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Causality in Quantiles and Dynamic Stock Return-Volume Relations

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Author Info

  • Chia-Chang Chuang

    (Department of International Business National Taipei College of Business)

  • Chung-Ming Kuan

    ()
    (Institute of Economics, Academia Sinica, Taipei, Taiwan)

  • Hsin-yi Lin

    (Department of Economics National Chengchi University)

Abstract

This paper investigates the causal relations between stock return and volume based on quantile regressions. We first define Granger non-causality in all quantiles and propose testing non-causality by a sup-Wald test. Such a test is consistent against any deviation from non-causality in distribution, as opposed to the existing tests that check only noncausality in certain moment. This test is readily extended to test non-causality in different quantile ranges, and the testing results enable us to identify the quantile range for which causality is relevant. In the empirical studies of 3 major stock market indices, we find that, while the conventional test suggests no causality in mean, there are strong evidences that lagged volume Granger causes return in all but some middle quantiles. In particular, the causal effects have opposite signs at lower and upper quantiles and are stronger at more extreme quantiles. These relations form (symmetric) V shapes across quantiles. They also show that the dispersion of the return distribution increases with volume so that volume has a positive effect on return volatility. It is also shown that the quantile causal effects of lagged return on volume are mainly negative.

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Bibliographic Info

Paper provided by Institute of Economics, Academia Sinica, Taipei, Taiwan in its series IEAS Working Paper : academic research with number 07-A006.

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Length: 22 pages
Date of creation: Jun 2007
Date of revision:
Handle: RePEc:sin:wpaper:07-a006

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Keywords: Granger non-causality in quantiles; quantile causal effect; quantile regression; return-volume relation; sup-Wald test;

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References

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Citations

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Cited by:
  1. 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.
  2. Rubin, Amir & Smith, Daniel R., 2011. "Comparing different explanations of the volatility trend," Journal of Banking & Finance, Elsevier, vol. 35(6), pages 1581-1597, June.
  3. Chen, Shiu-Sheng, 2012. "Revisiting the empirical linkages between stock returns and trading volume," MPRA Paper 36897, University Library of Munich, Germany.
  4. Gebka, Bartosz & Wohar, Mark E., 2013. "Causality between trading volume and returns: Evidence from quantile regressions," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 144-159.
  5. Chen, Cathy W.S. & Gerlach, Richard & Wei, D.C.M., 2009. "Bayesian causal effects in quantiles: Accounting for heteroscedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1993-2007, April.
  6. 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.
  7. Siddhartha Bandyopadhyay & Samrat Bhattacharya & Rudra Sensarma, 2011. "An Analysis of the Factors Determining Crime in England and Wales: A Quantile Regression Approach," Discussion Papers 11-12, Department of Economics, University of Birmingham.
  8. Jesús Gonzalo & AbderrahimTaamouti, 2012. "The reaction of stock market returns to anticipated unemployment," Economics Working Papers we1237, Universidad Carlos III, Departamento de Economía.
  9. Walid Mensi & Shawkat Hammoudeh & Juan Carlos Reboredo & Duc Khuong Nguyen, 2014. "Do global factors impact BRICS stock markets? A quantile regression approach," Working Papers 2014-159, Department of Research, Ipag Business School.
  10. Baur, Dirk G., 2013. "The structure and degree of dependence: A quantile regression approach," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 786-798.
  11. Broto, Carmen & Díaz-Cassou, Javier & Erce, Aitor, 2011. "Measuring and explaining the volatility of capital flows to emerging countries," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1941-1953, August.
  12. Lee, Bong Soo & Li, Ming-Yuan Leon, 2012. "Diversification and risk-adjusted performance: A quantile regression approach," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2157-2173.
  13. 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.
  14. Tekaya, Rim & Jouaber, Kaouther, 2010. "Time and dynamic Volume-Volatility Relation around Option Listing: Evidence from the French Underlying Stocks," Economics Papers from University Paris Dauphine 123456789/5069, Paris Dauphine University.

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