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

Posted: 22 Mar 2005

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

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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. In contrast, we argue that analysts likely face a linear loss function, and hence, try to minimize their absolute forecast errors. We conduct and compare rational expectations tests using these two alternative loss functions. We reproduce most prior findings of forecast inefficiency with OLS regressions, but find virtually no evidence of forecast inefficiency with Least Absolute Deviation regressions, where we explicitly assume a linear loss function.

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

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. Journal of Accounting & Economics, Vol. 38, Nos. 1-3, pp. 171-203, December 2004. Available at SSRN: https://ssrn.com/abstract=677548

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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