Adaptive Covered-Call Management – A Data-Driven Framework for Selection, Closing, and Rolling Decisions

This project assesses the feasibility of a transparent, data-driven framework for selecting, closing, and rolling covered calls in equity-income portfolios. It tests whether economically meaningful decision points can be reconstructed or simulated using option, equity, Greek, and volatility data.

Key data

Description

This project aims to develop a transparent, rules-based framework for determining when it is optimal to roll, adjust, close, or maintain a covered-call position across different market and volatility regimes. A central feasibility challenge is that the optimality of an observed decision cannot be assessed directly from its realised outcome. In particular, the counterfactual performance of alternative decisions—such as rolling rather than holding, or closing rather than allowing the option to expire—is not directly observable. This project reconstruct alternative decision paths and evaluate their relative performance under comparable market conditions. It also develops and calibrate a model that links the relative performance of these decisions to key option characteristics, including strike price, time to maturity, delta, theta, vega, and gamma, as well as prevailing market and volatility conditions.