📈 Quant Backtester

A lightweight, modular backtesting engine for evaluating trading strategies on historical stock data.
Perfect for learning quantitative finance, comparing strategies, and building your own framework.

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🚀 Features

• CLI interface with interactive menu
• Fetches historical stock data via Yahoo Finance
• Modular strategy architecture (easy to add your own)
• Computes performance metrics:
  • CAGR
  • Sharpe Ratio
  • Max Drawdown
• Grid Search for:
  • Moving Average Crossover
  • RSI Strategy
• Saves results in CSV and visualizes equity curves

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📸 Demo

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⚙️ How to Use

git clone https://github.com/tibonigabriele/quant-backtester-python.git
cd quant-backtester-python
pip install -r requirements.txt
python main.py

Make sure you're connected to the internet: the script fetches data using yfinance.

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🧠 CLI Menu

What would you like to do?
1. Run base strategies (Buy & Hold, MA, RSI)
2. Launch MA Crossover grid search
3. Launch RSI grid search
4. Exit

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💡 Included Strategies

• Buy & Hold – benchmark strategy
• Moving Average Crossover – customizable short/long windows
• RSI Strategy – buy when RSI < 30, sell when RSI > 70

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📊 Sample Grid Search Output

📉 MA Crossover Results (results/ma_crossover_results.csv)

Strategy	CAGR	Sharpe Ratio	Max Drawdown
MA 10-200	0.1122	0.95	0.1377
MA 10-100	0.1018	0.90	0.1966

🔄 RSI Strategy Results (results/rsi_grid_search_results.csv)

Strategy	CAGR	Sharpe Ratio	Max Drawdown
RSI 10-20-80	0.0954	0.87	0.1456
RSI 14-30-70	0.0889	0.81	0.1823

Both outputs are automatically ranked using a weighted performance score.

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📂 Project Structure

quant-backtester-python/
├── main.py                     # Entry point with CLI menu
├── requirements.txt            # Python dependencies
├── LICENSE                     # MIT License
├── README.md                   # This file
├── results/                    # CSV files from grid search
├── plots/                      # Saved equity curve images
├── src/
│   ├── data_loader.py
│   ├── performance_metrics.py
│   ├── plotter.py
│   ├── print_metrics.py
│   └── strategies/
│       ├── buy_hold_strategy.py
│       ├── ma_crossover_strategy.py
│       └── rsi_strategy.py
└── analysis/
    └── grid_search.py      # tuning logic

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📬 Contact

Project by Gabriele Tiboni
Feel free to reach out for feedback or collaboration!