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dc.contributor.authorMcAleer, M.
dc.contributor.authorChan, Felix
dc.contributor.authorHoti, S.
dc.contributor.authorLieberman, O.
dc.date.accessioned2017-01-30T13:37:05Z
dc.date.available2017-01-30T13:37:05Z
dc.date.created2010-05-18T20:03:05Z
dc.date.issued2008
dc.identifier.citationMcAleer, Michael and Chan, Felix and Hoti, Suhejla and Lieberman, Offer. 2008. Generalized autoregressive conditional correlation. Econometric Theory. 24: pp. 1554-1583.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/33440
dc.identifier.doi10.1017/S0266466608080614
dc.description.abstract

This paper develops a generalized autoregressive conditional correlation (GARCC) model when the standardized residuals follow a random coefficient vector autoregressive process. As a multivariate generalization of the Tsay (1987, Journal of the American Statistical Association 82, 590-604) random coefficient autoregressive (RCA) model, the GARCC model provides a motivation for the conditional correlations to be time varying. GARCC is also more general than the Engle (2002, Journal of Business & Economic Statistics 20, 339-350) dynamic conditional correlation (DCC) and the Tse and Tsui (2002, Journal of Business & Economic Statistics 20, 351-362) varying conditional correlation (VCC) models and does not impose unduly restrictive conditions on the parameters of the DCC model. The structural properties of the GARCC model, specifically, the analytical forms of the regularity conditions, are derived, and the asymptotic theory is established. The Baba, Engle, Kraft, and Kroner (BEKK) model of Engle and Kroner (1995, Econometric Theory 11, 122-150) is demonstrated to be a special case of a multivariate RCA process. A likelihood ratio test is proposed for several special cases of GARCC. The empirical usefulness of GARCC and the practicality of the likelihood ratio test are demonstrated for the daily returns of the Standard and Poor's 500, Nikkei, and Hang Seng indexes.

dc.publisherCambridge University Press
dc.titleGeneralized autoregressive conditional correlation
dc.typeJournal Article
dcterms.source.volume24
dcterms.source.startPage1554
dcterms.source.endPage1583
dcterms.source.issn0266-4666
dcterms.source.titleEconometric Theory
curtin.note

© Cambridge University Press 2008

curtin.accessStatusOpen access
curtin.facultyCurtin Business School
curtin.facultySchool of Economics and Finance


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