The Frequency of Financial Analysts' Forecast Revisions: Theory and Evidence about Determinants of Demand for Predisclosure Information

Authors

  • Craig W. Holden,

    1. The authors are respectively from the Kelley School of Business, Indiana University and the College of Business Administration, University of Missouri at St. Louis. They thank the editor, the anonymous referees, Steve Baginski, Mark Bagnoli, Orie Barron, Walt Blacconiere, Ted Christensen, Greg Geisler, Pat Hughes, Ivo Jansen, Bob Jennings, Heejoon Kang, Steve Moehrle, Mary Beth Mohrman, Jennifer Reynolds-Moehrle, Jerry Salamon, Jerry Stern, Susan Watts, session participants at the Decision Sciences Institute Annual Meetings, the American Accounting Association Annual Meetings, the Western Finance Association, and the JFM-Yale ICF Conference, and workshop participants at Indiana University, Case Western Reserve University, and Louisiana State University for helpful comments. The authors gratefully acknowledge the contribution of I/B/E/S International Inc. for providing earnings per share forecast data, available through the Institutional Brokers' Estimate System. These data have been provided as part of a broad academic program to encourage earnings expectation research. The authors alone are responsible for any errors.
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  • Pamela S. Stuerke

    Corresponding author
    1. The authors are respectively from the Kelley School of Business, Indiana University and the College of Business Administration, University of Missouri at St. Louis. They thank the editor, the anonymous referees, Steve Baginski, Mark Bagnoli, Orie Barron, Walt Blacconiere, Ted Christensen, Greg Geisler, Pat Hughes, Ivo Jansen, Bob Jennings, Heejoon Kang, Steve Moehrle, Mary Beth Mohrman, Jennifer Reynolds-Moehrle, Jerry Salamon, Jerry Stern, Susan Watts, session participants at the Decision Sciences Institute Annual Meetings, the American Accounting Association Annual Meetings, the Western Finance Association, and the JFM-Yale ICF Conference, and workshop participants at Indiana University, Case Western Reserve University, and Louisiana State University for helpful comments. The authors gratefully acknowledge the contribution of I/B/E/S International Inc. for providing earnings per share forecast data, available through the Institutional Brokers' Estimate System. These data have been provided as part of a broad academic program to encourage earnings expectation research. The authors alone are responsible for any errors.
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* Address for correspondence: Pamela S. Stuerke, College of Business Administration, University of Missouri at St. Louis, St. Louis, MO 63121-4400, USA.
e-mail: stuerkep@umsl.edu

Abstract

Abstract:  A fundamental property of a financial market is its degree of price informativeness. A major determinant of price informativeness is predisclosure information collected by financial analysts and then privately disseminated to clients, who make the recommended trades. We develop a dynamic model of the analyst's optimal strategy of forecast revision frequency with endogenous analysts and endogenous traders. We then empirically test the model's predictions. We find that forecast revision frequency is positively associated with earnings variability, trading volume, and earnings response coefficients, and negatively associated with skewness of trading volume. Thus, we find strong empirical support for our dynamic model.

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