Understanding Analysts' Earnings Expectations: Biases, Nonlinearities and Predictability

40 Pages Posted: 8 Feb 2010

See all articles by Marco Aiolfi

Marco Aiolfi

QMA

Marius Rodriguez

Board of Governors of the Federal Reserve System

Allan Timmermann

UCSD ; Centre for Economic Policy Research (CEPR)

Date Written: January 2010

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

JEL Classification: C22, G17

Suggested Citation

Aiolfi, Marco and Rodriguez, Marius and Timmermann, Allan, Understanding Analysts' Earnings Expectations: Biases, Nonlinearities and Predictability (January 2010). CEPR Discussion Paper No. DP7656. Available at SSRN: https://ssrn.com/abstract=1547576

Marco Aiolfi (Contact Author)

QMA ( email )

100 Mulberry Street
Gateway Center 2
Newark, NJ 07102
United States

Marius Rodriguez

Board of Governors of the Federal Reserve System ( email )

20th St. and Constitution Ave.
Washington, DC 20551
United States

Allan Timmermann

UCSD ( email )

9500 Gilman Drive
La Jolla, CA 92093-0553
United States
858-534-0894 (Phone)

HOME PAGE: http://rady.ucsd.edu/people/faculty/timmermann/

Centre for Economic Policy Research (CEPR)

London
United Kingdom

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