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Erschienen in: Review of Accounting Studies 1/2021

24.11.2020

Textual classification of SEC comment letters

verfasst von: James P. Ryans

Erschienen in: Review of Accounting Studies | Ausgabe 1/2021

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Abstract

This study examines the impact of SEC comment letters on future financial reporting outcomes and earnings credibility. Naïve Bayesian classification identifies comment letters associated with future restatements and write-downs. An investor attention-based quantitative measure of importance, using EDGAR downloads, also predicts 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 that draw investor attention and that relate to future restatements and write-downs. Innocuous comment letters are associated with improvements in earnings credibility following comment letter reviews.

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Fußnoten
1
Examples of short seller research that uses issues raised in comment letters include presentations by Greenlight Capital on Green Mountain Coffee, Pershing Square on Herbalife, and Prescience Point on Boulder Brands. http://​online.​wsj.​com/​public/​resources/​documents/​EinhornGMCRprese​ntation_​Oct2011_​VIC.​pdf. Retrieved 7 September, 2020.http://​factsabout-herbalife.​com/​wp-content/​uploads/​2013/​01/​Who-wants-to-be-a-Millionaire.​pdf. Retrieved 1 February 2013.https://​www.​presciencepoint.​com/​research/​research-archives/​boulder-brands-inc-bdbd/​. Retrieved 7 September, 2020.
 
2
Care needs to be taking cleaning the raw EDGAR log file data set to accurately count comment letter downloads, which are usually filed as PDF documents. Ryans, J., 2017. Using the EDGAR log file data set. Working paper, London Business School.
 
3
As described previously, the use of multi-word features such as bigrams, which are used in this study, can allow for some preservation of word order in naïve Bayesian analysis.
 
4
See Securities and Exchange Commission. Staff Observations in the Review of Executive Compensation Disclosure. September 10, 2007. http://www.sec.gov/divisions/corpfin/guidance/execcompdisclosu​re.​htm. Accessed 7 September 2020.
 
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Metadaten
Titel
Textual classification of SEC comment letters
verfasst von
James P. Ryans
Publikationsdatum
24.11.2020
Verlag
Springer US
Erschienen in
Review of Accounting Studies / Ausgabe 1/2021
Print ISSN: 1380-6653
Elektronische ISSN: 1573-7136
DOI
https://doi.org/10.1007/s11142-020-09565-6

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