increase prediction horizon

core/trading_executor.py

@@ -849,7 +849,116 @@ class TradingExecutor:
     def get_trade_history(self) -> List[TradeRecord]:
         """Get trade history"""
         return self.trade_history.copy()
-    
+
+    def export_trades_to_csv(self, filename: Optional[str] = None) -> str:
+        """Export trade history to CSV file with comprehensive analysis"""
+        import csv
+        from pathlib import Path
+
+        if not self.trade_history:
+            logger.warning("No trades to export")
+            return ""
+
+        # Generate filename if not provided
+        if filename is None:
+            timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+            filename = f"trade_history_{timestamp}.csv"
+
+        # Ensure .csv extension
+        if not filename.endswith('.csv'):
+            filename += '.csv'
+
+        # Create trades directory if it doesn't exist
+        trades_dir = Path("trades")
+        trades_dir.mkdir(exist_ok=True)
+        filepath = trades_dir / filename
+
+        try:
+            with open(filepath, 'w', newline='', encoding='utf-8') as csvfile:
+                fieldnames = [
+                    'symbol', 'side', 'quantity', 'entry_price', 'exit_price',
+                    'entry_time', 'exit_time', 'pnl', 'fees', 'confidence',
+                    'hold_time_seconds', 'hold_time_minutes', 'leverage',
+                    'pnl_percentage', 'net_pnl', 'profit_loss', 'trade_duration',
+                    'entry_hour', 'exit_hour', 'day_of_week'
+                ]
+                writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
+                writer.writeheader()
+
+                total_pnl = 0
+                winning_trades = 0
+                losing_trades = 0
+
+                for trade in self.trade_history:
+                    # Calculate additional metrics
+                    pnl_percentage = (trade.pnl / trade.entry_price) * 100 if trade.entry_price != 0 else 0
+                    net_pnl = trade.pnl - trade.fees
+                    profit_loss = "PROFIT" if net_pnl > 0 else "LOSS"
+                    trade_duration = trade.exit_time - trade.entry_time
+                    hold_time_minutes = trade.hold_time_seconds / 60
+
+                    # Track statistics
+                    total_pnl += net_pnl
+                    if net_pnl > 0:
+                        winning_trades += 1
+                    else:
+                        losing_trades += 1
+
+                    writer.writerow({
+                        'symbol': trade.symbol,
+                        'side': trade.side,
+                        'quantity': trade.quantity,
+                        'entry_price': trade.entry_price,
+                        'exit_price': trade.exit_price,
+                        'entry_time': trade.entry_time.strftime('%Y-%m-%d %H:%M:%S'),
+                        'exit_time': trade.exit_time.strftime('%Y-%m-%d %H:%M:%S'),
+                        'pnl': trade.pnl,
+                        'fees': trade.fees,
+                        'confidence': trade.confidence,
+                        'hold_time_seconds': trade.hold_time_seconds,
+                        'hold_time_minutes': hold_time_minutes,
+                        'leverage': trade.leverage,
+                        'pnl_percentage': pnl_percentage,
+                        'net_pnl': net_pnl,
+                        'profit_loss': profit_loss,
+                        'trade_duration': str(trade_duration),
+                        'entry_hour': trade.entry_time.hour,
+                        'exit_hour': trade.exit_time.hour,
+                        'day_of_week': trade.entry_time.strftime('%A')
+                    })
+
+            # Create summary statistics file
+            summary_filename = filename.replace('.csv', '_summary.txt')
+            summary_filepath = trades_dir / summary_filename
+
+            total_trades = len(self.trade_history)
+            win_rate = (winning_trades / total_trades * 100) if total_trades > 0 else 0
+            avg_pnl = total_pnl / total_trades if total_trades > 0 else 0
+            avg_hold_time = sum(t.hold_time_seconds for t in self.trade_history) / total_trades if total_trades > 0 else 0
+
+            with open(summary_filepath, 'w', encoding='utf-8') as f:
+                f.write("TRADE ANALYSIS SUMMARY\n")
+                f.write("=" * 50 + "\n")
+                f.write(f"Total Trades: {total_trades}\n")
+                f.write(f"Winning Trades: {winning_trades}\n")
+                f.write(f"Losing Trades: {losing_trades}\n")
+                f.write(f"Win Rate: {win_rate:.1f}%\n")
+                f.write(f"Total P&L: ${total_pnl:.2f}\n")
+                f.write(f"Average P&L per Trade: ${avg_pnl:.2f}\n")
+                f.write(f"Average Hold Time: {avg_hold_time:.1f} seconds ({avg_hold_time/60:.1f} minutes)\n")
+                f.write(f"Export Time: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n")
+                f.write(f"Data File: {filename}\n")
+
+            logger.info(f"📊 Trade history exported to: {filepath}")
+            logger.info(f"📈 Trade summary saved to: {summary_filepath}")
+            logger.info(f"📊 Total Trades: {total_trades} | Win Rate: {win_rate:.1f}% | Total P&L: ${total_pnl:.2f}")
+
+            return str(filepath)
+
+        except Exception as e:
+            logger.error(f"Error exporting trades to CSV: {e}")
+            return ""
+
     def get_daily_stats(self) -> Dict[str, Any]:
         """Get daily trading statistics with enhanced fee analysis"""
         total_pnl = sum(trade.pnl for trade in self.trade_history)