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Can We Really Know Where The Market is Headed?

October is upon us once again and, at least as far as the equity markets are concerned, one might say we can expand on our metaphor of the Summer Doldrums, which we talked about at length in our July market commentary, with this period being one of tempestuous seas of volatility and uncertainty.  

Equity markets are known to have crashes in October.  Even casual observers know of The Great Crash of 1929 as the prominent 1950’s economist John Kenneth Galbraith titled his book of the event in which the Dow Jones Industrial Average crashed more than 20% over the two days of October 28th and 29th after peaking in the month earlier. This brought an end to the “roaring 20s” and was followed by The Great Depression.  In 1987, the Crash of “Black Monday” occurred October 19th 1987 and the S&P 500 dropped more than 20% in one day from the previous close.  And, finally, in the first two weeks of October 2008 the S&P was down again over 20% in eight consecutive days of negative returns. 

If we know crashes happen in October, then it seems to follow investors should just sell at the end of September.  However, just as we explored the dictum “Sell in May and Go Away” a few months ago, it’s helpful to turn to the data for some possible answers.

The table below contains October price returns of the S&P 500 Index for each of the previous 20 years.  We mentioned October was a bad month in 2008--down more than 16% for the month--, but 13 of the 20 years were in fact positive for October.  This leaves only 7 of the years negative, and an average positive return across all months for the previous 20 years of around +1%.


Grid Source: Stadion
Data Source: Bloomberg Terminal

So, crashes happen in October, but positive returns happen also. This leaves us in a bit of a conundrum because, after examining the data of the past two decades, one would have been worse off having been out of the market than having been invested.

And this brings us to a “secret” of the markets.  Although there are seemingly an unlimited number of pundits and prognosticators willing to give their opinions to anyone who will listen, nobody knows where the market will go from here.  Or, as the brilliant philosopher and mathematician Bertrand Russell once said,

“The whole problem with the world is that fools and fanatics are always so certain of themselves, but wiser people are so full of doubts."

There is a noted and observable tendency among those who know little of a subject to amplify their own competence. This tendency, now categorized as the Dunning-Kruger Effect, has been popularized in recent years. This phenomenon occurs across all disciplines as we see “armchair experts” offer opinions on everything and do so with the highest degree of confidence. The Effect can also account for the inverse, i.e. those with deep knowledge on a subject can display a tendency toward doubt.

Perhaps this inflated sense of self can better be explained by the field of behavioral economics which combines elements of economics and psychology and studies the mental foibles of the human brain based on how humans behave and make decisions in the “Real World”.   The field likely began, or at least began to be formalized with the with the publishing of a paper in 1974 by Amos Tversky and Daniel Kahneman1 entitled Judgment under Uncertainty: Heuristics and Biases.

While it’s a title that only an academic could love, it belies the ancient or, perhaps better stated, pre-historic mental algorithms which we all use.  The heuristics are akin to mental, even subconscious, rules-of-thumb which likely stem from both evolutionary factors (evolutionary psychology) in the form of instincts and learned responses (behavioral psychology) a’la B.F. Skinner, Abraham Maslow or perhaps the best-known example of Ivan Pavlov and his work with dogs. 

One very illustrative example comes from Dr. Robert Cialdini in his book Influence: The Psychology of Persuasion in which he includes the following story: 

I got a phone call one day from a friend who had recently opened an Indian jewelry store in Arizona. She was giddy with a curious piece of news. Something fascinating had just happened, and she thought that, as a psychologist, I might be able to explain it to her. The story involved a certain allotment of turquoise jewelry she had been having trouble selling. It was the peak of the tourist season, the store was unusually full of customers, the turquoise pieces were of good quality for the prices she was asking; yet they had not sold. My friend had attempted a couple of standard sales tricks to get them moving. She tried calling attention to them by shifting their location to a more central display area; no luck. She even told her sales staff to “push” the items hard, again without success. Finally, the night before leaving on an out-of-town buying trip, she scribbled an exasperated note to her head saleswoman, “Everything in this display case, price × ½,” hoping just to be rid of the offending pieces, even if at a loss. When she returned a few days later, she was not surprised to find that every article had been sold. She was shocked, though, to discover that, because the employee had read the “½” in her scrawled message as a “2,” the entire allotment had sold out at twice the original price!

The heuristic demonstrated by the story, according to Dr. Cialdini, is that expensive things are seen as valuable or better-quality items (the mental shortcut of High price = quality). Circling back to markets, this very effect can be seen as price climb ever higher, as prices in equities are directly related to the influence of supply and demand.  As prices go up the demand strangely seems to increase, and on the flip side as prices fall suddenly it seems as if no one has any interest in buying the very thing that everyone clambered to buy when the price was higher.

Finally, the question can be posed: “Ok, I get that people make mistakes, but what is the solution? How do we avoid the mistakes?”. One answer may be, at least as far as investing is to not attempt to predict where the market will go from here.  Even the behavioral economics field seems to be oriented toward predictions.  In the case of science this makes sense, the point is to make predictions, and then to test them to see if they are true or not. 

But with investing perhaps the better solution is not to predict but to find a way to try and limit making mistakes.  This is the best solution we have been able to come up with so far, and our answer is to create models to try and “listen” to what the market is telling us and use the data to create a strategy to try and minimize mistakes.  That is not to say it’s the perfect solution, but so far at least it’s the best answer we have come up with.  We are always happy to discuss these ideas and we love feedback, so if you happen to find the perfect solution please let us know!  Happy Halloween.

Rob Dailey
Portfolio Management Analyst

1For those interested in reading more about Tversky and Kahneman: https://www.newyorker.com/books/page-turner/the-two-friends-who-changed-how-we-think-about-how-we-think

S&P 500 and Dow Jones Industrial Average data pulled from Bloomberg Terminal

The S&P 500 Index is the Standard & Poor’s Composite Index of 500 stocks and is a widely recognized, unmanaged index of common stock prices.

The Dow Jones Industrial Average is a price-weighted average of 30 significant stocks traded on the New York Stock Exchange.

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