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Extreme Return-Volume Dependence in East-Asian Stock Markets: A Copula Approach

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Author Info

  • Cathy Ning

    (Department of Economics, Ryerson University)

  • Tony S. Wirjanto

    (Department of Economics, University of Waterloo)

Abstract

A copula approach is adopted to examine the extreme return-volume relationship in six emerging East-Asian equity markets. The empirical results indicate that the return-volume dependence is significant and asymmetric at extremes for all six East-Asian markets. In particular extremely high returns (large gains) tend to be associated with extremely large trading volumes, but only marginal (extremely small) returns tend to be related to either large or small volumes.

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Bibliographic Info

Paper provided by University of Waterloo, Department of Economics in its series Working Papers with number 08009.

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Date of creation: Dec 2008
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Handle: RePEc:wat:wpaper:08009

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Keywords: Return-volume dependence; Extreme returns; Copulas; Tail dependence;

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References

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  1. Simon Gervais & Ron Kaniel & Dan Mingelgrin, . "The High Volume Return Premium," Rodney L. White Center for Financial Research Working Papers, Wharton School Rodney L. White Center for Financial Research 01-99, Wharton School Rodney L. White Center for Financial Research.
  2. Gerard Gennotte and Hayne Leland., 1989. "Market Liquidity, Hedging and Crashes," Research Program in Finance Working Papers, University of California at Berkeley RPF-192, University of California at Berkeley.
  3. Ser-Huang Poon, 2004. "Extreme Value Dependence in Financial Markets: Diagnostics, Models, and Financial Implications," Review of Financial Studies, Society for Financial Studies, Society for Financial Studies, vol. 17(2), pages 581-610.
  4. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1992. "Stock Prices and Volume," Review of Financial Studies, Society for Financial Studies, Society for Financial Studies, vol. 5(2), pages 199-242.
  5. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, Econometric Society, vol. 50(4), pages 987-1007, July.
  6. Robert J. Hodrick & Edward Prescott, 1981. "Post-War U.S. Business Cycles: An Empirical Investigation," Discussion Papers, Northwestern University, Center for Mathematical Studies in Economics and Management Science 451, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
  7. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, Elsevier, vol. 25(5), pages 827-853, August.
  8. Terry A. Marsh & Niklas Wagner, 2004. "Return-Volume Dependence and Extremes in International Equity Markets," Finance, EconWPA 0401007, EconWPA.
  9. Ling Hu, 2006. "Dependence patterns across financial markets: a mixed copula approach," Applied Financial Economics, Taylor & Francis Journals, Taylor & Francis Journals, vol. 16(10), pages 717-729.
  10. Andrew Patton, 2004. "Modelling Asymmetric Exchange Rate Dependence," Working Papers, Warwick Business School, Finance Group wp04-04, Warwick Business School, Finance Group.
  11. Balduzzi, Pierluigi & Kallal, Hedi & Longin, Francois, 1996. "Minimal returns and the breakdown of the price-volume relation," Economics Letters, Elsevier, Elsevier, vol. 50(2), pages 265-269, February.
  12. Chen, Xiaohong & Fan, Yanqin, 2006. "Estimation of copula-based semiparametric time series models," Journal of Econometrics, Elsevier, Elsevier, vol. 130(2), pages 307-335, February.
  13. Donaldson, R.G. & Uhlig, H., 1991. "Portfolio Insurance And Asset Prices," Papers, Princeton, Department of Economics - Financial Research Center 126, Princeton, Department of Economics - Financial Research Center.
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Cited by:
  1. Rossi, Eduardo & Santucci de Magistris, Paolo, 2013. "Long memory and tail dependence in trading volume and volatility," Journal of Empirical Finance, Elsevier, Elsevier, vol. 22(C), pages 94-112.
  2. Chen, Shiu-Sheng, 2012. "Revisiting the empirical linkages between stock returns and trading volume," MPRA Paper 36897, University Library of Munich, Germany.
  3. Ivan Medovikov, 2014. "Can Analysts Predict Rallies Better Than Crashes?," Papers 1405.3225, arXiv.org.
  4. Chen, Wang & Wei, Yu & Lang, Qiaoqi & Lin, Yu & Liu, Maojuan, 2014. "Financial market volatility and contagion effect: A copula–multifractal volatility approach," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 398(C), pages 289-300.

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