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Predicting Stock Market Returns Based on the Content of Annual Report Narrative: A New Anomaly

Author

Listed:
  • Wisniewski, Tomasz Piotr
  • Yekini, Liafisu Sina

Abstract

This paper uses the tools of computational linguistics to analyze the qualitative part of the annual reports of UK listed companies. More specifically, the frequency of words associated with praise, concreteness and activity is measured and used to forecast future stock returns. We find that our language indicators predict subsequent price increases, even after controlling for a wide range of factors. Elevated values of the linguistic variables, however, are not symptomatic of exacerbated risk. Consequently, investors are advised to peruse the annual report narrative, as it contains valuable information that may still not have been discounted in the prices.

Suggested Citation

  • Wisniewski, Tomasz Piotr & Yekini, Liafisu Sina, 2014. "Predicting Stock Market Returns Based on the Content of Annual Report Narrative: A New Anomaly," MPRA Paper 58107, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:58107
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    References listed on IDEAS

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    More about this item

    Keywords

    Content Analysis; Annual Reports; Stock Market Returns;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting

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