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 …

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

exhibiting leptokurtosis, asymmetry and conditional heteroskedasticity. It is based on a GARCH-type process driven by noncentral …

The class of mixed normal conditional heteroskedastic (MixN-GARCH) models, which couples a mixed normal distributional … structure with GARCH-type dynamics, has been shown to offer a plausible decomposition of the contributions to volatility, as … well as excellent out-of-sample forecasting performance, for financial asset returns. In this paper, we generalize the MixN-GARCH …

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 …

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

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