Superforecasting for Active Investors

When it comes to picking a winning equities portfolio, knowing what information is relevant is half the battle.

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In a fiercely competitive world, active managers are constantly looking for ways to advance their performance edge. Becoming a better forecaster is a good place to start.

If you just look at averages, the active management industry has a spotty record. Some active investors manage to beat the market consistently, however, suggesting that they possess some degree of skill. If you can identify them or become one of them, the payoff is large. The question is, What separates skilled investors from unskilled ones?

Many people will answer that question by pointing to credentials or certain signs: The manager seems especially smart, acts more authoritatively than others, shows more conviction or appears on television more frequently.

The problem is that none of these factors are necessarily correlated with increased predictive capabilities. In fact, some of them have a mildly negative relationship. In a world engulfed in random noise, performance alone is a fairly unreliable measure of skill in the short run.

So what, then, are the traits common to the most skillful investors?

We have some thoughts on the matter, largely drawn from insightful research conducted by Philip Tetlock, professor at the Wharton School of the University of Pennsylvania and co-author of Superforecasting: The Art and Science of Prediction. The 2015 book is based on the findings of the Good Judgment Project, a multiyear study in which Tetlock and his colleagues asked thousands of crowdsourced participants to predict the likelihood of a variety of future political and economic events.

As the book’s title suggests, so-called superforecasters do, in fact, walk among us. Despite their lack of professional expertise, a small group of participants in the study significantly outpredicted both their fellow volunteers and teams of top professional researchers. Over time, their advantage not only persisted but also grew. Most important, Tetlock and others found that good analytical judgment relies on a set of discrete approaches that can be taught and learned.

With that in mind, we offer a framework for investors looking to improve.

How forecasters think matters more than what they think, according to the research. In fact, how a person approaches a research question is the single biggest element distinguishing a great forecaster from a mediocre one.

Predictive research is about focusing on the information that is most likely to raise the odds of being right: If you know X, your odds improve by Y percent. Superforecasters think in terms of probabilities; break complex questions down into smaller, more tractable components; separate the knowns from the unknowns; and search for comparables to guide comprehension.

Professional investors and research analysts gather reams of data to build their forecasting models, a lot of which has little proven predictive value. Our research shows, for example, that there is little correlation between a country’s gross domestic product growth and how well its stock market performs.

Good investment forecasting is akin to meditating in the middle of Times Square. It requires learning how to isolate the few relevant signals from a cacophony of irrelevant market noise. That’s not something most of us are taught in our formal education. In areas such as math, science or engineering, however, the relationship between general laws and what you observe is much more concise.

In a world of complex, interrelated systems, the range of possible outcomes of any event is wider than most people can imagine. Outcomes usually look obvious after the fact, but they frequently surprise when they happen. The Superforecasting research suggests that a forecaster who considers many different theories and perspectives tends to be more accurate than a forecaster who subscribes to one grand idea or agenda. Being open-minded also means accepting the — very real — possibility of overconfidence.

Superforecasters also have a healthy appetite for information, a willingness to revisit and update their predictions as new evidence warrants and the ability to synthesize material from sources with very different outlooks on the world.

It takes a certain kind of person to have both the humility to accept that they may be overconfident in their assumptions and predictive powers and the conviction necessary to manage an investment portfolio. It also takes a certain type of person to learn from their mistakes without overlearning. The best forecasters are less interested in whether they are right or wrong than in why they are right or wrong.

In the words of Tetlock and his colleagues, superforecasters also tend to be in “perpetual beta mode.” Like software developers working on an untested app, these people rigorously analyze their past performances to figure out how to avoid repeating mistakes or overvaluing successes.

In the age of information overload, the active investor’s edge increasingly lies in knowing what information truly matters and how to process that information. If you can identify skill — whether you are looking to hire a portfolio manager or you are a portfolio manager aspiring to improve — we believe that this superforecasting framework can give you a better shot at beating the market.

Sammy Suzuki is portfolio manager of strategic core equities at AllianceBernstein in New York.

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