Option Pricing with State-dependent Pricing Kernel

TL;DR

This paper proposes a new option pricing model combining Markov switching and Realized GARCH, capturing time-varying risk premiums and improving pricing accuracy for S&P 500 options.

Contribution

It introduces a novel state-dependent pricing kernel and analytical approximation for European options, enhancing modeling of volatility risk premiums.

Findings

Outperforms competing models in pricing accuracy

Reduces option pricing errors by over 15%

Reveals time-varying investor risk aversion

Abstract

We introduce a new volatility model for option pricing that combines Markov switching with the Realized GARCH framework. This leads to a novel pricing kernel with a state-dependent variance risk premium and a pricing formula for European options, which is derived with an analytical approximation method. We apply the Markov switching Realized GARCH model to S&P 500 index options from 1990 to 2019 and find that investors' aversion to volatility-specific risk is time-varying. The proposed framework outperforms competing models and reduces (in-sample and out-of-sample) option pricing errors by 15% or more.