This paper proposes an up-to-date review of estimation strategies available for the Bayesian inference of GARCH … empirical application to S&P index log-returns. Several non-nested GARCH-type models are estimated and combined to predict the …

parsimonious and effective GARCH(1,1) model with Student-t innovations. The estimation procedure is fully automatic and thus avoids …

over a small time frame (e.g., a crisis period). We apply our method to test GARCH model specifications for a large panel …

parsimonious and effective GARCH(1,1) model with Student-t innovations. The estimation procedure is fully automatic and thus avoids …

This paper proposes an up-to-date review of estimation strategies available for the Bayesian inference of GARCH … empirical application to S&P index log-returns. Several non-nested GARCH-type models are estimated and combined to predict the …

over a small time frame (e.g., a crisis period). We apply our method to test GARCH model specifications for a large panel …

basis–for commonly used GARCH models in a large-scale study, using more than twelve years (2000–2012) of daily returns for … difference in performance between updating the parameter estimates of the GARCH equation at a daily or weekly frequency, whereas …

estimation strategies available for the Bayesian inference of GARCH-type models. The emphasis is put on a novel efficient …-nested GARCH-type models are estimated and combined to predict the distribution of next-day ahead log-returns. …