Financial Analyst Characteristics and Herding Behavior in Forecasting

Financial Analyst Characteristics and Herding Behavior in Forecasting

This study classifies analysts' earnings forecasts as herding or bold and finds that (1) boldness likelihood increases with the analyst's prior accuracy, brokerage size, and experience and declines with the number of industries the analyst follows, consistent with theory linking boldness w...

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Bibliographic Details
Published in:The Journal of finance (New York) Vol. 60; no. 1; pp. 307 - 341
Main Authors: CLEMENT, MICHAEL B., TSE, SENYO Y.
Format: Journal Article
Language:English
Published: 350 Main Street , Malden , MA 02148 , USA , and 9600 Garsington Road , Oxford OX4 2DQ , UK Blackwell Publishing, Inc 01-02-2005
Blackwell Publishers
Blackwell Publishers Inc
Subjects:
Analysts
Analytical forecasting
Brokerage industry
Brokerages
Earnings forecasting
Economic behaviour
Economic forecasts
Economic models
Error
Finance
Financial analysis
Financial economics
Forecasting models
Herding
Industry analysis
Investment
Investors
Mathematical models
Modeling
Regression analysis
Securities industry
Studies
Variable coefficients
United States > US
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Summary:This study classifies analysts' earnings forecasts as herding or bold and finds that (1) boldness likelihood increases with the analyst's prior accuracy, brokerage size, and experience and declines with the number of industries the analyst follows, consistent with theory linking boldness with career concerns and ability; (2) bold forecasts are more accurate than herding forecasts; and (3) herding forecast revisions are more strongly associated with analysts' earnings forecast errors (actual earnings-forecast) than are bold forecast revisions. Thus, bold forecasts incorporate analysts' private information more completely and provide more relevant information to investors than herding forecasts.
Bibliography:ArticleID:JOFI731
istex:327BE572390EAB33B36CEA30D1742F95488332E3
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Both authors are with The University of Texas at Austin. We are grateful to an anonymous reviewer and to Rick Green, the editor, for key suggestions. We also received useful comments from Rowland Atiase, Robert Freeman, Ross Jennings, Bill Mayew, seminar participants at Texas A&M University and the University of Texas at Austin, and especially Linda Bamber. Any remaining errors are ours. We gratefully acknowledge the assistance of I/B/E/S in providing earnings per share forecast data as part of a broad academic program to encourage earnings expectation research.
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ISSN:0022-1082
1540-6261
DOI:10.1111/j.1540-6261.2005.00731.x