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 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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Bibliographic InfoPaper provided by University of Tuebingen, Faculty of Economics and Social Sciences in its series University of Tuebingen Working Papers in Economics and Finance with number 24.
Date of creation: 2012
Date of revision:
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," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 254-265.
- 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
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- Jonathan Lewellen, 2002. "Momentum and Autocorrelation in Stock Returns," Review of Financial Studies, Society for Financial Studies, vol. 15(2), pages 533-564, March.
- 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.
- 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.
- 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.
- Barberis, Nicholas & Shleifer, Andrei & Vishny, Robert, 1998.
"A model of investor sentiment,"
Journal of Financial Economics,
Elsevier, vol. 49(3), pages 307-343, September.
- 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.
- 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.
- Robert Engle & Simone Manganelli, 2000. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Econometric Society World Congress 2000 Contributed Papers 0841, Econometric Society.
- Koenker, Roger & Xiao, Zhijie, 2006. "Quantile Autoregression," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 980-990, September.
- 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.
- 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.
- Walid Mensi & Shawkat Hammoudeh & Juan Carlos Reboredo & Duc Khuong Nguyen, 2014.
"Do global factors impact BRICS stock markets? A quantile regression approach,"
2014-159, Department of Research, Ipag Business School.
- Mensi, Walid & Hammoudeh, Shawkat & Reboredo, Juan Carlos & Nguyen, Duc Khuong, 2014. "Do global factors impact BRICS stock markets? A quantile regression approach," Emerging Markets Review, Elsevier, vol. 19(C), pages 1-17.
- Katarzyna Bien-Barkowska, 2012. ""Does it take volume to move fx rates?" Evidence from quantile regressions," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 12, pages 35-52.
- 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.
- 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.
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