Understanding Analysts' Earnings Expectations: Biases, Nonlinearities and Predictability

Allan Timmermann, Marco Aiolfi and Marius Rodriguez ()

No 7656, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: This paper studies the asymmetric behavior of negative and positive values of analysts' earnings revisions and links it to the conservatism principle of accounting. Using a new three-state mixture of log-normals model that accounts for differences in the magnitude and persistence of positive, negative and zero revisions, we find evidence that revisions to analysts' earnings expectations can be predicted using publicly available information such as lagged interest rates and past revisions. We also find that our forecasts of revisions to analysts' earnings estimates help predict the actual earnings figure beyond the information contained in analysts' earnings expectations.

Keywords: Analysts' earnings forecasts; Mixture model; Predictability of forecast revisions (search for similar items in EconPapers)
JEL-codes: C22 G17 (search for similar items in EconPapers)
Date: 2010-01
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Citations: View citations in EconPapers (1)

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Journal Article: Understanding Analysts' Earnings Expectations: Biases, Nonlinearities, and Predictability (2010)
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