Please use this identifier to cite or link to this item: http://ir.library.ui.edu.ng/handle/123456789/7655
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dc.contributor.authorAdepoju, A. A.-
dc.contributor.authorYaya, O. S.-
dc.contributor.authorOjo, O. O.-
dc.date.accessioned2022-09-05T08:08:01Z-
dc.date.available2022-09-05T08:08:01Z-
dc.date.issued2013-
dc.identifier.issn2222-2855-
dc.identifier.otherui_art_adepoju_estimation_2013-
dc.identifier.otherJournal of Economics and Sustainable Development 4(3), 2013. Pp. 88 - 97-
dc.identifier.urihttp://ir.library.ui.edu.ng/handle/123456789/7655-
dc.description.abstractFinancial series often displays evidence of leptokurticity and in that case, the empirical distribution often fails normality. GARCH models were initially based on normality assumption but estimated model based on this assumption cannot capture all the degree of leptokurticity in the return series. In this paper, we applied variants of GARCH models under non-normal innovations-t-distribution and Generalized Error Distribution (GED) on selected Nigeria exchange rates. The Berndt, Hall, Hall, Hausman (BHHH) numerical derivatives applied in the estimation of models converged faster and the time varied significantly across models. Asymmetric GARCH model with t-distribution (GARCH-t) was selected in most of the cases whereas for Nigeria-US Dollar exchange rate, GARCH-GED was specified. Both distributions showed evidence of leptokurticity in Naira exchange rate return series. The result is of practical importance to practitionersen_US
dc.language.isoen_USen_US
dc.subjectGARCHen_US
dc.subjectExchange rateen_US
dc.subjectModel specificationen_US
dc.subjectNon-Gaussian distributionen_US
dc.titleEstimation of garch models for Nigerian exchange rates under non-gaussian innovationsen_US
dc.typeArticleen_US
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