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Understanding Analysts' Earnings Expectations: Biases, Nonlinearities, and Predictability

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  • Marco Aiolfi
  • Marius Rodriguez
  • Allan Timmermann

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 lognormal models 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 to predict the actual earnings figure beyond the information contained in analysts' earnings expectations. Copyright The Author 2009. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.

Suggested Citation

  • Marco Aiolfi & Marius Rodriguez & Allan Timmermann, 2010. "Understanding Analysts' Earnings Expectations: Biases, Nonlinearities, and Predictability," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 8(3), pages 305-334, Summer.
  • Handle: RePEc:oup:jfinec:v:8:y:2010:i:3:p:305-334
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    References listed on IDEAS

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    Cited by:

    1. Baghestani, Hamid & Khallaf, Ashraf, 2012. "Predictions of growth in U.S. corporate profits: Asymmetric vs. symmetric loss," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 222-229.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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