A Note on Analysts' Earnings Forecast Errors Distribution
Daniel A. Cohen
University of Texas at Dallas - Naveen Jindal School of Management
Thomas Z. Lys
Northwestern University - Kellogg School of Management
Journal of Accounting & Economics, Vol. 36, No. 1-3, pp. 147-164, December 2003
Abarbanell and Lehavy provide evidence that analysts' forecast errors are not normally distributed exhibiting a high occurrence of extreme negative forecast errors (left-tail asymmetry) and a high occurrence of small positive forecast errors (middle asymmetry). This is important for researchers who rely on techniques that are sensitive to the distributional assumptions of analysts' forecast errors. Many of the conclusions drawn by Abarbanell and Lehavy, however, are based on visual impressions (as opposed to formal empirical tests) or based on methods that are very sensitive to the empirical methods used (e.g., whether the serial correlation of forecast errors is caused by the left-tail asymmetry).
JEL Classification: G10, G29, M41, M43
Date posted: January 7, 2004
© 2016 Social Science Electronic Publishing, Inc. All Rights Reserved.
This page was processed by apollobot1 in 0.156 seconds