Understanding Analysts’ Earnings Expectations: Biases, Nonlinearities and Predictability∗

Financial analysts’ earnings forecasts are a key determinant of stock prices and understanding how these forecasts evolve over time is important. 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−which under conventional assumptions should follow a martingale difference process−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 estimate help predict the actual earnings figure beyond the information contained in analysts’ earnings expectations. ∗We are grateful to the editor, Rene Garcia, an associate editor and an anonymous referee for comments on an earlier draft. Participants at the 2008 SoFie conference at New York University provided helpful comments on the paper. †The views, thoughts and opinions expressed in this paper are those of the authors in their individual capacity and should not in any way be attributed to Platinum Grove Asset Management LP or to Marco Aiolfi as a representative officer, or employee of Platinum Grove Asset Management LP. ‡The opinions herein are our own, and do not reflect the views of the Board of Governors of the Federal Reserve System. Corresponding Author: [email protected]