- Predicted the implied volatility of the S&P 500 index options based on the Hyperbola model using Python trained on engineered features, such as option moneyness and bid-ask spreads
- Built a calibration process of implied volatility curve and used a quantitative loss function to evaluate the calibration
- Conducted sensitivity analysis on different model parameters, including curve convexity and skewness, to test and validate the robustness of the curve calibration model