The standard continuous-state GARCH model is misspecified if applied to returns calculated from discrete price series … proposed model differ significantly from the one we would have if all variables were observed, i.e. an underlying latent GARCH … in no case does the proposed model differ significantly from an unobservable continuous-state GARCH model. …

Using unobservable conditional variance as measure, latentvariable approaches, such as GARCH and stochasticvolatility …

use a collection of ARCH models (GARCH, EGARCH and TARCH) based on three distributional assumptions (Normal, Student-T and … Skewed Student-T), while we combine the Extreme Value Theory with a volatility updating technique (via GARCH type …

heteroscedasticity (GARCH)-type models to forecast oil price volatility over the time periods from January 02, 1875 to December 31, 1895 … outperformed by other models, with long memory GARCH-type models coming out second best. …

We develop univariate regime-switching GARCH (RS-GARCH) models wherein the conditional variance switches in time from … one GARCH process to another. The switching is governed by a time-varying probability, specified as a function of past …

A Bayesian estimation of a regime-switching threshold asymmetric GARCH model is proposed. The specification is based on …

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

case of the GARCH(1,1)-Student-t model the average VaR may be adjusted for parameter uncertainty to arrive at levels which …

We develop a Markov-switching GARCH model (MS-GARCH) wherein the conditional mean and variance switch in time from one … GARCH process to another. The switching is governed by a hidden Markov chain. We provide sufficient conditions for geometric …