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Rationality and Analysts' Forecast Bias

Rationality and Analysts' Forecast Bias ABSTRACT This paper proposes and tests a quadratic‐loos utility function for modeling corporate earnings forecasting, where financial analysts trade off bias to improve management access and forecast accuracy. Optimal forecasts with minimum expected error are optimistically biased and exhibit predictable cross‐sectional variation related to analyst and company characteristics. Empirical evidence from individual analyst forecasts is consistent with the model's predictions. These results suggest that positive and predictable bias may be a rational property of optimal earnings forecasts. Prior studies using classical notions of unbiasedness may have prematurely dismissed analysts' forecasts as being irrational or inaccurate. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Journal of Finance Wiley

Rationality and Analysts' Forecast Bias

The Journal of Finance , Volume 56 (1) – Feb 1, 2001

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References (31)

Publisher
Wiley
Copyright
© American Finance Association
ISSN
0022-1082
eISSN
1540-6261
DOI
10.1111/0022-1082.00329
Publisher site
See Article on Publisher Site

Abstract

ABSTRACT This paper proposes and tests a quadratic‐loos utility function for modeling corporate earnings forecasting, where financial analysts trade off bias to improve management access and forecast accuracy. Optimal forecasts with minimum expected error are optimistically biased and exhibit predictable cross‐sectional variation related to analyst and company characteristics. Empirical evidence from individual analyst forecasts is consistent with the model's predictions. These results suggest that positive and predictable bias may be a rational property of optimal earnings forecasts. Prior studies using classical notions of unbiasedness may have prematurely dismissed analysts' forecasts as being irrational or inaccurate.

Journal

The Journal of FinanceWiley

Published: Feb 1, 2001

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