This paper is concerned with simulation based inference in generalized models of stochastic volatility defined by heavy-tailed student-t distributions (with unknown degrees of freedom) and covariate effects in the observation and volatility equations and a jump component in the observation...

GARCH models are commonly used as latent processes in econometrics, financial economics and macroeconomics. Yet no exact likelihood analysis of these models has been provided so far. In this paper we outline the issues and suggest a Markov chain Monte Carlo algorithm which allows the calculation...

In the past fifteen years computational statistics has been enriched by a powerful, somewhat abstract method of generating variates from a target probability distribution that is based on Markov chains whose stationary distribution is the probability distribution of interest. This class of...