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Article: On a multivariate conditional heteroscedastic model

TitleOn a multivariate conditional heteroscedastic model
Authors
KeywordsCausality in volatility
Conditional heteroscedastic arma model
Random coefficient model
Volatility
Issue Date1997
PublisherOxford University Press. The Journal's web site is located at http://biomet.oxfordjournals.org/
Citation
Biometrika, 1997, v. 84 n. 1, p. 111-123 How to Cite?
AbstractTsay (1987) developed the conditional heteroscedastic autoregressive moving-average model, which includes the conditional heteroscedastic autoregressive and random coefficient autoregressive models as special cases. This paper establishes the multivariate conditional heteroscedastic autoregressive moving-average model, and considers its theoretical properties and applications. Maximum likelihood estimation of the model is discussed in detail. A representation of the information matrix is obtained using the star product. This enhances estimation and statistical inferences procedures. Some simulation results and an application to the volatility of the Standard & Poor's 500 and Sydney's All Ordinaries indices are also considered.
Persistent Identifierhttp://hdl.handle.net/10722/82978
ISSN
2015 Impact Factor: 1.13
2015 SCImago Journal Rankings: 2.801
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorWong, Hen_HK
dc.contributor.authorLi, WKen_HK
dc.date.accessioned2010-09-06T08:35:33Z-
dc.date.available2010-09-06T08:35:33Z-
dc.date.issued1997en_HK
dc.identifier.citationBiometrika, 1997, v. 84 n. 1, p. 111-123en_HK
dc.identifier.issn0006-3444en_HK
dc.identifier.urihttp://hdl.handle.net/10722/82978-
dc.description.abstractTsay (1987) developed the conditional heteroscedastic autoregressive moving-average model, which includes the conditional heteroscedastic autoregressive and random coefficient autoregressive models as special cases. This paper establishes the multivariate conditional heteroscedastic autoregressive moving-average model, and considers its theoretical properties and applications. Maximum likelihood estimation of the model is discussed in detail. A representation of the information matrix is obtained using the star product. This enhances estimation and statistical inferences procedures. Some simulation results and an application to the volatility of the Standard & Poor's 500 and Sydney's All Ordinaries indices are also considered.en_HK
dc.languageengen_HK
dc.publisherOxford University Press. The Journal's web site is located at http://biomet.oxfordjournals.org/en_HK
dc.relation.ispartofBiometrikaen_HK
dc.rightsBiometrika. Copyright © Oxford University Press.en_HK
dc.subjectCausality in volatilityen_HK
dc.subjectConditional heteroscedastic arma modelen_HK
dc.subjectRandom coefficient modelen_HK
dc.subjectVolatilityen_HK
dc.titleOn a multivariate conditional heteroscedastic modelen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0006-3444&volume=84&issue=1&spage=111&epage=123&date=1997&atitle=On+a+multivariate+conditional+heteroscedastic+modelen_HK
dc.identifier.emailLi, WK: hrntlwk@hku.hken_HK
dc.identifier.authorityLi, WK=rp00741en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1093/biomet/84.1.111-
dc.identifier.scopuseid_2-s2.0-0000140190en_HK
dc.identifier.hkuros22004en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0000140190&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume84en_HK
dc.identifier.issue1en_HK
dc.identifier.spage111en_HK
dc.identifier.epage123en_HK
dc.identifier.isiWOS:A1997WT08200010-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridWong, H=7402864953en_HK
dc.identifier.scopusauthoridLi, WK=14015971200en_HK

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