Open Access Open Access  Restricted Access Subscription or Fee Access

Investigating the Specification of the Distributional Assumption of the Innovations of Generalised Autoregressive Score Model with its Variants

O. T. Babatunde, O. S. Yaya, A. V. Oladugba

Abstract



This paper investigates the specification of the distributional assumption of the innovations of Generalised Autoregressive Score model with its variants through Monte Carlo simulation experiment with extension to international crude oil prices using three levels of volatility persistence by varying the parameters of the models. The estimates of Akaike Information Criterion and Excess Kurtosis were used to access fitness performance. The results obtained showed that when the distributional assumption of the innovations of Generalised Autoregressive Score model with its variants is either Student-t or Skewed Student-t, specifying it as Skewed Student-t distribution fits better than the other distributions considered.

Keywords


Generalised Autoregressive Score, Innovation, Persistence, Skewed-Student-t distribution, Specification.

Full Text:

PDF


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.