The Information Content of Forward‐Looking Statements in Corporate Filings—A Naïve Bayesian Machine Learning Approach

Feng Li

Journal of Accounting Research, 2010, vol. 48, issue 5, 1049-1102

Abstract: This paper examines the information content of the forward‐looking statements (FLS) in the Management Discussion and Analysis section (MD&A) of 10‐K and 10‐Q filings using a Naïve Bayesian machine learning algorithm. I find that firms with better current performance, lower accruals, smaller size, lower market‐to‐book ratio, less return volatility, lower MD&A Fog index, and longer history tend to have more positive FLSs. The average tone of the FLS is positively associated with future earnings even after controlling for other determinants of future performance. The results also show that, despite increased regulations aimed at strengthening MD&A disclosures, there is no systematic change in the information content of MD&As over time. In addition, the tone in MD&As seems to mitigate the mispricing of accruals. When managers “warn” about the future performance implications of accruals (i.e., the MD&A tone is positive (negative) when accruals are negative (positive)), accruals are not associated with future returns. The tone measures based on three commonly used dictionaries (Diction, General Inquirer, and the Linguistic Inquiry and Word Count) do not positively predict future performance. This result suggests that these dictionaries might not work well for analyzing corporate filings.

Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (230)

Downloads: (external link)
https://doi.org/10.1111/j.1475-679X.2010.00382.x

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:joares:v:48:y:2010:i:5:p:1049-1102

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0021-8456

Access Statistics for this article

Journal of Accounting Research is currently edited by Philip G. Berger, Luzi Hail, Christian Leuz, Haresh Sapra, Douglas J. Skinner, Rodrigo Verdi and Regina Wittenberg Moerman

More articles in Journal of Accounting Research from Wiley Blackwell
Bibliographic data for series maintained by Wiley Content Delivery ().