Using unobservable conditional variance as measure, latentvariable approaches, such as GARCH and stochasticvolatility … observable or realized volatility series from intraday transaction data, the use of standard time series models, such as ARFIMA …

Both unconditional mixed-normal distributions and GARCH models with fat-tailed conditional distributions have been … employed for modeling financial return data. We consider a mixed-normal distribution coupled with a GARCH-type structure which …

, such as GARCH models, are investigated, to determine if they are more appropriate for predicting future return volatility …

) forecasting ability of the normal-GARCH model. Compared to the use of more sophisticated GARCH models, the new method is fast …

-tailed conditionally heteroskedastic time series. In an application to the 1992-93 European Exchange Rate Mechanism crises, that both the …

-making approach, communication strategy and operational framework of a Central bank. Through a GARCH specification we show that the …

-tailed conditionally heteroskedastic time series. In an application to the 1992-93 European Exchange Rate Mechanism crises, that both the …

Using unobservable conditional variance as measure, latent–variable approaches, such as GARCH and stochastic … “observable” or realized volatility series from intraday transaction data, the use of standard time series models, such as ARFIMA … residuals of the commonly used time–series models for realized volatility exhibit non–Gaussianity and volatility clustering. We …