Extreme Categories and Overreaction to News.

What characteristics of news generate over-or-underreaction? We study the asset-pricing consequences of diagnostic expectations, a model of belief formation based on the representativeness heuristic, in a setting where news events are drawn from categories with extreme distributions of fundamentals....

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Publicado en:Review of Economic Studies Vol. 93; no. 2; pp. 1137 - 1167
Autores principales: Kwon, Spencer Y, Tang, Johnny
Formato: Artículo
Publicado: Oxford University Press / USA Mar2026
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Mar2026
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          Kwon, Spencer Y
          Tang, Johnny
        affil:
          Brown University, USA
          Cornell University, USA
      su:
        Heuristic
        Investors
        Outliers (Statistics)
        Announcements
        Prices of securities
        Investment risk
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          Heuristic
          Investors
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          Investment Banking and Securities Dealing
          Outliers (Statistics)
          Announcements
          Prices of securities
          Investment risk
      keyword:
        Asset pricing
        Behavioural finance
        copyrightHolder:Review of Economic Studies Ltd
        copyrightYear:2026
        inLanguage:en
        Overreaction
        publisher:Oxford University Press
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        Underreaction
        Asset pricing
        Behavioural finance
        copyrightHolder:Review of Economic Studies Ltd
        copyrightYear:2026
        inLanguage:en
        Overreaction
        publisher:Oxford University Press
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        Underreaction
      ab: What characteristics of news generate over-or-underreaction? We study the asset-pricing consequences of diagnostic expectations, a model of belief formation based on the representativeness heuristic, in a setting where news events are drawn from categories with extreme distributions of fundamentals. Our model predicts greater overreaction to news belonging to categories with more extreme outliers, or tail events. We test our theory on a comprehensive database of corporate news that includes news from twenty-four different categories, including earnings announcements, product launches, mergers and acquisition, business expansions, and client-related news. We find theory-consistent heterogeneity in investor reaction to news, with more overreaction in the form of greater post-announcement return reversals and trading volume for news categories with more extreme distributions of fundamentals.
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