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 …

-known GARCH models for density prediction of daily S&P 500 and Nikkei 225 index returns, a comparison is provided between …

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

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 …

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

Using GARCH models for density prediction of stock index returns, a comparison is provided between frequentist and …

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 …