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The Accounting Review Vol. 73 No. 2 1998

Earnings predictability and bias in analysts' earnings forecasts.

Somnath Das1; Carolyn B. Levine2; K. Sivaramakrishnan3

1 University of illinois at Chicago. 1 · 2 Duke University. 2 · 3 Texas A&M University. 3

open access

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 fore- casts. 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.

DOI
10.2308/tar-542138
Volume
73
Issue
2
Pages
277-294
Language
en
Sources
crossref openalex

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