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Asymmetric Learning from Prices and Post‐Earnings‐Announcement Drift

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  • Jaewon Choi
  • Linh Thompson
  • Jared Williams

Abstract

Motivated by research in psychology and experimental economics, we assume that investors update their beliefs about an asset's value upon observing the price, but only when the price clearly reveals that others obtained private information that differs from their own private information. Specifically, we assume that investors learn from the price of an asset in an asymmetric manner—they learn from the price if they observe good (bad) private information and the price is worse (better) than what is justified based on public information alone. We show that asymmetric learning from an asset's price leads to post‐earnings‐announcement drift (PEAD), and that it generates arbitrage opportunities that are less attractive than alternative explanations of PEAD. In addition, our model predicts that PEAD will be concentrated in earnings surprises that are not dominated by accruals, and it also predicts that earnings response coefficients will decline in the magnitude of the earnings surprises. Asymétrie de l'enseignement tiré des prix et mouvement réactif postérieur à l'annonce des résultats Les recherches en psychologie et en économie expérimentale amènent les auteurs à poser l'hypothèse selon laquelle les investisseurs mettent à jour leurs convictions quant à la valeur d'un actif en observant le prix, mais seulement si ce prix révèle clairement que d'autres ont eu accès à de l'information privilégiée différente de celle dont eux disposent. Les auteurs supposent plus précisément que l'enseignement que tirent les investisseurs du prix d'un actif est asymétrique — il ne se concrétise que si les investisseurs ont accès à de l'information privilégiée favorable (défavorable) et que le prix est moins avantageux (plus avantageux) que ne le justifie à elle seule l'information portée à la connaissance du public. Ils montrent que l'enseignement asymétrique tiré du prix d'un actif mène à un mouvement réactif postérieur à l'annonce des résultats (MRPAR) et qu'il donne naissance à des occasions d'arbitrage qui sont moins intéressantes que celles qui découlent d'autres explications du MRPAR. De plus, les auteurs prédisent, conformément à leur modèle, que le MRPAR se manifestera surtout dans le cas de résultats inattendus dont les régularisations ne sont pas la principale explication, et que les coefficients de réaction aux résultats déclinent avec l'ampleur de l'écart par rapport aux attentes.

Suggested Citation

  • Jaewon Choi & Linh Thompson & Jared Williams, 2019. "Asymmetric Learning from Prices and Post‐Earnings‐Announcement Drift," Contemporary Accounting Research, John Wiley & Sons, vol. 36(3), pages 1724-1750, September.
  • Handle: RePEc:wly:coacre:v:36:y:2019:i:3:p:1724-1750
    DOI: 10.1111/1911-3846.12477
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    References listed on IDEAS

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    1. Babcock, Bruce A. & Choi, E. Kwan & Feinerman, Eli, 1993. "Risk And Probability Premiums For Cara Utility Functions," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 18(1), pages 1-8, July.
    2. Barinov, Alexander & Park, Shawn Saeyeul & Yildizhan, Celim, 2014. "Firm Complexity and Post-Earnings-Announcement Drift," MPRA Paper 53887, University Library of Munich, Germany.
    3. Grossman, Sanford J & Stiglitz, Joseph E, 1976. "Information and Competitive Price Systems," American Economic Review, American Economic Association, vol. 66(2), pages 246-253, May.
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    1. Josef Fink, 2020. "A Review of the Post-Earnings-Announcement Drift," Working Paper Series, Social and Economic Sciences 2020-04, Faculty of Social and Economic Sciences, Karl-Franzens-University Graz.
    2. Fink, Josef, 2021. "A review of the Post-Earnings-Announcement Drift," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).

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