Measuring historical earnings surprises, their frequency and severity

Question

This is my first post to Quantitative Finance, so I hope my question is formatted the right way.

I am starting to research the effects of earnings surprises on certain equity indices. Is there a source, such as an academic paper or database, for:

Companies that have had a high incidence of positive and/or negative earnings surprises over the last 5 to 10 years? Statistics on the frequency and severity of earnings surprises on the day of and a few days after the event? Statistics about the medium-term performance (the following quarter, for example) of stocks with large negative or positive surprises? Industries with more earning surprises than others?

Thank you very much in advance for your help.

Answer 1

Recently I found a book on earnings trading but did not have time to read thoroughly.

Trading on Corporate Earnings News - John Shon

I also had spent some time to see earnings surprise effects and it is a quite interesting but not easy to use topic. There is certainly a jump if the estimates and announced earnings have a large mismatch but the magnitude and direction are hard to quantify.

I also recommmend Fama's efficient markets survey. It is generally about market but it also makes a point about the market's quick reaction to news such as earnings.

p.s. I used Google's returns to make a point. It is totally crazy.

Answer 2

There are many issues with doing this type of study. Will you be looking only at EPS surprises? Many times the bottom line EPS is not relevant to the earnings of the company since it contains extraordinary items. You may want to consider revenue surprises.

Investors are typically looking at a lot more than just the EPS when earnings are released. They're looking at the company's guidance for future earnings. So it's difficult to say what percentage of a stock's price movement is due to the earnings result and what percentage is reacting to the company's guidance for its future earnings potential.

StarMine (Thompson Reuters) has been following analyst estimates. With any data set of analyst estimates, you need to consider whether you'll use the mean estimate, the median estimate and whether you'll consider the range of estimates. Sometimes a star analyst's estimate carries more clout than the average of all analyst estimates. Also, sometimes investors believe the consensus estimate and sometimes there is more of a "whisper" number that is not officially publicized but generally expected. For example, people may expect a company will beat analyst estimates, yet the analysts haven't come out and increased their estimates.

You could also consider using company guidance vs. reported earnings.

Answer 3

building these statistics is just a matter of getting the right data... the actual earnings are easy to find on EDGAR... using their very friendly and fast FTP site. The estimates could take a little more work.

yahoo earnings has a few entries, but it is not very complete, and you have to crawl day by day instead of doing it by symbol... which can be a pain... msn money seems to have pretty complete info and the navigation is done by symbol so it sounds quicker, specially if you only need a few stocks and don't care about little details like the time when the reported...

http://investing.money.msn.com/investments/earnings-estimates?symbol=aapl http://biz.yahoo.com/research/earncal/today.html

once you have the data, you would need to define what a suprise is (maybe estimate a distribution of the error on the estimate and get those that are more than 2 std from the mean?) and voila! you have your event. At that point you just need to get daily stock prices and see the moves in the days after each event.

last step is, once you have your results, share them back with the community by uploading them to quandl :)