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Rationality and Analysts' Forecast Bias Author info | Abstract | Publisher info | Download info | Related research | Statistics Terence Lim
This paper proposes and tests a quadratic-loss 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. Copyright The American Finance Association 2001.
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Article provided by American Finance Association in its journal The Journal of Finance .
Volume (Year): 56 (2001)
Issue (Month): 1 (02)
Pages: 369-385
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Handle: RePEc:bla:jfinan:v:56:y:2001:i:1:p:369-385Contact details of provider: Web page: http://www.afajof.org/ More information through EDIRC
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