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Ambiguous Text

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  • Eric Tham

Abstract

Investors infer ambiguity from text in news and social media. A proxy for information ambiguity is developed from text processing and used in regression tests against the S&P 500 returns. A risk-neutral agent model with uniform prior beliefs is developed to explain the ambiguity premium or discount under unfavorable or favorable market conditions agnostic of the ambiguity preferences. The model postulates that the ambiguity premium is often elusive in efficient markets due to returns unpredictability, and the information ambiguity as an omitted variable bias in the fundamental relationship between risks and returns. Empirically, the author finds that news media drives equity prices more than social media except from June 2009 to November 2016.

Suggested Citation

  • Eric Tham, 2023. "Ambiguous Text," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 24(4), pages 466-478, October.
    • Handle: RePEc:taf:hbhfxx:v:24:y:2023:i:4:p:466-478
    DOI: 10.1080/15427560.2022.2037600
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