# Trading Algorithm Project

A production-ready modular trading system that supports multiple strategies for paper and live trading on Alpaca Markets.

## Features

- **Multiple Strategy Support**: Conservative and Enhanced trend-following strategies
- **Paper & Live Trading**: Safe testing with paper trading, production-ready for live trading
- **Modular Architecture**: Clean separation of concerns for easy maintenance
- **Risk Management**: Position sizing, drawdown limits, and trailing stops
- **Professional Logging**: Comprehensive trade and performance logging
- **Configuration Management**: Environment-based and file-based configuration
- **Strategy Comparison**: Built-in tools to compare strategy performance

## Project Structure

```
trading/
├── src/
│   ├── data_handler.py          # Market data retrieval and processing
│   ├── strategy_conservative.py # Conservative trend-following strategy
│   ├── strategy_enhanced.py     # Enhanced trend-following with tighter risk controls
│   ├── strategy_factory.py      # Strategy selection and instantiation
│   ├── risk_manager.py          # Position sizing and risk controls
│   ├── trading_engine.py        # Main trading execution engine
│   └── logger_setup.py          # Logging configuration
├── config/
│   └── trading_config.py        # Configuration settings
├── logs/                        # Generated log files
├── main.py                      # Application entry point
├── compare_strategies.py        # Strategy comparison tool
└── README.md
```

## Strategy Types

### Conservative Strategy
- **Philosophy**: Let big winners run, relaxed exit conditions
- **Trailing Stops**: 18-40% (wider range for bigger moves)
- **Emergency Exits**: 28-day maximum hold time
- **Best For**: Trending markets, patient traders

### Enhanced Strategy  
- **Philosophy**: Tighter risk control, early loss protection
- **Trailing Stops**: 12-40% (tighter range for quicker exits)
- **Emergency Exits**: 7-14 day maximum hold time
- **Entry Conditions**: More selective (2% above trend line)
- **Best For**: Volatile markets, risk-conscious traders

## Quick Start

### 1. Setup Environment

```bash
# Clone and navigate to project
cd /path/to/trading

# Install dependencies
pip install alpaca-trade-api pandas numpy python-dotenv

# Setup environment variables
echo "ALPACA_API_KEY=your_api_key" > .env
echo "ALPACA_SECRET_KEY=your_secret_key" >> .env
echo "ALPACA_BASE_URL=https://paper-api.alpaca.markets" >> .env
echo "STRATEGY_TYPE=enhanced" >> .env
```

### 2. Run Backtesting

```bash
# Test conservative strategy
python3 main.py --mode backtest --strategy conservative

# Test enhanced strategy  
python3 main.py --mode backtest --strategy enhanced

# Compare both strategies
python3 compare_strategies.py
```

### 3. Paper Trading

```bash
# Start paper trading with enhanced strategy
python3 main.py --mode paper --strategy enhanced

# Start paper trading with conservative strategy
python3 main.py --mode paper --strategy conservative
```

## Configuration

### Environment Variables
- `ALPACA_API_KEY`: Your Alpaca API key
- `ALPACA_SECRET_KEY`: Your Alpaca secret key  
- `ALPACA_BASE_URL`: API endpoint (paper or live)
- `STRATEGY_TYPE`: Default strategy ("conservative" or "enhanced")

### Strategy Selection
You can select strategies in multiple ways:

1. **Command Line**: `--strategy enhanced`
2. **Environment Variable**: `STRATEGY_TYPE=conservative`
3. **Config File**: Modify `trading_config.py`

Priority: Command line > Environment variable > Config file

## Usage Examples

```bash
# Backtest enhanced strategy for 90 days
python3 main.py --mode backtest --strategy enhanced --days 90

# Paper trade with conservative strategy
python3 main.py --mode paper --strategy conservative

# Compare strategies side-by-side
python3 compare_strategies.py

# Check strategy configuration
python3 -c "from config.trading_config import TradingConfig; print(TradingConfig())"
```

## Strategy Comparison

The `compare_strategies.py` script provides detailed performance comparison:

- **Returns**: Total return vs market benchmark
- **Risk Metrics**: Max drawdown, Sharpe ratio
- **Trade Analytics**: Win rate, profit factor, average wins/losses
- **Timing**: Time in market, trade frequency

## Risk Management

Both strategies include comprehensive risk controls:

- **Position Sizing**: Configurable risk per trade
- **Trailing Stops**: Dynamic stop-loss adjustment
- **Emergency Exits**: Maximum hold time limits
- **Drawdown Limits**: Account protection thresholds
- **Market Hours**: Trading only during market hours

## Logging

The system generates detailed logs in the `logs/` directory:

- `trading.log`: General trading activity
- `trades.log`: Trade execution details
- `risk.log`: Risk management events
- `performance.log`: Performance metrics

## Safety Features

- **Paper Trading First**: Always test with paper money
- **Fail-Safe Defaults**: Conservative settings by default
- **Error Handling**: Graceful error recovery
- **Position Limits**: Maximum position size controls
- **Market Data Validation**: Data quality checks

## Development

To add a new strategy:

1. Create new strategy file in `src/strategy_your_name.py`
2. Inherit from base strategy pattern (see existing strategies)
3. Register in `src/strategy_factory.py`
4. Update configuration options
5. Test with backtesting before live usage

## Support

For issues or questions:
1. Check logs in `logs/` directory
2. Verify API keys and permissions
3. Test with paper trading first
4. Review strategy configuration

## Disclaimer

This software is for educational and testing purposes. Always test thoroughly with paper trading before using real money. Past performance does not guarantee future results.