Ryans, J (2021) Textual classification of SEC comment letters. Review of Accounting Studies, 26. pp. 37-80. ISSN 1380-6653
Abstract
This study examines the impact of SEC comment letters on future financial reporting outcomes and earnings credibility. Naive Bayesian classification identifies comment letters associated with future restatements and write-downs. An investor attention-based quantitative measure of importance, using EDGAR downloads, is also predictive of these outcomes. Disclosure-event abnormal returns, revenue recognition comments, and the number of letters in a conversation appear to be useful quantitative metrics for classifying importance in certain settings. This study also documents trends in comment letter topics over time, and identifies topics associated with the textual and quantitative classifications of importance, providing insights into the factors drawing investor attention and which relate to future restatements and write-downs. Innocuous comment letters are associated with improvements in earnings credibility following comment letter reviews.
More Details
Item Type: | Article |
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Subject Areas: | Accounting |
Additional Information: |
© 2020 Springer Nature
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Date Deposited: | 11 Nov 2019 13:11 |
Date of first compliant deposit: | 08 Nov 2019 |
Subjects: |
Statistical classifications Financial reporting Statistical analysis |
Last Modified: | 14 Oct 2024 14:40 |
URI: | https://lbsresearch.london.edu/id/eprint/1268 |