Stock Return Autocorrelations Revisited: A Quantile Regression Approach

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Show simple item record Baur, Dirk G. de_DE Dimpfl, Thomas de_DE Jung, Robert C. de_DE 2012-01-10 de_DE 2014-03-18T10:03:49Z 2012-01-10 de_DE 2014-03-18T10:03:49Z 2012 de_DE
dc.identifier.other 356166791 de_DE
dc.identifier.uri de_DE
dc.description.abstract The aim of this study is to provide a comprehensive description of the dependence pattern of stock returns by studying a range of quantiles of the conditional return distribution using quantile autoregression. This enables us in particular to study the behavior of extreme quantiles associated with large positive and negative returns in contrast to the central quantile which is closely related to the conditional mean in the least-squares regression framework. Our empirical results are based on 30 years of daily, weekly and monthly returns of the stocks comprised in the Dow Jones Stoxx 600 index. We find that lower quantiles exhibit positive dependence on past returns while upper quantiles are marked by negative dependence. This pattern holds when accounting for stock specific characteristics such as market capitalization, industry, or exposure to market risk. en
dc.language.iso en de_DE
dc.publisher Universität Tübingen de_DE
dc.rights ubt-podno de_DE
dc.rights.uri de_DE
dc.rights.uri en
dc.subject.classification Aktie de_DE
dc.subject.ddc 330 de_DE
dc.subject.other Aktien de_DE
dc.subject.other Stock return distribution , Quantile autoregression , Overreaction and underreaction en
dc.title Stock Return Autocorrelations Revisited: A Quantile Regression Approach en
dc.type ResearchPaper de_DE
utue.publikation.fachbereich Wirtschaftswissenschaften de_DE
utue.publikation.fakultaet 6 Wirtschafts- und Sozialwissenschaftliche Fakultät de_DE
dcterms.DCMIType Text de_DE
utue.publikation.typ workingPaper de_DE 5976 de_DE
utue.publikation.source University of Tübingen Working Papers in Economics and Finance ; 24 de_DE


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