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Do Heterogeneous Beliefs Matter to Post‐announcement Informed Trading?

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  • Tao Chen
  • Andreas Karathanasopoulos

Abstract

We examine whether heterogeneous beliefs among investors affect post‐announcement informed trading. Using a global transaction‐level dataset, we find that post‐announcement informed trading increases with heterogeneous beliefs developed at the event window. Such an inference survives from several robustness checks. As additional analyses indicate, shrinking liquidity at the earnings announcement serves as a transmission mechanism to rationalize the documented association. Eventually, we reveal that informed trading driven by belief heterogeneity plays a dominant role in explaining post‐announcement returns.

Suggested Citation

  • Tao Chen & Andreas Karathanasopoulos, 2022. "Do Heterogeneous Beliefs Matter to Post‐announcement Informed Trading?," Abacus, Accounting Foundation, University of Sydney, vol. 58(4), pages 714-741, December.
    • Handle: RePEc:bla:abacus:v:58:y:2022:i:4:p:714-741
    DOI: 10.1111/abac.12272
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    1. Beveridge, Stephen & Nelson, Charles R., 1981. "A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the `business cycle'," Journal of Monetary Economics, Elsevier, vol. 7(2), pages 151-174.
    2. Arthur Lewbel, 2012. "Using Heteroscedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 67-80.
    3. Bruno Biais & Peter Bossaerts, 1998. "Asset Prices and Trading Volume in a Beauty Contest," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 307-340.
    4. Paolo Pasquariello, 2007. "Imperfect Competition, Information Heterogeneity, and Financial Contagion," The Review of Financial Studies, Society for Financial Studies, vol. 20(2), pages 391-426.
    5. Adem Atmaz & Suleyman Basak, 2018. "Belief Dispersion in the Stock Market," Journal of Finance, American Finance Association, vol. 73(3), pages 1225-1279, June.
    6. Chen, Tao, 2021. "Informed trading and earnings announcement driven disagreement in global markets," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 43(C).
    7. Verardo, Michela, 2009. "Heterogeneous Beliefs and Momentum Profits," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(4), pages 795-822, August.
    8. Pevzner, Mikhail & Xie, Fei & Xin, Xiangang, 2015. "When firms talk, do investors listen? The role of trust in stock market reactions to corporate earnings announcements," Journal of Financial Economics, Elsevier, vol. 117(1), pages 190-223.
    9. Beaver, Wh, 1968. "Information Content Of Annual Earnings Announcements," Journal of Accounting Research, Wiley Blackwell, vol. 6, pages 67-92.
    10. Joshua D. Anderson & John E. Core, 2018. "Managerial Incentives to Increase Risk Provided by Debt, Stock, and Options," Management Science, INFORMS, vol. 64(9), pages 4408-4432, September.
    11. 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.
    12. Hasbrouck, Joel, 1991. "The Summary Informativeness of Stock Trades: An Econometric Analysis," The Review of Financial Studies, Society for Financial Studies, vol. 4(3), pages 571-595.
    13. Haw, In-Mu & Hu, Bingbing & Lee, Jay Junghun, 2015. "Product market competition and analyst forecasting activity: International evidence," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 48-60.
    14. Thaddeus Neururer & George Papadakis & Edward J. Riedl, 2016. "Tests of investor learning models using earnings innovations and implied volatilities," Review of Accounting Studies, Springer, vol. 21(2), pages 400-437, June.
    15. Tao Chen, 2022. "Delayed informed trades and opinion divergence: Evidence from earnings releases," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4556-4574, October.
    16. Brian M. Weller, 2018. "Does Algorithmic Trading Reduce Information Acquisition?," The Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2184-2226.
    17. Meulbroek, Lisa K, 1992. "An Empirical Analysis of Illegal Insider Trading," Journal of Finance, American Finance Association, vol. 47(5), pages 1661-1699, December.
    18. Sebastien Pouget & Julien Sauvagnat & Stephane Villeneuve, 2017. "A Mind Is a Terrible Thing to Change: Confirmatory Bias in Financial Markets," The Review of Financial Studies, Society for Financial Studies, vol. 30(6), pages 2066-2109.
    19. Avramov, Doron & Chordia, Tarun & Jostova, Gergana & Philipov, Alexander, 2009. "Dispersion in analysts' earnings forecasts and credit rating," Journal of Financial Economics, Elsevier, vol. 91(1), pages 83-101, January.
    20. Mulherin, J. Harold & Boone, Audra L., 2000. "Comparing acquisitions and divestitures," Journal of Corporate Finance, Elsevier, vol. 6(2), pages 117-139, July.
    21. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    22. Jianguo Xu, 2007. "Price Convexity and Skewness," Journal of Finance, American Finance Association, vol. 62(5), pages 2521-2552, October.
    23. Karpoff, Jonathan M, 1986. "A Theory of Trading Volume," Journal of Finance, American Finance Association, vol. 41(5), pages 1069-1087, December.
    24. Michael J. Barclay, 2003. "Price Discovery and Trading After Hours," The Review of Financial Studies, Society for Financial Studies, vol. 16(4), pages 1041-1073.
    25. Jon A. Garfinkel, 2009. "Measuring Investors' Opinion Divergence," Journal of Accounting Research, Wiley Blackwell, vol. 47(5), pages 1317-1348, December.
    26. T. Clifton Green, 2004. "Economic News and the Impact of Trading on Bond Prices," Journal of Finance, American Finance Association, vol. 59(3), pages 1201-1234, June.
    27. Jain, Archana & Jain, Pankaj K. & McInish, Thomas H. & McKenzie, Michael, 2013. "Worldwide reach of short selling regulations," Journal of Financial Economics, Elsevier, vol. 109(1), pages 177-197.
    28. Ekkehart Boehmer & Juan (Julie) Wu, 2013. "Short Selling and the Price Discovery Process," The Review of Financial Studies, Society for Financial Studies, vol. 26(2), pages 287-322.
    29. William R. Gebhardt & Charles M. C. Lee & Bhaskaran Swaminathan, 2001. "Toward an Implied Cost of Capital," Journal of Accounting Research, Wiley Blackwell, vol. 39(1), pages 135-176, June.
    30. Ronnie Sadka & Anna Scherbina, 2007. "Analyst Disagreement, Mispricing, and Liquidity," Journal of Finance, American Finance Association, vol. 62(5), pages 2367-2403, October.
    31. Aktas, Nihat & de Bodt, Eric & Roll, Richard, 2004. "Market Response to European Regulation of Business Combinations," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(4), pages 731-757, December.
    32. Lee, Charles M C & Ready, Mark J, 1991. "Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-746, June.
    33. Linda Smith Bamber & Orie E. Barron & Douglas E. Stevens, 2011. "Trading Volume Around Earnings Announcements and Other Financial Reports: Theory, Research Design, Empirical Evidence, and Directions for Future Research," Contemporary Accounting Research, John Wiley & Sons, vol. 28(2), pages 431-471, June.
    34. Ed Dehaan & Joshua Madsen & Joseph D. Piotroski, 2017. "Do Weather‐Induced Moods Affect the Processing of Earnings News?," Journal of Accounting Research, Wiley Blackwell, vol. 55(3), pages 509-550, June.
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