FN ISI Export Format VR 1.0 PT J TI Stock return autocorrelations revisited: A quantile regression approach AF Baur, Dirk G. Dimpfl, Thomas Jung, Robert C. AU Baur, DG Dimpfl, T Jung, RC SO Journal of Empirical Finance SN 0927-5398 VL 19 BP 254 EP 265 PY 2012 DE Overreaction and underreaction;Quantile autoregression;Stock return distribution AB 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 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. DI 10.1016/j.jempfin.2011.12.002 ER