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.
Review of Quantitative Finance and Accounting – Springer Journals
Published: May 16, 2014
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera