methods. The effects ofseveral modelcharacteristics (unit roots, GARCH, stochastic volatility, heavy taileddisturbance …

Volatility (SV) and Generalised Autoregressive Conditional Heteroskedasticity (GARCH) models which are both extended to include … outperforms the GARCH model. …

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 …

quarterly basis - for commonly used GARCH models in a large-scale study, using more than twelve years (2000-2012) of daily … following conclusions. First, updating the parameter estimates of the GARCH equation on a daily frequency improves only … overlap, reflecting that the performance is not significantly different. Second, the asymmetric GARCH model with non …

. A generalized autoregressive conditional heteroscedasticity (GARCH) model is applied to the data of four large US banks … over the period ranging from January 01, 2006, to December 31, 2009. More specifically, a multivariate GARCH approach fits …

increased interest in recent research. Using a dummy-augmented GARCH model, we investigate whether the occurrence of this …

Dynamic Factor GARCH (DF-GARCH), is used here to exploit the relations between inflation and the other macroeconomic variables … for inflation forecasting purposes. The DF-GARCH is a dynamic factor model with the additional assumption of conditionally … heteroskedastic dynamic factors. When comparing the Dynamic Factor GARCH with univariate models and with the traditional dynamic …

GARCH model. The GDFM, applied to a large number of series, captures the multivariate information and disentangles the … a GARCH.We compare GDFM+GARCH and standard GARCH performance on two samples up to 171 series, providing one …-step-ahead volatility predictions of returns. The GDFM+GARCH model outperforms the standard GARCH in most cases. These results are robust …