This is not a misprint. It’s not a mistake. And it’s not
voodoo. You pick a month, any month, and Steve Heston, associate professor of
finance, can predict which stocks are going to do better than the market in that
Sound crazy? Heston thought so too. But it turns out that
stocks with high historical returns in a particular calendar month tend to have
high future returns in that same calendar month in succeeding years. If a stock
did well one February or July or October, for example, it tended to do well in
February, July or October of future years.
These results—which arose from a study Heston was
conducting on seasonality in the stock market—were so unexpected that when
Heston first saw them he was convinced they were caused by a programming error.
He called his collaborater, Ronnie Sadka of the University of Washington, to ask
him to write the code from scratch and re-run the data. Sadka got the same
results, but Heston still wasn’t quite convinced. Could they have made the same
mistake, he wondered? Because this couldn’t be real. Could it?
“People have been looking for predictability in the stock
market for so long, and finding, if any evidence, very weak evidence,” says
Heston. “And suddenly we were finding that we could predict returns very easily
using almost astrological methods.”
Seasonality in the economy is an old idea. It’s no surprise
that retail sales go up in November for Christmas, or that snow tires sell
better in October than in May.
Seasonality in the stock market has also been explored
before—historically, the stock market has gone up more in January than in other
months, a phenomenon known as the January effect.
One interesting facet of the monthly seasonal effect
identified by Heston is that it doesn’t fade over time, holding true for the
entire 20-year time period Heston studied. And it didn’t matter what industry
Heston looked at, how big the company was or when it published its earnings
report—buying or selling stock based on its performance in that same month in
previous years was a winning strategy.
So what’s going on here? Heston’s not sure yet, but when his paper describing
the study comes out in the Journal of Financial
Economics, it is bound to spark a whole new stream of research
aimed at finding out exactly what is driving this seasonal effect.
In the meantime, is it possible to design an investing
strategy that takes advantage of this monthly seasonal variation? Sure, says
Heston. While it may not be financially advantageous to rebalance your portfolio
every month, seasonal variation may be a good way to decide what to sell when,
even if you’re only doing so occasionally.
“Buying and selling stocks is expensive. But imagine you
have a portfolio of stocks and you’re going to sell some for your retirement, or
to fund your child’s college education,” says Heston. “Some of those stocks went
up a lot last October. You won’t want to sell those in September, because
historically they will do well in October. Rather, you’d sell stocks that
historically do poorly in October. If you’re going to pay a brokerage fee, you’d
rather pay a brokerage fee to sell stocks that are likely to go down in value
“Seasonality in the Cross-Section of Expected Stock Returns” is forthcoming
from the Journal of Financial Economics. For more information about this research, contact