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Disagreement after News: Gradual Information Diffusion or Differences of Opinion?

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  • Anastassia Fedyk

    (Harvard Business School)

Abstract

This paper explores the long-standing empirical fact of increased trading volume around news releases through the lens of canonical models of gradual information diffusion and differences of opinion. I use a unique dataset of clicks on news by key finance professionals to distinguish between trading among investors who see the news at different times and trading among investors who see the same news but disagree regarding its interpretation. Consistent with gradual information diffusion, dispersion in the timing of investors' attention is strongly predictive of daily volume around earnings announcements and volume within minutes of individual news articles. Furthermore, delayed attention is predictive of minute-level return continuation, daily-level post-earnings-announcement drift, and monthly-level return momentum. Differences of opinion, measured as heterogeneity in the investors clicking on the news, are generally weaker in explaining trading volume around news, but plays a larger role when the news is more textually ambiguous.

Suggested Citation

  • Anastassia Fedyk, 2018. "Disagreement after News: Gradual Information Diffusion or Differences of Opinion?," 2018 Meeting Papers 1095, Society for Economic Dynamics.
    • Handle: RePEc:red:sed018:1095
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    References listed on IDEAS

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