Loss Function Assumptions in Rational Expectations Tests on Financial Analysts' Earnings Forecasts

Emory University Working Paper

40 Pages Posted: 9 Apr 2003

See all articles by Sudipta Basu

Sudipta Basu

Temple University - Department of Accounting

Stanimir Markov

University of Texas at Dallas - Naveen Jindal School of Management

Multiple version iconThere are 2 versions of this paper

Date Written: February 26, 2002

Abstract

Prior research concludes that financial analysts do not process public information efficiently in generating their earnings forecasts. The OLS regression-based tests used in prior studies assume implicitly that analysts face a quadratic loss function, or that analysts minimize their squared forecast errors. In contrast, we argue that analysts face a linear loss function, or that they minimize their absolute forecast errors. We conduct and compare rational expectations tests conditioned on these two alternative loss functions. While we replicate prior findings of inefficiency with OLS regressions, we find virtually no evidence of forecast inefficiency with Least Absolute Deviation regressions, where we explicitly assume a linear loss function.

Keywords: unbiased, economic significance, analyst rankings, conditional median, performance evaluation

JEL Classification: G10, G29, M41, D84

Suggested Citation

Basu, Sudipta and Markov, Stanimir, Loss Function Assumptions in Rational Expectations Tests on Financial Analysts' Earnings Forecasts (February 26, 2002). Emory University Working Paper. Available at SSRN: https://ssrn.com/abstract=384597 or http://dx.doi.org/10.2139/ssrn.384597

Sudipta Basu

Temple University - Department of Accounting ( email )

Philadelphia, PA 19122
United States
215.204.0489 (Phone)
215.204.5587 (Fax)

Stanimir Markov (Contact Author)

University of Texas at Dallas - Naveen Jindal School of Management ( email )

P.O. Box 830688
Richardson, TX 75083-0688
United States
972 883 5166 (Phone)

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