Predictability in Financial Analyst Forecast Errors: Learning or Irrationality?
In this paper, we propose a rational learning-based explanation for the predictability in financial analysts' earnings forecast errors documented in prior literature. In particular, we argue that the serial correlation pattern in analysts' quarterly earnings forecast errors is consistent with an environment in which analysts face parameter uncertainty and learn rationally about the parameters over time. Using simulations and real data, we show that the predictability evidence is more consistent with rational learning than with irrationality (fixation on a seasonal random walk model or some other dogmatic belief). Copyright University of Chicago on behalf of the Institute of Professional Accounting, 2006.
Year of publication: |
2006
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Authors: | MARKOV, STANIMIR ; TAMAYO, ANE |
Published in: |
Journal of Accounting Research. - Wiley Blackwell, ISSN 0021-8456. - Vol. 44.2006, 4, p. 725-761
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Publisher: |
Wiley Blackwell |
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