On the origins of high persistence in GARCH-models

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DC Field	Value	Language
dc.contributor.author	Azamo, Baudouin Tameze	de
dc.contributor.author	Christou, Konstantinos	de
dc.contributor.author	Krämer, Walter	de
dc.date.accessioned	2009-10-29T10:14:30Z	-
dc.date.available	2009-10-29T10:14:30Z	-
dc.date.issued	2009-06	de
dc.identifier.uri	http://hdl.handle.net/2003/26486	-
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-12666	-
dc.description.abstract	The estimated persistence in various types of GARCH-models is known to be too large when the parameters of the model undergo structural changes somewhere in the sample. The present paper adds further insights into this phenomenon for the Baillie and Chung (2001) minimum distance estimates of the model parameters. While previous research has focused on the effects of changes in the GARCH-parameters, we investigate here the consequences of a changing mean.	en
dc.language.iso	en	de
dc.relation.ispartofseries	Discussion Paper / SFB 823; 12/2009	de
dc.subject	GARCH	en
dc.subject	long memory	en
dc.subject	minimum distance estimates	en
dc.subject	structural change	en
dc.subject.ddc	310	de
dc.subject.ddc	330	de
dc.subject.ddc	620	de
dc.title	On the origins of high persistence in GARCH-models	en
dc.type	Text	de
dc.type.publicationtype	report	de
dcterms.accessRights	open access	-
Appears in Collections:	Sonderforschungsbereich (SFB) 823

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