Estimation of a Stochastic-Volatility Jump-Diffusion Model

Abstract

This paper makes two contributions: (1) it presents estimates of a continuous-time stochastic-volatility jump-diffusion process (SVJD) using a simulation-based estimator, and (2) it shows that misspecified models that allow for jumps, but not stochastic volatility, can give very bad estimates of the true process. Simulation-based estimation is a very flexible and powerful technique. It is ideally suited to high frequency financial data. It can estimate models with intractable likelihood functions, and since the simulations can be performed in (essentially) continuous-time the estimates are consistent estimates of the parameters of the continuous-time process.