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dc.contributor.authorStorti, Giuseppe
dc.date.accessioned2019-11-08T14:15:00Z
dc.date.available2019-11-08T14:15:00Z
dc.date.issued2006
dc.identifier.citationSorti, G. (2006). “Modelling asymmetric volatility dynamics by multivariate bl-garch models”. DISES Working Paper 3.177, Università degli Studi di Salerno, Dipartimento di Scienze Economiche e Statistiche.it_IT
dc.identifier.issn1971-3029it_IT
dc.identifier.urihttp://elea.unisa.it:8080/xmlui/handle/10556/3859
dc.identifier.urihttp://dx.doi.org/10.14273/unisa-2081
dc.description.abstractThe class of Multivariate BiLinear GARCH (MBL-GARCH) models is proposed and its statistical properties are investigated. The model can be regarded as a generalization to a multivariate setting of the univariate BLGARCH model proposed by Storti and Vitale (2003a; 2003b). It is shown how MBL-GARCH models allow to account for asymmetric effects in both conditional variances and correlations. An EM algorithm for the maximum likelihood estimation of the model parameters is provided. Furthermore, in order to test for the appropriateness of the conditional variance and covariance specifications, a set of robust conditional moments test statistics are defined. Finally, the effectiveness of MBL-GARCH models in a risk management setting is assessed by means of an application to the estimation of the optimal hedge ratio in futures hedging.it_IT
dc.format.extent54 p.it_IT
dc.language.isoenit_IT
dc.relation.ispartofWorking Papers ; 3.177it_IT
dc.sourceUniSa. Sistema Bibliotecario di Ateneoit_IT
dc.subjectMultivariate GARCHit_IT
dc.subjectAsymmetryit_IT
dc.subjectConditional correlationit_IT
dc.subjectEM algorithmit_IT
dc.subjectRobust conditional moment testsit_IT
dc.subjectFutures hedgingit_IT
dc.titleModelling asymmetric volatility dynamics by multivariate bl-garch modelsit_IT
dc.typeWorking Paperit_IT
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