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The Stock Return - Trading Volume Relationship in European Countries: Evidence from Asymmetric Impulse Responses

Author

Listed:
  • Ralf Brüggemann

    (Department of Economics, University of Konstanz, Germany)

  • Markus Glaser

    (Institute for Capital Markets and Corporate Finance, Munich School of Management, Ludwig- Maximilians-Universität München, Germany)

  • Stefan Schaarschmidt

    (Department of Economics, University of Konstanz, Germany)

  • Sandra Stankiewicz

    (Department of Economics, University of Konstanz, Germany)

Abstract

We investigate non-linearities in the stock return - trading volume relationship by using daily data for 16 European countries in an asymmetric vector autoregressive model. In this framework, we test for asymmetries and analyze the dynamic relationship using a simulation based procedure for computing asymmetric impulse response functions. We find that stock returns have a significant influence on trading volume, but there is no evidence for the influence of trading volume on returns. Our analysis indicates that responses of trading volume to return shocks are non-linear and the sign of the response depends on the absolute size of the shock. Thus, using linear VAR models may lead to wrong conclusions concerning the return - volume relationship. We also find that after stock markets go up (down), investors trade significantly more (less) in small and mid cap stocks, supporting evidence for the theories of overconfidence, market participation, differences of opinion, and disposition effect.

Suggested Citation

  • Ralf Brüggemann & Markus Glaser & Stefan Schaarschmidt & Sandra Stankiewicz, 2014. "The Stock Return - Trading Volume Relationship in European Countries: Evidence from Asymmetric Impulse Responses," Working Paper Series of the Department of Economics, University of Konstanz 2014-24, Department of Economics, University of Konstanz.
    • Handle: RePEc:knz:dpteco:1424
    as

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    File URL: http://www.uni-konstanz.de/FuF/wiwi/workingpaperseries/WP_24_Brueggemann-Glaser-Schaarschmidt-Stankiewicz_2014.pdf
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    References listed on IDEAS

    as
    1. Shalen, Catherine T, 1993. "Volume, Volatility, and the Dispersion of Beliefs," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 405-434.
    2. Gervais, Simon & Odean, Terrance, 2001. "Learning to be Overconfident," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 1-27.
    3. Terrance Odean., 1996. "Volume, Volatility, Price and Profit When All Trader Are Above Average," Research Program in Finance Working Papers RPF-266, University of California at Berkeley.
    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. Kandel, Eugene & Pearson, Neil D, 1995. "Differential Interpretation of Public Signals and Trade in Speculative Markets," Journal of Political Economy, University of Chicago Press, vol. 103(4), pages 831-872, August.
    6. Glaser, Markus & Weber, Martin, 2009. "Which past returns affect trading volume?," Journal of Financial Markets, Elsevier, vol. 12(1), pages 1-31, February.
    7. Orosel, Gerhard O, 1998. "Participation Costs, Trend Chasing, and Volatility of Stock Prices," The Review of Financial Studies, Society for Financial Studies, vol. 11(3), pages 521-557.
    8. You, Leyuan & Daigler, Robert T., 2010. "Is international diversification really beneficial?," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 163-173, January.
    9. John M. Griffin & Federico Nardari & René M. Stulz, 2007. "Do Investors Trade More When Stocks Have Performed Well? Evidence from 46 Countries," The Review of Financial Studies, Society for Financial Studies, vol. 20(3), pages 905-951.
    10. Moosa, Imad A. & Silvapulle, Param, 2000. "The price-volume relationship in the crude oil futures market Some results based on linear and nonlinear causality testing," International Review of Economics & Finance, Elsevier, vol. 9(1), pages 11-30, February.
    11. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(1), pages 109-126, March.
    12. Goncalves, Silvia & Kilian, Lutz, 2004. "Bootstrapping autoregressions with conditional heteroskedasticity of unknown form," Journal of Econometrics, Elsevier, vol. 123(1), pages 89-120, November.
    13. Kent Daniel & David Hirshleifer & Avanidhar Subrahmanyam, 1998. "Investor Psychology and Security Market Under- and Overreactions," Journal of Finance, American Finance Association, vol. 53(6), pages 1839-1885, December.
    14. Terrance Odean, 1998. "Are Investors Reluctant to Realize Their Losses?," Journal of Finance, American Finance Association, vol. 53(5), pages 1775-1798, October.
    15. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    16. Lutz Kilian & Robert J. Vigfusson, 2011. "Are the responses of the U.S. economy asymmetric in energy price increases and decreases?," Quantitative Economics, Econometric Society, vol. 2(3), pages 419-453, November.
    17. Meir Statman & Steven Thorley & Keith Vorkink, 2006. "Investor Overconfidence and Trading Volume," The Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1531-1565.
    18. Lee, Bong-Soo & Rui, Oliver M., 2002. "The dynamic relationship between stock returns and trading volume: Domestic and cross-country evidence," Journal of Banking & Finance, Elsevier, vol. 26(1), pages 51-78, January.
    19. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    20. Harris, Milton & Raviv, Artur, 1993. "Differences of Opinion Make a Horse Race," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 473-506.
    21. Werner Antweiler & Murray Z. Frank, 2004. "Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards," Journal of Finance, American Finance Association, vol. 59(3), pages 1259-1294, June.
    22. Brown, Stephen J, et al, 1992. "Survivorship Bias in Performance Studies," The Review of Financial Studies, Society for Financial Studies, vol. 5(4), pages 553-580.
    23. Ozgur S. Ince & R. Burt Porter, 2006. "Individual Equity Return Data From Thomson Datastream: Handle With Care!," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 29(4), pages 463-479, December.
    24. Wang, Jiang, 1994. "A Model of Competitive Stock Trading Volume," Journal of Political Economy, University of Chicago Press, vol. 102(1), pages 127-168, February.
    25. Epps, Thomas W, 1975. "Security Price Changes and Transaction Volumes: Theory and Evidence," American Economic Review, American Economic Association, vol. 65(4), pages 586-597, September.
    26. Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    27. Terrance Odean, 1998. "Volume, Volatility, Price, and Profit When All Traders Are Above Average," Journal of Finance, American Finance Association, vol. 53(6), pages 1887-1934, December.
    28. Bamber, Linda Smith & Barron, Orie E. & Stober, Thomas L., 1999. "Differential Interpretations and Trading Volume," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(3), pages 369-386, September.
    29. Imad A. Moosa & Param Silvapulle & Mervyn Silvapulle, 2003. "Testing for Temporal Asymmetry in the Price‐Volume Relationship," Bulletin of Economic Research, Wiley Blackwell, vol. 55(4), pages 373-389, October.
    30. Chen, Shiu-Sheng, 2012. "Revisiting the empirical linkages between stock returns and trading volume," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1781-1788.
    31. Gerlach, Richard & Chen, Cathy W.S. & Lin, Doris S.Y. & Huang, Ming-Hsiang, 2006. "Asymmetric responses of international stock markets to trading volume," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 360(2), pages 422-444.
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    More about this item

    Keywords

    asymmetric vector autoregression; asymmetric impulse response functions; stock return; trading volume;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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