Option Pricing with State-dependent Pricing Kernel: A Realized GARCH Approach

Chen Tong is a PhD student in the National School of Development, Peking University. His research interests include financial econometrics and financial engineering. He has published research papers in several academic journals including Journal of Futures Markets (twice), International Review of Finance, Economics Letters, Applied Economics, Journal of Financial Research (in Chinese) and China Economic Quarterly (in Chinese). He will join Xiamen University as an assistant professor in Fall 2021. 

We introduce a new volatility model within the Realized GARCH framework, that permits structural changes in the volatility process. When combined with a novel pricing kernel, our model allows for a state-dependent variance risk premium. We model the time variation in key parameters, using a hidden Markov switching process, and derive the corresponding pricing formula for European options using an analytical approximation method. The proposed framework is easy to estimate and implement, as inferences about regimes are deduced from realized volatility measures. The estimation results indicates that investor shows two distinct attitudes towards volatility-specific risk within different market states. We conduct an extensive empirical application on S&P 500 index options from 1990 to 2019 and find that the newly proposed model outperforms competing methods. Both in-sample and out-of-sample.