pnl = (self.strategy.position['open_price'] - bar_data['close']) * \
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self.strategy.position['volume'] * 10000 * 10
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self.strategy.equity = self.strategy.current_balance + unrealized_pnl
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else:
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self.strategy.equity = self.strategy.current_balance
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processed_bars += 1
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if processed_bars % 100 == 0:
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print(f"Processed {processed_bars}/{len(rates)} bars...")
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# Close any open position at the end
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if self.strategy.position is not None:
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last_bar = rates[-1]
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last_price = float(last_bar['close'])
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self.strategy.close_position(last_price)
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print(f"Backtest completed. Processed {processed_bars} bars.")
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# Get performance metrics
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metrics = self.strategy.get_performance_metrics()
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# Cleanup
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self.cleanup()
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return {
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'metrics': metrics,
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'trades': self.strategy.closed_trades,
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'strategy_name': self.strategy.__class__.__name__
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}
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def cleanup(self):
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"""Clean up indicator handles and MT5 connection."""
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for handle in self.indicator_handles.values():
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mt5.indicator_release(handle)
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mt5.shutdown()
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