ANALYST CHARACTERISTICS AND EARNINGS FORECAST ERRORS

Author: 
File(s): 
Peer reviewed: 
No, item is not peer reviewed.
Scholarly level: 
Graduate student (Masters)
Date created: 
2017-12
Supervisor(s): 
Amir Rubin
Department: 
Beedie School of Business-Segal Graduate School
Keywords: 
analyst
characteristics
forecast errors
Abstract: 

In this article, we investigate the association between analysts’ earnings forecast errors and analyst characteristics. These characteristics include working experience, company experience, brokerage house size, and boldness in making recommendations. We use t-tests and time-series regressions to examine the relationship. Our results reveal that analysts’ years of experience is the most important factor. The more experience analysts have, the more accurate their forecasts tend to be, which is consistent with the learning-by-doing theory. For the brokerage house size, analysts from larger brokerage houses are more likely to provide accurate forecasts. For boldness, when an analyst’s recommendation is far away from mean recommendation, the earnings forecast tends to be less accurate. Company-specific experience has no robust relation with forecast errors. We conclude that experience of analysts, brokerage size, and analysts’ recommendation dispersion are correlated with forecast accuracy.

Description: 

MSc in Finance Project-Simon Fraser University.

Language: 
English
Document type: 
Graduating extended essay / Research project
Rights: 
Copyright remains with the author.
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