Good Quant, Bad Quant

MarketWatch’s Paul Farrell recently offered up a scathing critique of “quants”, complete with this eye-catching subhead: “By Predicting Your Behavior, Quants Control Your Mind, Money, the Markets”.

Since I run what could be considered “quantitative strategies” both on my web site, Validea.com, and in my money management business, I was interested to see what Farrell had to say about quants and their impact on the market.

To be sure, quants play a big role on Wall Street, and they no doubt played a role in the recent crisis. Farrell references a very interesting article in Wired magazine, for example, that explains how one widely used quant formula wreaked havoc on the market by vastly underestimating risk leading up to the financial bust and market crash. Those who follow the hedge fund industry, where quants may have gained the most attention, have heard the horror stories of Goldman Sachs’s Global Alpha fund and AQR’s Absolute Return fund, both of which were pounded in 2008, according to reports.

But, according to Farrell, the issue is much greater than that one quant theory. In fact, he sees what amounts to a quant conspiracy as the major driver behind just about everything on Wall Street, usually for the worse: “Quant technologies influence everything Wall Street does ‘to’ Main Street: Not just trading, portfolio management and market manipulation, but every aspect of the Street including financial planning and broker training, day-trading systems, data design and transparency, 401(k) retirement programs, marketing, advertising and branding, lobbying and government regulations, and so many other niches,” writes Farrell. “The real story is far broader and much more interesting, offering clues to the next meltdown.”

I have a lot of respect for Mr. Farrell and I’ve appeared on his radio show in the past, but unfortunately Farrell’s quant article doesn’t offer any clues about the next meltdown. In fact, it doesn’t really offer any clues as to why quants are the primary group responsible for the current meltdown, or how quants “control your mind, money, [and] the markets”. He criticizes those who talk or write about neuroeconomics and behavioral finance as “misleading” the public, but offers no real evidence to refute their research — just this generalized, unsupported conclusion: “Even if you learn all the new rules from the new pop-psychology books your brain will unconsciously ignore the new neuroeconomic stuff you read and convince you that you’re acting ‘rational.'”

As you probably can tell, I take issue with Mr. Farrell’s assertions. Yes, quantitative models can cause problems when used improperly, or when their underlying assertions are wrong. But so, too, can humans cause problems when acting inappropriately, or when operating on underlying assertions that are wrong.

When it comes to stock investing, the reality is this: Quantitative investing approaches have been proven to be a blessing for investors. Such approaches take emotion out of the equation, helping investors to buy low, when their brains tell them to stay on the sidelines, and sell high, when their brains want to keep holding on to overvalued stocks. Are quantitative methods perfect? Of course not. There is no perfect way to play the market, and any quantitative strategy will go through periods of underperformance. But over the long run, good, proven quant strategies can significantly help your portfolio.

There is a key distinction to make here about quant strategies, however: Fundamental quant strategies look at firms’ underlying businesses, and try to exploit differences in the value of those businesses and the value of their stocks; technical, trading quant approaches instead try to capitalize on some anomaly in price based on historical price patterns, industry, momentum, and other technical variables. They are not tied to the underlying value of the business (it’s earnings, sales, debts, etc.), which, to me, makes them inherently more risky. The strategies I run on my web site and in my money management business are all fundamental-based approaches. Nevertheless, technical quant strategies at least employ a system that takes dangerous emotion and hunch-playing out of the process.

Now I want to offer up some evidence to support my contention that quantitative strategies — particularly fundamental-based quant approaches — can be a great help to investors. And there’s a lot of it.

For starters, there’s the research of Philip Tetlock, the University of California-Berkeley professor whose two-decade study of predictive powers included nearly 300 academics, economists, policymakers and journalists, and detailed how more than 82,000 forecasts fared against real-world outcomes in the areas of politics, economics, and other areas. Tetlock found that so-called “experts” couldn’t predict more than 20 percent of outcomes when asked to make various political and economic predictions. Crude algorithms, on the other hand, yielded accurate predictions 25 to 30 percent of the time, while sophisticated algorithms were right almost half the time. In other words, quantitative models were far better prognosticators than even the best humans.

For more evidence, let’s turn to James O’Shaughnessy, one of the gurus upon whom I base my strategies. O’Shaughnessy is a pure quant. His study of more than four decades of stock returns identified what have historically been the best quantitative stock-picking methods, and he uses his quantitative models to manage money today. In What Works on Wall Street, he cites several studies that all found that human forecasters couldn’t match statistical-actuarial forecasting models. In one study, for example, an actuarial model did better in predicting whether certain high school students would be successful in college than did admissions officers at many colleges. In another, a researcher named Jack Sawyer reviewed 45 different studies that compared human and actuarial predictive ability. “In none [of the 45] was the clinical, intuitive method—the one favored by most people—found to be superior,” O’Shaughnessy writes. “What’s more, Sawyer included instances in which the human judges had more information than the model and were given the results of the quantitative models before being asked for a prediction. The actuarial models still beat the human judges!”

How can that be? It’s because people are emotional creatures, and emotions lead to inconsistency in how we assess problems. Explains O’Shaughnessy: “Models beat human forecasters because they reliably and consistently apply the same criteria time after time. … 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.”

In short, quantitative models work precisely because they avoid the problems that neuroeconomics and behavioral science point out as reasons humans usually aren’t good investors — hindsight bias, overconfidence, short-sightedness, etc.

Farrell contends, however, that being aware of these problems cannot, in the end, help us change our behavior. “Paradoxically,” he writes, “the more we learn about our irrational brains, the more we convince ourselves we’re in control, acting rationally.”

If you read the writings of some of Wall Street’s most successful investors, you’ll find a much different take. Warren Buffett, Peter Lynch, Benjamin Graham, John Neff, Joel Greenblatt — these and other star investors write extensively about how understanding the mind and emotions made them better investors, and many did so years or decades before behavioral finance came into the spotlight. And a big way the gurus sidestepped irrational emotions was by focusing on the numbers, through fundamental-based, mostly or completely quantitative strategies. Their track records and those of many others who share their views show that, while achieving total rationality is impossible, you can learn from your behavior and become a better, more rational investor, and quantitative strategies are a key tool in doing so.

When it comes to following purely quantitative investment strategies, there’s another key point. Following proven, fundamental-based quant methods isn’t a way to convince yourself that you are in control. Rather than putting your faith in your perpetually irrational brain, you’re putting control in the hands of years and years and years of data and research that have identified long-term trends and realities in the stock market. In doing so, you acknowledge that you are not in control, and, in fact, relinquish the control that we humans so crave. And the facts show that, in the process, you probably make yourself a much better investor.

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