The Predictive Content of Aggregate Analyst Recommendations
John S. Howe
University of Missouri at Columbia - Department of Finance
Xuemin Sterling Yan
University of Missouri - Columbia
University of Nebraska at Lincoln
AFA 2007 Chicago Meetings Paper
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.
Number of Pages in PDF File: 44
Keywords: analyst recommendation, predictability, market returns
JEL Classification: G14, M41working papers series
Date posted: March 8, 2006 ; Last revised: April 13, 2008
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