Evidence of an asymmetry in the relationship between volatility and autocorrelation McKenzie, Michael en_US Kim, Suk-Joong en_US 2021-11-25T13:37:37Z 2021-11-25T13:37:37Z 2007 en_US
dc.description.abstract This paper focuses on the general determinants of autocorrelation and the relationship between autocorrelation and volatility in particular. Using UK stock market index and individual stock price data, a multivariate generalized autoregressive conditional heteroskedasticity (M-GARCH) model is used to generate estimates of conditional autocorrelation. The covariance equation of this model is modified to include the potential determinants of autocorrelation including volatility, which is proxied using the time series of filtered probabilities of a Markov regime switching model. Consistent with the previous literature, this paper documents a negative relationship between volatility and autocorrelation. The results suggest that an asymmetry exists in this relationship which is attributed to the constraints placed on short selling. en_US
dc.identifier.issn 1057-5219 en_US
dc.language English
dc.language.iso EN en_US
dc.rights CC BY-NC-ND 3.0 en_US
dc.rights.uri en_US
dc.source Legacy MARC en_US
dc.title Evidence of an asymmetry in the relationship between volatility and autocorrelation en_US
dc.type Journal Article en
dcterms.accessRights open access
dspace.entity.type Publication en_US
unsw.identifier.doiPublisher en_US
unsw.relation.faculty Business
unsw.relation.ispartofissue 1 en_US
unsw.relation.ispartofjournal International Review of Financial Analysis en_US
unsw.relation.ispartofpagefrompageto 22-40 en_US
unsw.relation.ispartofvolume 16 en_US
unsw.relation.originalPublicationAffiliation McKenzie, Michael en_US
unsw.relation.originalPublicationAffiliation Kim, Suk-Joong, Banking & Finance, Australian School of Business, UNSW en_US School of Banking & Finance *
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