Stock return autocorrelations revisited: A quantile regression approach
AbstractThe 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 30years 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Journal of Empirical Finance.
Volume (Year): 19 (2012)
Issue (Month): 2 ()
Contact details of provider:
Web page: http://www.elsevier.com/locate/jempfin
Stock return distribution; Quantile autoregression; Overreaction and underreaction;
Other versions of this item:
- Baur, Dirk G. & Dimpfl, Thomas & Jung, Robert C., 2012. "Stock return autocorrelations revisited: A quantile regression approach," University of Tuebingen Working Papers in Economics and Finance 24, University of Tuebingen, Faculty of Economics and Social Sciences.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Chuang, Chia-Chang & Kuan, Chung-Ming & Lin, Hsin-Yi, 2009.
"Causality in quantiles and dynamic stock return-volume relations,"
Journal of Banking & Finance,
Elsevier, vol. 33(7), pages 1351-1360, July.
- Chia-Chang Chuang & Chung-Ming Kuan & Hsin-yi Lin, 2007. "Causality in Quantiles and Dynamic Stock Return-Volume Relations," IEAS Working Paper : academic research 07-A006, Institute of Economics, Academia Sinica, Taipei, Taiwan.
- Koenker, Roger & Xiao, Zhijie, 2006. "Quantile Autoregression," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 980-990, September.
- Lingjie Ma & Larry Pohlman, 2008. "Return forecasts and optimal portfolio construction: a quantile regression approach," The European Journal of Finance, Taylor & Francis Journals, vol. 14(5), pages 409-425.
- Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993.
"On the relation between the expected value and the volatility of the nominal excess return on stocks,"
157, Federal Reserve Bank of Minneapolis.
- Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. " On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
- Andrew W. Lo & Craig A. MacKinlay, .
"An Econometric Analysis of Nonsyschronous-Trading,"
Rodney L. White Center for Financial Research Working Papers
19-89, Wharton School Rodney L. White Center for Financial Research.
- Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
- Robert Engle & Simone Manganelli, 2000.
"CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles,"
Econometric Society World Congress 2000 Contributed Papers
0841, Econometric Society.
- Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
- Engle, Robert F & Manganelli, Simone, 1999. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," University of California at San Diego, Economics Working Paper Series qt06m3d6nv, Department of Economics, UC San Diego.
- Barberis, Nicholas & Shleifer, Andrei & Vishny, Robert, 1998.
"A model of investor sentiment,"
Journal of Financial Economics,
Elsevier, vol. 49(3), pages 307-343, September.
- Jonathan Lewellen, 2002. "Momentum and Autocorrelation in Stock Returns," Review of Financial Studies, Society for Financial Studies, vol. 15(2), pages 533-564, March.
- Campbell, Rachel A.J. & Forbes, Catherine S. & Koedijk, Kees G. & Kofman, Paul, 2008. "Increasing correlations or just fat tails?," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 287-309, March.
- Katarzyna Bien-Barkowska, 2012. ""Does it take volume to move fx rates?" Evidence from quantile regressions," Dynamic Econometric Models, Wydawnictwo Naukowe Uniwersytetu Mikolaja Kopernika, vol. 12, pages 35-52.
- Hendrik Kaufmannz & Robinson Kruse, 2013. "Bias-corrected estimation in potentially mildly explosive autoregressive models," CREATES Research Papers 2013-10, School of Economics and Management, University of Aarhus.
- Dirk G Baur & Thomas Dimpfl, 2012. "State-dependent Momentum in International Stock Markets," Working Paper Series 169, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
- Adelina Gschwandtner & Michael Hauser, 2013. "Profit Persistence and Stock Returns," Studies in Economics 1320, Department of Economics, University of Kent.
- Paulo Sergio Ceretta & Marcelo Brutti Righi & Alexandre Silva Da costa & Fernanda Maria Muller, 2012. "Quantiles autocorrelation in stock markets returns," Economics Bulletin, AccessEcon, vol. 32(3), pages 2065-2075.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.