Research

The Predictive Content of Aggregate Analyst Recommendations

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

strong evidence that aggregate changes in analyst recommendations forecast future market

excess returns, suggesting that analyst recommendations contain market-level information not

yet incorporated into market prices. Our results remain significant after controlling for

macroeconomic variables that have been shown to influence market returns. A simple trading

strategy based on lagged aggregate analyst recommendations yields an abnormal return of

approximately 1% per quarter. Our results are not attributable to the implementation of NASD

Rule 2711, nor are they driven by a small-sample bias. Further, changes in industry-aggregated

analyst recommendations predict future industry returns. Overall, our findings suggest that

analyst recommendations contain valuable market-level and industry-level information.

Publication Information
Article Title: The Predictive Content of Aggregate Analyst Recommendations
Journal: Journal of Accounting Research (Oct, 2007)
Author(s): Howe, John S.;  Unlu, Emre;  Yan, Xuemin (Sterling)
Researcher Information
    
Unlu, Emre
Unlu, Emre
Executive Director of Executive Education
Expertise:
  • Corporate Finance
Finance
CoB 201 H
P.O. Box 880490
University of Nebraska-Lincoln
Lincoln, NE 68588-0490, USA
Phone: (402) 472-2353
emre@unl.edu