March 18, 2008
Existing empirical investigations of jump dynamics in returns and volatility are fairly complicated due to the presence of latent factors. We present a new discrete-time frame-work that combines heteroskedastic processes with rich specifications of jumps in returns and volatility. We provide a tractable risk neutralization framework for this class of mod-els allowing for option valuation with separate modeling of risk premia for the jump and normal innovations. Our models can be estimated with ease on returns using standard maximum likelihood techniques, and joint estimation on returns and a large sample of options is also feasible.