The literature on dynamic option valuation typically does not explicitly specify a pricing kernel. Instead it characterizes the kernel indirectly by specifying prices of risk, or defines it implicitly as the ratio of the risk-neutral and physical probabilities. We propose explicit pricing...

The cross-section of options holds great promise for identifying return distributions and risk premia, but estimating dynamic option valuation models with latent state variables is challenging when using large option panels. We propose a particle MCMC framework with a novel filtering approach...

We present a new discrete-time GARCH jump framework that allows for rich dynamics in higher moments by combining heteroskedastic processes with fat-tailed innovations in returns and volatility. We provide a tractable risk neutralization framework allowing for option valuation with separate...