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The Predictive Content of Aggregate Analyst Recommendations
Author(s) -
HOWE JOHN S.,
UNLU EMRE,
YAN XUEMIN STERLING
Publication year - 2009
Publication title -
journal of accounting research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.767
H-Index - 141
eISSN - 1475-679X
pISSN - 0021-8456
DOI - 10.1111/j.1475-679x.2009.00337.x
Subject(s) - aggregate (composite) , content (measure theory) , business , econometrics , computer science , actuarial science , economics , mathematics , materials science , composite material , mathematical analysis
Using more than 350,000 sell‐side analyst recommendations from January 1994 to August 2006, this paper examines the predictive content of aggregate analyst recommendations. We find that changes in aggregate analyst recommendations forecast future market excess returns after controlling for macroeconomic variables that have been shown to influence market returns. Similarly, changes in industry‐aggregated analyst recommendations predict future industry returns. Changes in aggregate analyst recommendations also predict one‐quarter‐ahead aggregate earnings growth. Overall, our results suggest that analyst recommendations contain market‐ and industry‐level information about future returns and earnings.