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 …

, there have been no studies which have used the GARCH methodology to study export volatility. This paper fills the void. It …

independence over time should be taken with caution due to the presence of GARCH effects. In addition, extreme co-movements are …

employ daily values of one from the main indexes of the Bucharest Stock Exchange. We use a GARCH model to reveal the monthly …

heteroscedasticity (GARCH), robust regression quantile of least absolute deviation (LAD), and Hoerl's Ordinary ridge regression (ORR …

2013. In this analysis we employ daily values of five main indexes of Bucharest Stock Exchange. We use GARCH models to …

sub-samples corresponding to different stages of the Romanian financial markets evolution. The GARCH models employed in …

, but the data generating process is shown to be non-linear. A non-linear GARCH model is then applied, achieving a good …

clustering and leptokurtosis are well-documented characteristics of such time series. An ARMA (1, 1)-GARCH (1, 1) ap- proach …, the ARMA-GARCH process is run assuming alternatively that the standardized residuals are distributed with Pearson Type IV …, Johnson SU, Manly’s exponential transformation, normal and t-distributions. In the second ap- proach, the ARMA-GARCH process …