Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/314274 
Year of Publication: 
2024
Citation: 
[Journal:] Journal of Applied Economics [ISSN:] 1667-6726 [Volume:] 27 [Issue:] 1 [Article No.:] 2354641 [Year:] 2024 [Pages:] 1-19
Publisher: 
Taylor & Francis, Abingdon
Abstract: 
By utilizing web-crawling and text analysis techniques on unstructured big data (text sets), this study examines to what extent investors disagree with the sentiment conveyed in annual reports. The main empirical findings suggest that the tone of annual reports significantly influences investor opinions. Specifically, a negative tone in annual reports is associated with high levels of divergence among investors' opinions, whereas a positive tone correlates with lower divergence. In the robustness tests, the results remain consistent after controlling for various factors. After we control for Management Discussion and Analysis (MD&A), both positive and negative tones in annual reports continue to be significant predictors of divergences in investor opinions. Additionally, after controlling for future earnings quality, future cash flows, and future earnings surprises, investors still present high/low divergence of opinion in response to a negative/positive tone in annual reports. Moreover, the robustness of our analysis is assessed by employing alternative sentiment analysis word lists.
Subjects: 
corporate disclosure tone
Divergence of opinion
textual analysis
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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