ABSTRACT
Author: Heng Li
Advisor: Dragos Bozdog
Date: December 11th, 2024
Department: Financial Engineering
Degree: Master of Science- Financial Engineering
”This thesis investigates the development, implementation, and evaluation of ad vanced option pricing models, focusing on a Stochastic Liquidity model to address the limitations of the traditional Black-Scholes-Merton framework. The Liquidity model uses a mean-reverting stochastic process to capture the impact of liquidity risk on option pricing. We use market options data for the 30 component stocks of Dow Jones Industrial Average (DJIA) index. We also calibrate risk-free rates using a traditional Nelson-Siegel framework. The model is calibrated daily and its perfor mance compared with the Black Scholes benchmark as well as a Heston stochastic volatility model and Merton’s jump diffusion mode. Empirical analysis shows that the Stochastic Liquidity model outperforms the Heston and Jump Diffusion models on the test data considered. These findings underscore the critical role of liquidity dynamics in enhancing option pricing precision. This can serve to better the current risk management processes in current financial markets.”