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Pervasive underreaction: Evidence from high-frequency data

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  • Jiang, Hao
  • Li, Sophia Zhengzi
  • Wang, Hao

Abstract

We propose a novel high-frequency decomposition of daily stock returns into news- and non-news-driven components, and uncover evidence of pervasive stock market underreaction to firm news. Prices tend to drift in the same direction as the initial market response for several days after the news arrival without reversals. A trading strategy exploiting the return drift generates high abnormal returns and remains profitable after transaction costs. To understand the economic mechanism, we find that the return drift is stronger when investors are distracted. Analysts’ slow adjustments of market expectations following firm news also contribute to the market underreaction.

Suggested Citation

  • Jiang, Hao & Li, Sophia Zhengzi & Wang, Hao, 2021. "Pervasive underreaction: Evidence from high-frequency data," Journal of Financial Economics, Elsevier, vol. 141(2), pages 573-599.
    • Handle: RePEc:eee:jfinec:v:141:y:2021:i:2:p:573-599
    DOI: 10.1016/j.jfineco.2021.04.003
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    8. Rick Steinert & Saskia Altmann, 2023. "Linking microblogging sentiments to stock price movement: An application of GPT-4," Papers 2308.16771, arXiv.org.
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    More about this item

    Keywords

    Underreaction; High-frequency; News; Attention; Expectation formation;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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