Stock Return Autocorrelations Revisited: A Quantile Regression Approach

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URI: http://nbn-resolving.de/urn:nbn:de:bsz:21-opus-59769
http://hdl.handle.net/10900/47887
Dokumentart: ResearchPaper
Date: 2012
Source: University of Tübingen Working Papers in Economics and Finance ; 24
Language: English
Faculty: 6 Wirtschafts- und Sozialwissenschaftliche Fakultät
Department: Wirtschaftswissenschaften
DDC Classifikation: 330 - Economics
Keywords: Aktie
Other Keywords: Aktien
Stock return distribution , Quantile autoregression , Overreaction and underreaction
License: Publishing license excluding print on demand
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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.

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