Earnings Predictability and Bias in Analysts? Earnings Forecasts

Posted: 3 Aug 1998

See all articles by Somnath Das

Somnath Das

University of Illinois at Chicago

Carolyn B. Levine

Carnegie Mellon University - David A. Tepper School of Business

Shiva Sivaramakrishnan

Rice University

Abstract

This paper examines cross-sectional differences in the optimistic behavior of financial analysts. Specifically, we investigate whether the predictive accuracy of past information (e.g., time-series of earnings, past returns, etc.) is associated with the magnitude of the bias in analysts' earnings forecasts. We posit that there is higher demand for non-public information for firms whose earnings are difficult to accurately predict than for firms whose earnings can be accurately forecasted using public information. Assuming that optimism facilitates access to management's non-public information, we hypothesize that analysts will issue more optimistic forecasts for low predictability firms than for high predictability firms. Our results support this hypothesis.

JEL Classification: G29, M41

Suggested Citation

Das, Somnath and Levine, Carolyn B. and Sivaramakrishnan, Shiva, Earnings Predictability and Bias in Analysts? Earnings Forecasts. The Accounting Review, Vol 73, No 2, April 1998, Available at SSRN: https://ssrn.com/abstract=112208

Somnath Das (Contact Author)

University of Illinois at Chicago ( email )

601 South Morgan Street
University Hall, Room 2303
Chicago, IL 60607
United States
312-996-4482 (Phone)
312-996-4520 (Fax)

Carolyn B. Levine

Carnegie Mellon University - David A. Tepper School of Business ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213-3890
United States

Shiva Sivaramakrishnan

Rice University ( email )

6100 South Main Street
Houston, TX 77005-1892
United States

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