Automated Trading Bot

Quick Start

1. Install dependencies:

pip install -r requirements.txt

2. Run the backtest:

python backtest.py

What's Included

• Backtester: Framework to test strategies on historical data
• SMA Crossover Strategy: Simple moving average crossover (buy when 10-day MA crosses above 30-day MA)

Next Steps

1. Test Different Strategies

Modify sma_crossover_strategy() or create new strategy functions:

• RSI (Relative Strength Index)
• MACD (Moving Average Convergence Divergence)
• Bollinger Bands
• ML-based predictions

2. Add ML/AI Model

def ml_strategy(data):
    # Load your trained model
    # features = extract_features(data)
    # prediction = model.predict(features)
    # return 'BUY' if prediction > threshold else 'SELL'
    pass

3. Live Trading (Paper Trading First!)

Use broker APIs:

• Alpaca (free paper trading): pip install alpaca-trade-api
• Interactive Brokers: pip install ib_insync
• TD Ameritrade: pip install tda-api

4. Risk Management

Add to your strategy:

• Stop-loss orders
• Position sizing (don't use all capital at once)
• Maximum drawdown limits
• Diversification across multiple stocks

Warning

⚠️ Never trade real money without extensive testing

• Backtest on multiple years of data
• Test in paper trading for weeks/months
• Understand that past performance ≠ future results