Billings and Jennings (2011) develop a new measure of stock price sensitivity to earnings called anticipated information content (AIC). The main difference between an AIC and an earnings response coefficient (ERC) is that AICs measure expected rather than actual sensitivity. I evaluate the AIC’s potential usefulness in future research, and conclude that AICs have several disadvantages relative to ERCs but might be useful in rare circumstances. Estimates of AICs contain considerable measurement error and fail a primary test of construct validity when left uncorrected. I outline a method for correcting two of the three sources of measurement error, which can be used by researchers interested in pursuing work on AICs. The method may have uses beyond computing AICs because it yields a prediction of the unsigned change in stock price during a scheduled event window.
Review of Accounting Studies – Springer Journals
Published: May 26, 2011
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