ParallelLLC/algorithmic_trading

1import logging2import time3import pandas as pd4from typing import Dict, Any, Optional5from .data_ingestion import load_data, validate_data6from .strategy_agent import StrategyAgent7from .execution_agent import ExecutionAgent8 9logger = logging.getLogger(__name__)10 11def run(config: Dict[str, Any]) -> Dict[str, Any]:12    """13    Main orchestration function that coordinates the trading workflow.14    15    Args:16        config: Configuration dictionary17        18    Returns:19        Dictionary containing execution results and statistics20    """21    start_time = time.time()22    logger.info("Starting trading system orchestration")23    24    try:25        # Initialize workflow results26        workflow_result = {27            'success': False,28            'data_loaded': False,29            'signal_generated': False,30            'order_executed': False,31            'execution_result': None,32            'errors': [],33            'execution_time': 034        }35        36        # Step 1: Load market data37        logger.info("Step 1: Loading market data")38        data = load_data(config)39        40        if data is not None and not data.empty:41            workflow_result['data_loaded'] = True42            logger.info(f"Successfully loaded {len(data)} data points")43            44            # Validate data quality45            if validate_data(data):46                logger.info("Data validation passed")47            else:48                logger.warning("Data validation failed, but continuing with workflow")49        else:50            logger.error("Failed to load market data")51            workflow_result['errors'].append("Failed to load market data")52            return workflow_result53        54        # Step 2: Generate trading signal55        logger.info("Step 2: Generating trading signal")56        strategy_agent = StrategyAgent(config)57        signal = strategy_agent.act(data)58        59        if signal and signal.get('action') != 'hold':60            workflow_result['signal_generated'] = True61            logger.info(f"Generated signal: {signal['action']} {signal['quantity']} {signal['symbol']}")62        else:63            logger.info("No actionable signal generated (hold)")64            workflow_result['signal_generated'] = True  # Hold is still a valid signal65        66        # Step 3: Execute order67        logger.info("Step 3: Executing order")68        execution_agent = ExecutionAgent(config)69        execution_result = execution_agent.act(signal)70        71        if execution_result['success']:72            workflow_result['order_executed'] = True73            workflow_result['execution_result'] = execution_result74            logger.info("Order executed successfully")75        else:76            logger.error(f"Order execution failed: {execution_result.get('error', 'Unknown error')}")77            workflow_result['errors'].append(f"Order execution failed: {execution_result.get('error')}")78        79        # Calculate execution time80        workflow_result['execution_time'] = time.time() - start_time81        workflow_result['success'] = workflow_result['data_loaded'] and workflow_result['signal_generated']82        83        logger.info(f"Trading workflow completed in {workflow_result['execution_time']:.2f} seconds")84        85        return workflow_result86        87    except Exception as e:88        logger.error(f"Error in trading workflow: {e}", exc_info=True)89        workflow_result = {90            'success': False,91            'data_loaded': False,92            'signal_generated': False,93            'order_executed': False,94            'execution_result': None,95            'errors': [str(e)],96            'execution_time': time.time() - start_time97        }98        return workflow_result99 100def run_backtest(config: Dict[str, Any], start_date: str = '2024-01-01', end_date: str = '2024-12-31') -> Dict[str, Any]:101    """102    Run backtesting simulation over historical data.103    104    Args:105        config: Configuration dictionary106        start_date: Start date for backtest107        end_date: End date for backtest108        109    Returns:110        Dictionary containing backtest results111    """112    logger.info(f"Starting backtest from {start_date} to {end_date}")113    114    try:115        # Load historical data116        data = load_data(config)117        118        if data is None or data.empty:119            logger.error("No data available for backtest")120            return {'success': False, 'error': 'No data available'}121        122        # Filter data for backtest period123        data['timestamp'] = pd.to_datetime(data['timestamp'])124        mask = (data['timestamp'] >= start_date) & (data['timestamp'] <= end_date)125        backtest_data = data.loc[mask]126        127        if backtest_data.empty:128            logger.error("No data available for specified backtest period")129            return {'success': False, 'error': 'No data for backtest period'}130        131        logger.info(f"Running backtest on {len(backtest_data)} data points")132        133        # Initialize agents134        strategy_agent = StrategyAgent(config)135        execution_agent = ExecutionAgent(config)136        137        # Track backtest results138        trades = []139        portfolio_value = config['trading']['capital']140        positions = {}141        142        # Run simulation143        for i in range(len(backtest_data)):144            current_data = backtest_data.iloc[:i+1]145            146            if len(current_data) < 50:  # Need minimum data for indicators147                continue148            149            # Generate signal150            signal = strategy_agent.act(current_data)151            152            # Execute if not hold153            if signal['action'] != 'hold':154                execution_result = execution_agent.act(signal)155                trades.append({156                    'timestamp': current_data.index[-1],157                    'signal': signal,158                    'execution': execution_result159                })160                161                # Update portfolio (simplified)162                if execution_result['success']:163                    symbol = signal['symbol']164                    if signal['action'] == 'buy':165                        positions[symbol] = positions.get(symbol, 0) + signal['quantity']166                        portfolio_value -= execution_result['total_value']167                    elif signal['action'] == 'sell':168                        positions[symbol] = positions.get(symbol, 0) - signal['quantity']169                        portfolio_value += execution_result['total_value']170        171        # Calculate final portfolio value172        final_value = portfolio_value173        for symbol, quantity in positions.items():174            if quantity > 0:175                final_price = backtest_data['close'].iloc[-1]176                final_value += quantity * final_price177        178        # Calculate performance metrics179        total_return = (final_value - config['trading']['capital']) / config['trading']['capital']180        181        backtest_results = {182            'success': True,183            'start_date': start_date,184            'end_date': end_date,185            'initial_capital': config['trading']['capital'],186            'final_value': final_value,187            'total_return': total_return,188            'total_trades': len(trades),189            'trades': trades,190            'positions': positions191        }192        193        logger.info(f"Backtest completed: {total_return:.2%} return over {len(trades)} trades")194        return backtest_results195        196    except Exception as e:197        logger.error(f"Error in backtest: {e}", exc_info=True)198        return {'success': False, 'error': str(e)}199 200def run_live_trading(config: Dict[str, Any], duration_minutes: int = 60) -> Dict[str, Any]:201    """202    Run live trading simulation for a specified duration.203    204    Args:205        config: Configuration dictionary206        duration_minutes: Duration to run live trading in minutes207        208    Returns:209        Dictionary containing live trading results210    """211    logger.info(f"Starting live trading simulation for {duration_minutes} minutes")212    213    try:214        import time215        from datetime import datetime, timedelta216        217        end_time = datetime.now() + timedelta(minutes=duration_minutes)218        trades = []219        220        while datetime.now() < end_time:221            # Run single trading cycle222            result = run(config)223            224            if result['order_executed'] and result['execution_result']['success']:225                trades.append(result['execution_result'])226            227            # Wait before next cycle228            time.sleep(60)  # Wait 1 minute between cycles229        230        live_results = {231            'success': True,232            'duration_minutes': duration_minutes,233            'total_trades': len(trades),234            'trades': trades,235            'start_time': datetime.now() - timedelta(minutes=duration_minutes),236            'end_time': datetime.now()237        }238        239        logger.info(f"Live trading completed: {len(trades)} trades executed")240        return live_results241        242    except Exception as e:243        logger.error(f"Error in live trading: {e}", exc_info=True)244        return {'success': False, 'error': str(e)}245