This project is a modular Python engine for detecting option mispricing using the Black-Scholes model, visualizing volatility surfaces, and ranking arbitrage opportunities. It is designed for quantitative finance analysis and visualization.
- Data input via CSV or yfinance
- Black-Scholes pricing (manual implementation, no external pricing libraries)
- Greeks calculation (Delta, Gamma, Vega, Theta)
- Mispricing detection and statistical ranking
- Volatility smile and 3D volatility surface visualization
- Professional, object-oriented, modular structure
- data_loader.py: Data input, cleaning, and preprocessing
- pricing.py: Black-Scholes pricing and mispricing logic
- greeks.py: Greeks calculation (Delta, Gamma, Vega, Theta)
- analysis.py: Quantitative analysis, visualization, and ranking
- main.py: Orchestration, CLI, and end-to-end execution
- requirements.txt: Python dependencies
- sample.csv: Example data file for testing
date,strike,expiry,option_type,market_price,underlying_price,implied_vol
- pandas
- numpy
- scipy
- matplotlib
- plotly
- yfinance
MIT