This paper studies a class of tractable jump-diffusion models,including stochastic volatility models with self-exciting jumpsfor stock returns and variance processes. We employ the Markovchain Monte Carlo (MCMC) method to implement model estimation, andinvestigate the performance of all models...

We show that there are two distinct ways to make volatility stochastic that are differentiated by their consequences for skewness. Most models in the literature have adopted the relatively tractable methodology of using stochastic time changes to engineer stochastic volatility. Unfortunately,...