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Title:Stock return autocorrelations revisited: A quantile regression approach PDF Logo
Authors:Baur, Dirk G.
Dimpfl, Thomas
Jung, Robert C.
Issue Date:2012
Series/Report no.:University of Tübingen working papers in economics and finance 24
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.
Subjects:stock return distribution
quantile autoregression
overreaction and underreaction
JEL:C22
G14
Persistent Identifier of the first edition:urn:nbn:de:bsz:21-opus-59769
Document Type:Working Paper
Appears in Collections:University of Tübingen Working Papers in Economics and Finance

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