Download this Paper Open PDF in Browser

Reading the Tea Leaves: Model Uncertainty, Robust Forecasts, and the Autocorrelation of Analysts' Forecast Errors

58 Pages Posted: 28 Jan 2010 Last revised: 11 Aug 2015

Juhani T. Linnainmaa

USC Marshall School of Business; National Bureau of Economic Research (NBER)

Walter N. Torous

Massachusetts Institute of Technology

James S. Yae

University of Houston - C.T. Bauer College of Business

Date Written: August 1, 2015

Abstract

We put forward a model in which analysts are uncertain about a firm's earnings process. Faced with the possibility of using a misspecified model, analysts issue forecasts that are robust to model misspecification. We estimate that this mechanism explains approximately 60% of the autocorrelation in analysts' forecast errors. The remainder stems from the cross-sectional variation in mean forecast errors and in analysts' estimation errors of the persistence of earnings growth shocks. Consistent with our model, we find that analysts learn about some features of the earnings process but not others, and this learning reduces, but does not eliminate, the auto- correlation of forecast errors as firms age. Other potential explanations for the autocorrelation of analyst's forecast errors are rejected. Our model of robust forecasting applies not only to analysts' forecasts but to all model-based forecasts.

Keywords: Model uncertainty, parameter uncertainty, forecasting, robustness, financial analysts

JEL Classification: G14, G24

Suggested Citation

Linnainmaa, Juhani T. and Torous, Walter N. and Yae, James S., Reading the Tea Leaves: Model Uncertainty, Robust Forecasts, and the Autocorrelation of Analysts' Forecast Errors (August 1, 2015). Chicago Booth Research Paper No. 10-04; CRSP Working Paper. Available at SSRN: https://ssrn.com/abstract=1543309 or http://dx.doi.org/10.2139/ssrn.1543309

Juhani Linnainmaa (Contact Author)

USC Marshall School of Business ( email )

Marshall School of Business
Los Angeles, CA 90089
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Walter N. Torous

Massachusetts Institute of Technology ( email )

Center for Real Estate and Sloan School
Cambridge, MA 02138
United States

James Yae

University of Houston - C.T. Bauer College of Business ( email )

Houston, TX 77204-6021
United States

Paper statistics

Downloads
463
Rank
51,504
Abstract Views
2,110