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. …

Conditional Heteroskedasticity (GARCH), the Exponential GARCH and the Autoregressive Stochastic Volatility model. The focus is on …

. Bootstrap and asymptotic values of these tests are estimated. Alternative models from the GARCH family (GARCH, EGARCH and TGARCH …

fractionally-integrated GARCH for the conditional variance. The interaction between the funds is modelled as the Dynamic …

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. …

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. …

GARCH models which capture volatility clustering and, therefore, are appropriate to analyse financial market data. Models …

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 …