Textual classification of SEC comment letters

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
Subject Areas: Accounting
Additional Information:

© 2020 Springer Nature

This is a post-peer-review, pre-copyedit version of an article published in Review of Accounting Studies. The final authenticated version is available online at: https://dx.doi.org/10.1007/s11142-020-09565-6

Date Deposited: 11 Nov 2019 13:11
Date of first compliant deposit: 08 Nov 2019
Subjects: S > Statistical classifications
F > Financial reporting
S > Statistical analysis
Last Modified: 20 Sep 2021 00:21
URI: https://lbsresearch.london.edu/id/eprint/1268
More

Export and Share


Download

Accepted Version - Text
  • Restricted to Repository staff only

Statistics

Altmetrics
View details on Dimensions' website

Downloads from LBS Research Online

View details

Actions (login required)

Edit Item Edit Item