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

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.

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Bibliographic details
Volume: 48
Main Author: LI, FENG
Format: Journal Article
Language: English
Zielgruppe: Academic
Place of publication: Malden, USA Blackwell Publishing Inc 01.12.2010
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published in: Journal of accounting research Vol. 48; no. 5; pp. 1049 - 1102
Edition: Received 14 January 2009; accepted 8 June 2010
Data of publication: 2010-12
ISSN: 0021-8456
EISSN: 1475-679X
Discipline: Business
Bibliography: I would like to thank Phil Berger, Dave Burgstahler, John Core, Ilia Dichev, Weili Ge, Leslie Hodder, Jack Hughes, Raffi Indjejikian, Mark Lang, Dave Larcker, Charles Lee, Roby Lehavy, Russell Lundholm, Dawn Matsumoto, Brian P. Miller, Venky Nagar, Marlene Plumlee, Grace Powell, Jonathan Rogers, Haresh Sapra, Cathy Shakespeare, Terry Shevlin, Doug Skinner, Abbie Smith, K. R. Subramanyam, Brett Trueman, Jenny Tucker, Regina Wittenberg Moerman, Sarah Zechman, the participants of the 2008 University of Michigan Traverse City Conference, the 2008 North American Summer Meeting of the Econometric Society, the 2009 FARS mid‐year conference, the New York University 2009 Summer Camp, and the Deutsche Bank Asset Management seminar, and the workshop participants at Chicago, Notre Dame, University of Washington, UCLA, Indiana, Florida, Emory, and Stanford for their helpful comments and Julie Miller for her editorial help. Special thanks go to Merle Erickson (the editor) and an anonymous reviewer. I also thank Mike Chen, Qian Fang, Qian Li, Chris Liong, Doris Lu, Amy McMahon, Bharat Modi, Qimin Ni, Darin Styles, Kathy Wang, Tina Wei, Sarah Xia, Quan Yuan, and especially Rencheng Wang and Winnie Wei for their excellent research assistance and Ernst, and Young Faculty Development Fund and the Harry Jones Endowment for Earnings Quality at the University of Michigan for financial support.
Series: Journal of Accounting Research
Online Access: Fulltext
Database: Istex
Web of Knowledge
Social Sciences Citation Index
Web of Science
Web of Science - Social Sciences Citation Index - 2010
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