AI-Powered Trading Bot

A comprehensive trading system that combines reinforcement learning, risk management, and real-time execution.

Core Components

1. Reinforcement Learning

• PPO-based trading agent
• Custom trading environments
• Multi-agent support
• Hyperparameter optimization with Ray Tune
• MLflow experiment tracking

2. Risk Management

• Position size control
• Portfolio VaR monitoring
• Multi-asset correlation tracking
• Dynamic risk adjustment
• Advanced backtesting

3. Live Trading

• Real-time execution via CCXT
• Paper trading support
• Order types: limit, stop-limit, trailing-stop
• Rate limiting and error handling
• Network resilience

4. Data Pipeline

• OHLCV data processing
• Technical indicators (TA-Lib)
• Market scenario simulation
• Multi-asset data handling
• Real-time data streaming

Installation

pip install -r requirements.txt

Quick Start

1. Training an Agent

from training.agents import PPOAgent
from training.environments import TradingEnv

# Initialize and train agent
agent = PPOAgent(config)
env = TradingEnv(data)
agent.train(env)

2. Backtesting

from training.utils.risk_backtest import RiskAwareBacktester
from training.utils.risk_config import RiskConfig

# Run backtest
backtester = RiskAwareBacktester(data, risk_config)
results = backtester.run(agent)

3. Live Trading

from trading.live import LiveTradingEnvironment

# Start live trading
live_env = LiveTradingEnvironment(
    exchange_config=config,
    risk_config=risk_config
)
live_env.run(agent)

Project Structure

trading_bot/
├── training/
│   ├── agents/           # RL agents (PPO, etc.)
│   ├── environments/     # Trading environments
│   └── utils/           
│       ├── risk_backtest.py
│       └── hyperopt.py   # Ray Tune integration
├── trading/
│   ├── live/            # Live trading
│   ├── paper/           # Paper trading
│   └── data/            # Data handling
├── risk/
│   └── risk_manager.py  # Risk management
├── tests/
│   ├── test_agents/
│   ├── test_trading/
│   └── test_risk/
└── scripts/
    ├── train.py
    ├── backtest.py
    └── live_trade.py

Development

Testing

python -m pytest tests/

Code Quality

• Follow PEP 8
• Add docstrings
• Update CHANGELOG.md

Documentation

• See class/method docstrings
• Check CHANGELOG.md
• Review test files

Contributing

1. Fork repository
2. Create feature branch
3. Add tests
4. Update documentation
5. Submit pull request

License

MIT License