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Article: Detecting and diagnostic checking multivariate conditional heteroscedastic time series models

TitleDetecting and diagnostic checking multivariate conditional heteroscedastic time series models
Authors
KeywordsARCH models
Cross-correlation tests
Score test
Squared residuals
Issue Date2002
PublisherSpringer Verlag.
Citation
Annals Of The Institute Of Statistical Mathematics, 2002, v. 54 n. 1, p. 45-59 How to Cite?
AbstractTwo tests for multivariate conditional heteroscedastic models are proposed. One is based on the cross-correlations of standardized squared residuals and the other is a score (Lagrange multiplier) test. The cross-correlations test can be used to detect the presence of multivariate conditional heteroscedasticity whereas the other test can be used for diagnostic checking. Simulation studies on the size and power of the test statistics are reported. The application of the tests is illustrated by an example using the S & P 500 and Sydney All Ordinary Indexes.
Persistent Identifierhttp://hdl.handle.net/10722/82906
ISSN
2015 Impact Factor: 0.768
2015 SCImago Journal Rankings: 0.931
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorWong, Hen_HK
dc.contributor.authorLi, WKen_HK
dc.date.accessioned2010-09-06T08:34:44Z-
dc.date.available2010-09-06T08:34:44Z-
dc.date.issued2002en_HK
dc.identifier.citationAnnals Of The Institute Of Statistical Mathematics, 2002, v. 54 n. 1, p. 45-59en_HK
dc.identifier.issn0020-3157en_HK
dc.identifier.urihttp://hdl.handle.net/10722/82906-
dc.description.abstractTwo tests for multivariate conditional heteroscedastic models are proposed. One is based on the cross-correlations of standardized squared residuals and the other is a score (Lagrange multiplier) test. The cross-correlations test can be used to detect the presence of multivariate conditional heteroscedasticity whereas the other test can be used for diagnostic checking. Simulation studies on the size and power of the test statistics are reported. The application of the tests is illustrated by an example using the S & P 500 and Sydney All Ordinary Indexes.en_HK
dc.languageengen_HK
dc.publisherSpringer Verlag.en_HK
dc.relation.ispartofAnnals of the Institute of Statistical Mathematicsen_HK
dc.subjectARCH modelsen_HK
dc.subjectCross-correlation testsen_HK
dc.subjectScore testen_HK
dc.subjectSquared residualsen_HK
dc.titleDetecting and diagnostic checking multivariate conditional heteroscedastic time series modelsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0020-3157&volume=54&issue=1&spage=45&epage=59&date=2002&atitle=Detecting+and+diagnostic+checking+multivariate+conditional+heteroscedastic+time+series+modelsen_HK
dc.identifier.emailLi, WK: hrntlwk@hku.hken_HK
dc.identifier.authorityLi, WK=rp00741en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1023/A:1016161620735en_HK
dc.identifier.scopuseid_2-s2.0-6444244545en_HK
dc.identifier.hkuros65671en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-6444244545&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume54en_HK
dc.identifier.issue1en_HK
dc.identifier.spage45en_HK
dc.identifier.epage59en_HK
dc.identifier.isiWOS:000174797700004-
dc.publisher.placeGermanyen_HK
dc.identifier.scopusauthoridWong, H=7402864953en_HK
dc.identifier.scopusauthoridLi, WK=14015971200en_HK

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