Are aggregate corporate earnings forecasts unbiased and efficient?

Are aggregate corporate earnings forecasts unbiased and efficient? In this article, we analyze the properties of professional aggregate corporate earnings forecasts with regards to accuracy, unbiasedness, and efficiency. Using a large panel of forecasts for the years 1992–2011, we find that forecast errors are in general large, and the magnitude of forecast errors varies substantially across forecasters. Forecasts are however directionally accurate, especially during periods of slowdown. We find evidence of an underprediction bias, as forecasters failed to predict the strong growth of corporate earnings that took place over the past two decades. Forecasts biases and forecast errors are particularly large during periods of economic instability such as recession years, suggesting that biases originate in forecasters’ slow adjustment to structural shocks. Finally, we reject forecast efficiency, and find evidence of overreaction to new information, as evidenced by the negative autocorrelation of forecast revisions. Forecasters overreact equally strongly to good and bad aggregate earnings news, resulting in excessive forecast volatility. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Quantitative Finance and Accounting Springer Journals

Are aggregate corporate earnings forecasts unbiased and efficient?

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Publisher
Springer US
Copyright
Copyright © 2014 by Springer Science+Business Media New York
Subject
Economics / Management Science; Finance/Investment/Banking; Accounting/Auditing; Econometrics; Operations Research/Decision Theory
ISSN
0924-865X
eISSN
1573-7179
D.O.I.
10.1007/s11156-014-0456-2
Publisher site
See Article on Publisher Site

Abstract

In this article, we analyze the properties of professional aggregate corporate earnings forecasts with regards to accuracy, unbiasedness, and efficiency. Using a large panel of forecasts for the years 1992–2011, we find that forecast errors are in general large, and the magnitude of forecast errors varies substantially across forecasters. Forecasts are however directionally accurate, especially during periods of slowdown. We find evidence of an underprediction bias, as forecasters failed to predict the strong growth of corporate earnings that took place over the past two decades. Forecasts biases and forecast errors are particularly large during periods of economic instability such as recession years, suggesting that biases originate in forecasters’ slow adjustment to structural shocks. Finally, we reject forecast efficiency, and find evidence of overreaction to new information, as evidenced by the negative autocorrelation of forecast revisions. Forecasters overreact equally strongly to good and bad aggregate earnings news, resulting in excessive forecast volatility.

Journal

Review of Quantitative Finance and AccountingSpringer Journals

Published: May 16, 2014

References

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