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Inefficiency in Earnings Forecasts: Experimental Evidence of Reactions to Positive vs. Negative Information

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  • Douglas Stevens
  • Arlington Williams

Abstract

Prior archival studies of analysts' forecasts have found evidence for systematic underreaction, systematic overreaction, and systematic optimism bias. Easterwood and Nutt (1999) attempt to reconcile the conflicting evidence by testing the robustness of Abarbanell and Bernard's (1992) underreaction results to the nature of the information. Consistent with systematic optimism, forecasts are found to underreact to negative earnings information but overreact to positive information. However, Easterwood and Nutt are unable to distinguish between misreaction caused by incentives unique to analysts with misreaction caused by human decision bias that may be typical of investors. We address this issue by analyzing forecast reactions to positive versus negative information in the controlled experimental setting of Gillette, Stevens, Watts, and Williams (1999). The forecast data reveal systematic underreaction to both positive and negative information, and the underreaction is generally greater for positive information than negative information. This suggests that prior empirical evidence of forecast overreaction to positive information is unlikely to be attributable to human decision bias. Copyright Kluwer Academic Publishers 2004

Suggested Citation

  • Douglas Stevens & Arlington Williams, 2004. "Inefficiency in Earnings Forecasts: Experimental Evidence of Reactions to Positive vs. Negative Information," Experimental Economics, Springer;Economic Science Association, vol. 7(1), pages 75-92, February.
  • Handle: RePEc:kap:expeco:v:7:y:2004:i:1:p:75-92
    DOI: 10.1023/A:1026214106025
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    References listed on IDEAS

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    3. Thomas Stöckl & Jürgen Huber & Michael Kirchler, 2015. "Multi-period experimental asset markets with distinct fundamental value regimes," Experimental Economics, Springer;Economic Science Association, vol. 18(2), pages 314-334, June.
    4. Merl, Robert & Palan, Stefan & Schmidt, Dominik & Stöckl, Thomas, 2023. "Insider trading regulation and trader migration," Journal of Financial Markets, Elsevier, vol. 66(C).
    5. Ondrej Rydval, 2012. "The Causal Effect of Cognitive Abilities on Economic Behavior: Evidence from a Forecasting Task with Varying Cognitive Load," Jena Economics Research Papers 2011-064, Friedrich-Schiller-University Jena.
    6. Domonkos F. Vamossy & Rolf Skog, 2021. "EmTract: Extracting Emotions from Social Media," Papers 2112.03868, arXiv.org, revised Jun 2023.
    7. Gunduz Caginalp & David Porter & Li Hao, 2011. "Asset Market Reactions to News: An Experimental Study," Working Papers 11-15, Chapman University, Economic Science Institute.
    8. Selima Mansour & Elyès Jouini & Clotilde Napp, 2006. "Is There a “Pessimisticâ€\x9D Bias in Individual Beliefs? Evidence from a Simple Survey," Theory and Decision, Springer, vol. 61(4), pages 345-362, December.
    9. Owen Powell & Natalia Shestakova, 2017. "Experimental asset markets: behavior and bubbles," Chapters, in: Morris Altman (ed.), Handbook of Behavioural Economics and Smart Decision-Making, chapter 21, pages 375-391, Edward Elgar Publishing.
    10. repec:grz:wpsses:2021-03 is not listed on IDEAS
    11. Vandenbruaene, Jonas & De Ceuster, Marc & Annaert, Jan, 2023. "Does time series momentum also exist outside traditional financial markets? Near-laboratory evidence from sports betting," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 104(C).
    12. Lionel Page & Christoph Siemroth, 2021. "How Much Information Is Incorporated into Financial Asset Prices? Experimental Evidence," Review of Financial Studies, Society for Financial Studies, vol. 34(9), pages 4412-4449.
    13. Domonkos F. Vamossy, 2024. "Social Media Emotions and Market Behavior," Papers 2404.03792, arXiv.org.

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