Textual uncertainty in financial disclosures and information asymmetry among investors

Abstract Prior literature documents a temporary spike in information asymmetry between sophisticated and unsophisticated traders around corporate disclosures because the former process new information faster. Using advances in textual analysis, we show that when management issues more uncertain financial statements, the resulting spike in information asymmetry is significantly lower than for firms that use less uncertain text. Furthermore, textual uncertainty measures of the disclosures are negatively associated with Intermarket Sweep Order (ISO) volume, an order type commonly used by sophisticated traders. This suggests sophisticated traders and algorithms are less able to extract value‐relevant information from financial disclosures when they are uncertain.

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Publication Details

Journal
Financial Review
Published
2025-02-05
DOI
https://doi.org/10.1111/fire.12430
Primary Topic
Financial Markets and Investment Strategies
Type
article
Field-Weighted Citation Impact
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article

Textual uncertainty in financial disclosures and information asymmetry among investors

Rasheek Irtisam, Jeffrey R. Black, Pankaj K. Jain
Financial Review
Financial Markets and Investment Strategies
article

Textual uncertainty in financial disclosures and information asymmetry among investors

Rasheek Irtisam, Jeffrey R. Black, Pankaj K. Jain
article en

Abstract

Abstract Prior literature documents a temporary spike in information asymmetry between sophisticated and unsophisticated traders around corporate disclosures because the former process new information faster. Using advances in textual analysis, we show that when management issues more uncertain financial statements, the resulting spike in information asymmetry is significantly lower than for firms that use less uncertain text. Furthermore, textual uncertainty measures of the disclosures are negatively associated with Intermarket Sweep Order (ISO) volume, an order type commonly used by sophisticated traders. This suggests sophisticated traders and algorithms are less able to extract value‐relevant information from financial disclosures when they are uncertain.

Financial ReviewVol. 60(3)
Texas Tech University (US), University of Memphis (US)
Openalex Percentile: Top 97%
Financial Markets and Investment Strategies
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