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Article: Score tests for hyperbolic GARCH models

TitleScore tests for hyperbolic GARCH models
Authors
KeywordsHyperbolic decay
Long-range dependence
Issue Date2011
PublisherAmerican Statistical Association. The Journal's web site is located at http://www.amstat.org/publications/jbes/index.cfm?fuseaction=main
Citation
Journal Of Business And Economic Statistics, 2011, v. 29 n. 4, p. 579-586 How to Cite?
AbstractDavidson (2004) recently proposed the hyperbolic GARCH model to capture the phenomenon of longrange dependence in volatility, with the extent of such dependence measured by the geometric or hyperbolic decay of the coefficients in an ARCH(∞) model. In this article, we reinterpret the hyperbolic GARCH model by building a link with the common GARCH model, and construct a simplified score test to check the presence of the hyperbolic decay. We derive the asymptotic of the test statistic under the null hypothesis and the local alternatives.We conductMonte Carlo simulation experiments to study the performance of this test, and report an illustration on two log return sequences. This article has supplementary material online. © 2011 American Statistical Association.
Persistent Identifierhttp://hdl.handle.net/10722/143389
ISSN
2015 Impact Factor: 1.648
2015 SCImago Journal Rankings: 2.566
ISI Accession Number ID
Funding AgencyGrant Number
Hong Kong Research Grants CouncilHKU 702908P
Funding Information:

The authors thank Professor J. Wright, an Associate Editor, and two anonymous referees for valuable comments that led to the substantial improvement of this manuscript. This work was partially supported by Hong Kong Research Grants Council Grant HKU 702908P.

References
Grants

 

DC FieldValueLanguage
dc.contributor.authorLi, Men_HK
dc.contributor.authorLi, Gen_HK
dc.contributor.authorLi, WKen_HK
dc.date.accessioned2011-11-24T10:04:56Z-
dc.date.available2011-11-24T10:04:56Z-
dc.date.issued2011en_HK
dc.identifier.citationJournal Of Business And Economic Statistics, 2011, v. 29 n. 4, p. 579-586en_HK
dc.identifier.issn0735-0015en_HK
dc.identifier.urihttp://hdl.handle.net/10722/143389-
dc.description.abstractDavidson (2004) recently proposed the hyperbolic GARCH model to capture the phenomenon of longrange dependence in volatility, with the extent of such dependence measured by the geometric or hyperbolic decay of the coefficients in an ARCH(∞) model. In this article, we reinterpret the hyperbolic GARCH model by building a link with the common GARCH model, and construct a simplified score test to check the presence of the hyperbolic decay. We derive the asymptotic of the test statistic under the null hypothesis and the local alternatives.We conductMonte Carlo simulation experiments to study the performance of this test, and report an illustration on two log return sequences. This article has supplementary material online. © 2011 American Statistical Association.en_HK
dc.languageengen_US
dc.publisherAmerican Statistical Association. The Journal's web site is located at http://www.amstat.org/publications/jbes/index.cfm?fuseaction=mainen_HK
dc.relation.ispartofJournal of Business and Economic Statisticsen_HK
dc.subjectHyperbolic decayen_HK
dc.subjectLong-range dependenceen_HK
dc.titleScore tests for hyperbolic GARCH modelsen_HK
dc.typeArticleen_HK
dc.identifier.emailLi, G: gdli@hku.hken_HK
dc.identifier.emailLi, WK: hrntlwk@hku.hken_HK
dc.identifier.authorityLi, G=rp00738en_HK
dc.identifier.authorityLi, WK=rp00741en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1198/jbes.2011.10024en_HK
dc.identifier.scopuseid_2-s2.0-80053585734en_HK
dc.identifier.hkuros197783en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-80053585734&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume29en_HK
dc.identifier.issue4en_HK
dc.identifier.spage579en_HK
dc.identifier.epage586en_HK
dc.identifier.eissn1537-2707-
dc.identifier.isiWOS:000295584300011-
dc.publisher.placeUnited Statesen_HK
dc.relation.projectStatistical Inference for the Hyberbolic Generalized Conditional Autoregressive Heteroscedastic (HYGARCH) Model and Extensions-
dc.identifier.scopusauthoridLi, M=52563850200en_HK
dc.identifier.scopusauthoridLi, G=52563850500en_HK
dc.identifier.scopusauthoridLi, WK=14015971200en_HK

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