Sell in September? Time for Reality!

Anyone paying attention to market news must know that September is the weakest month for stocks.  Mark Hulbert, one of our favorite writers, calls it The Cruelest Month.  He provides a table of returns, summarized as follows:

Notice from the table that in all but one of the last 11 decades,
September was a below-average performer. In more than half the decades,
in fact, the month’s rank was dead last.

Why, given such an overwhelming record, would anyone question
September’s bad record? Because there is no good theory for why the
month should be such an awful month for the stock market. And, without
such an explanation, there’s the distinct possibility that the
statistical pattern is just a fluke.

As one can see, Hulbert is well aware of data mining.  He mentions the popular “butter production in Bangladesh” example.

Hulbert next considers a number of hypotheses and invites readers to share their own ideas.  His thought is that a good explanation would make the September story more convincing, although he shares the information that day traders do not wait for any hypothesis testing!  The sophisticated audience of “A Dash” may not find that very convincing.

Hulbert’s Market Watch colleague, Irwin Kellner, has a number of reasons for September weakness, including the possibility of a self-fulfilling prophecy.

Why Both Articles are Wrong

Here at “A Dash” we are veteran debunkers of mythical market lore.  Most people (including our employers when we started in the business) just want to see the data — all of it!  Traders all believe in patterns.  The more data the better.

The idea of random results is lost on most, like the “day traders” Hulbert mentions.  There are twelve months.  There will be a distribution.  Some will be good and others will be bad.  Always.

What if there is a reason?  A hypothesis does not really help.  When you already know the outcome, any smart person can invent a compelling reason.  New readers can revisit our discussion of this topic, where a group of very smart grad students were given a list of findings and asked to provide reasons.  They did very well.  Only after the class were they told that all of the relationships were reversed!

The scientific method works only when one begins with the hypothesis.

Let us try an experiment.  Instead of taking the currently constituted months of September, instead put all of the individual trading days in a basket.  (We know that this basket has a negative bias, but bear with us).  From this basket we create trading months.  From the days in the other months, we create comparison months.

This is an interesting approach to getting beyond the data mining issue.  It is (unfortunately) not our idea but that of Andrew Moe.  He writes as follows:

When comparing the months composing September to a random basket of
days the results are random. Attempts to find seasons of non-randomness in a data lake
are frequently subject to data mining bias, as the same permutation
test debunking the September drift is easily used to identify (falsely)
statistically significant periods.

The study. Running a bootstrap permutation study on Dow data from
1960 to 2008 we estimate the empirical distribution of differences in
monthly return between September and other months. We test the
hypothesis that a random September is no more bearish than a
composition of random days sampled with replacement. We find that the
mean difference between populations is 0.0695%, yielding a p-value of
0.3612 – random.

Our Take

Here are four good reasons to ignore the September weakness articles.

  1. This is a widely advertised theory.  Even if you do not believe in completely efficient markets, one would expect some anticipation.
  2. We have already had a decline of nearly 2%, exceeding the expected monthly decline on the first day.  Should we now expect normal trading for the rest of the month?
  3. The evidence shows that the September pattern is not a statistically significant deviation.
  4. Other seasonal methods (Sell in May, Presidential Cycle) have not worked well in this time of turmoil

Quite obviously we do not know whether stock prices will mover higher or lower during the rest of September.  We do expect trading to reflect fundamental information about economic changes, as well as perceptions and trader lore.

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8 comments

  • Russ September 2, 2009  

    Well said. The September “horror” story seems to be getting even more press than usual this year. I’m tempted to view it as a contrarian indicator, a la magazine covers. Of course, everything I just wrote is purely anecdotal, which is no way to invest.

  • RB September 2, 2009  

    Bernanke did have a theory for Octobers . I recall reading a relation with the release of economic reports during this timeframe, but I can’t remember who or what exactly.

  • RB September 2, 2009  

    There are other theories as well.

  • Daniel September 3, 2009  

    Excellent post, RB! And you, Dashin-Jeff, as well!
    The stock market is a closed system. However, there are (at least) four factors which impose ‘spin’ on it from OUTSIDE the system. They are all very real. Two have obvious effects; two are more subtle and impossible to quantify.
    Taxes and tax-deadline dates cause ripples of perturbation. Selling is induced for non-market reasons.
    Quarterly and Annual performance snapshots cause all the tracked managers to become little squirrels adjusting their bowties and windowdressing their Portfolios, and then smiling for the camera. Then afterwards they go back to where their real models would have them. This also causes EXTERNALLY induced ripples.
    The moon exerts a tidal pull on ALL water on Earth. All means all. This includes the oceans. This includes the water molecules within our bodies. This is real. What is hard to quantify is WHAT the effect is, as the Moon waxes and wanes–although many have tried…
    MAJOR (and only major) astrological configurations of the planets exert broad emotional influences, either through electromagnetic variances, electronic variances, or the waxing and waning strength of the radio-wave signals they emit. (Anyone who thinks this is foo-foo is just dumb. Go to the NASA website, they have recordings of what the various planets “sound” like. What IS foo-foo are most of the simplistic interpretations of what these effects will be.)
    Perhaps the serotonin-level variances and vitamin D variances that come with reduced hours of sun exposure (mentioned in RB’s excellent post) CAN be included as well.
    Sometimes one must look to sources OUTSIDE the Market to explain the seemingly inexplicable within the Market.
    Daniel

  • VennData September 3, 2009  

    ^
    |
    |
    Whacko

  • RB September 3, 2009  

    I actually didn’t expect to find this.

  • Jeff Miller September 3, 2009  

    RB — Theories you want, theories you get 🙂
    Jeff

  • Daniel September 3, 2009  

    Astonishing! Where do you come up with this treasure-trove of reference material, RB? Are you curator at the Oracle of Delphi?
    >> “We find strong lunar cycle effects in stock returns. Specifically, returns in the 15 days around new moon dates are about double the returns in the 15 days around full moon dates. This pattern of returns is pervasive…”
    ..A reference librarian at the Akashic Records?
    All I know for a fact, which I got from a NOVA program on Public Television, is that the same macro tidal/gravitational pull that the Moon exerts on the oceans also occurs on a micro level on water everywhere, including in our bodies. I have no guess as to how this fact of physics correlates with the research observations you unearthed, RB.
    Very interesting. Lunacy as a “quantifiable edge.”
    Dashin Jeff, if your smile was a smile I share it with you. If it was a smirk, I have no use for you. Get me Vince.
    Daniel