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Why Models Beat Humans

An excerpt from James O’Shaughnessy’s book, “What Works on Wall Street”:

In a famous cartoon, Walt Kelly’s character Pogo says: “we’ve met the enemy, and he is us.” This illustrates our dilemma. Models beat the human forecasters because they reliably and consistently apply the same criteria time after time. In almost every instance, it is the total reliability of application of the model that accounts for its superior performance. Models never vary. They are always consistent. They are never moody, never fight with their spouse, are never hung over from a night on the town, and never get bored. They don’t favor vivid, interesting stories over reams of statistical data. They never take anything personally. They don’t have egos. They’re not out to prove anything. If they were people, they’d be the death of any party.

People, on the other hand, are far more interesting. It’s far more natural to react emotionally or personalize the problem than is to dispassionately review broad statistical occurrences — and so much more fun! It’s much more natural for us to look at the limited set of our personal experiences and then generalize from this small sample to create a rule of thumb heuristic. We are a bundle of inconsistencies, and although making us interesting, it plays havoc with our ability to successfully invest our money. In most instances, money managers, like the college administrators, doctors, and accountants mentioned above, favor the intuitive method of forecasting. They all follow the same path: analyze the company, interview the management, talk to customers and competitors, etc. Most, if not all, money managers think that they have the superior insights and intelligence to help them to pick winning stocks, yet 70 percent of them are routinely outperformed by the S&P 500. They are victims of their own overconfidence in their ability to outsmart and out guess everyone else on Wall Street. Even though virtually every study conducted over the last 60 years finds that simple, actuarially-based models created with a large data sample will outperform traditional active managers, they refuse to admit this simple fact, clinging to the belief that, while that may be true for other investors, it’s not true for them.

Each of us, it seems, believe that we are above average. Sadly, this cannot be true statistically. Yet, in tests of people’s belief in their own ability — typically people are asked to rank their ability as drivers — virtually everyone puts their own ability in the upper 10 to 20 percent! It may be tempting to dismiss this as a foible that highly trained professionals would not stumble into, yet, as Professor Nick Bostrom of Oxford University points out in his paper Existential Risks: Analyzing Human Extinction and Related Hazards: “Bias seems to be present even among highly educated people. According to one survey, almost half of all sociologists believed that they would become one of the top ten in their field, and 94% of sociologists thought they were better at their jobs than their average colleagues.” In his 1997 paper the Psychology of the Nonprofessional Investor, Nobel laureate Daniel Kahneman says: “The biases of judgment and decision-making have sometimes been called cognitive illusions. Like visual illusions, the mistakes of intuitive reasoning are not easily eliminated… merely learning about illusions does not eliminate them.” Kahneman goes on to say that, like our investors above, the majority of investors are dramatically over confident and optimistic, prone to the illusion of control where none exists. Kahneman also points out that the reason it is so difficult for investors to correct their false beliefs is because they also suffer from hindsight bias, a condition that he described thus: “psychological evidence indicates people can rarely reconstruct, after the fact, what they thought about the probability of an event before it occurred. Most are honestly deceived when they exaggerate their earlier estimate of the probability that the event would occur… because of another hindsight bias, events that the best informed experts did not anticipate often appear almost inevitable after they occur.”

If Kahneman’s insight seems hard to believe, go back and see how many of the “experts” were calling for a NASDAQ crash in the early part of the year 2000—and contrast that with the number of people who now say it was inevitable. Or go to the library and browse business magazines from the summer of 2007: Were any of them filled with dire warnings about the coming crash in real estate and credit markets and the worst stock market downturn since the Great Depression? On January 1, 2008, would a panel of Wall Street’s top analysts, economists, market forecasters, stock pickers, and money managers ever have predicted that in less than two years, Bear Stearns would be forced to sell itself to J.P. Morgan Chase for a fraction of book value because of a run on the bank? That Lehman Brothers, a firm with more than 156 years of operating history, would collapse into bankruptcy? That Merrill Lynch— the thundering herd — would be forced to sell itself to the Bank of America to avoid its own collapse? That Goldman Sachs and J.P. Morgan, kings of the investment bankers, would be forced to declare themselves ordinary banks? My guess is that no matter how diligently you search, you will find no such warnings. After the fact, we see a plethora of books, articles, and documentaries chronicling the crash, with many authors claiming it was inevitable. That’s hindsight bias.

What’s more, even investors who were guided by a quantitative stock selection system can let their human inconsistencies hogtie them. A September 16, 2004 issue of the Wall Street Journal includes an article entitled A Winning Stock Pickers Losing Fund. The story centers on the Value Line Investment Survey, which is one of the top independent stock research services and has a remarkable long-term record of identifying winners. According to the Wall Street Journal, “the company also runs a mutual fund, and in one of Wall Street’s odd paradoxes, it has performed terribly. Investors following the Value Line approach to buying and selling stocks would’ve racked up cumulative gains of nearly 76% over the five years ended in December, according to the investment research firm. That period includes the worst bear market in a generation [Author’s note: they were referring to the downturn on 2000-2003, not what turned out to be the worse downturn of 2008-2009]. By contrast, the mutual fund — one of the nation’s oldest, having started in 1950 — lost a cumulative 19% over the same period The discrepancy has a lot to do with the fact that the Value Line fund, despite its name, does not rigorously follow the weekly investment advice printed by its parent Value Line publishing.” In other words, the managers of the fund ignore their own data, thinking they can improve on the quantitative selection process! The article goes on to point out that another closed-end fund, the First Trust Value Line Fund, adheres closely to the Value Line survey advice, and has earned gains more in line with the underlying research.

Models beat humans.

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