Image Credit: Christophe Vorlet
By Jason Zweig | 1:57 pm ET Sept. 25, 2015
Can’t anybody here play this game?
Three-quarters of all U.S. stock mutual funds have failed to beat the market over the past decade. Last year, 98% of economists expected interest rates to rise; they fell instead. Most energy analysts didn’t foresee oil’s collapse from $145 a barrel in 2008 to $38 this summer—or its 15% rebound since.
A new book suggests that amateurs might well be less-hapless forecasters than the experts—so long as they go about it the right way.
I think Philip Tetlock’s Superforecasting: The Art and Science of Prediction, co-written with the journalist Dan Gardner, is the most important book on decision making since Daniel Kahneman’s Thinking, Fast and Slow. (I helped write and edit the Kahneman book but receive no royalties from it.) Prof. Kahneman agrees. “It’s a manual to systematic thinking in the real world,” he told me. “This book shows that under the right conditions regular people are capable of improving their judgment enough to beat the professionals at their own game.”
The book is so powerful because Prof. Tetlock, a psychologist and professor of management at the University of Pennsylvania’s Wharton School, has a remarkable trove of data. He has just concluded the first stage of what he calls the Good Judgment Project, which pitted some 20,000 amateur forecasters against some of the most knowledgeable experts in the world.
The amateurs won—hands down. Their forecasts were more accurate more often, and the confidence they had in their forecasts—as measured by the odds they set on being right—was more accurately tuned.
The top 2%, whom Prof. Tetlock dubs “superforecasters,” have above-average—but rarely genius-level intelligence. Many are mathematicians, scientists or software engineers; but among the others are a pharmacist, a Pilates instructor, a caseworker for the Pennsylvania state welfare department and a Canadian underwater-hockey coach.
The forecasters competed online against four other teams and against government intelligence experts to answer nearly 500 questions over the course of four years: Will the president of Tunisia go into exile in the next month? Will the gold price exceed $1,850 on Sept. 30, 2011? Will OPEC agree to cut its oil output at or before its November 2014 meeting?
It turned out that, after rigorous statistical controls, the elite amateurs were on average about 30% more accurate than the experts with access to classified information. What’s more, the full pool of amateurs also outperformed the experts.
The most careful, curious, open-minded, persistent and self-critical—as measured by a battery of psychological tests—did the best.
“What you think is much less important than how you think,” says Prof. Tetlock; superforecasters regard their views “as hypotheses to be tested, not treasures to be guarded.”
Most experts—like most people—“are too quick to make up their minds and too slow to change them,” he says. And experts are paid not just to be right, but to sound right: cocksure even when the evidence is sparse or ambiguous.
So the project was designed to force the forecasters “to be ruthlessly honest about why they think what they do,” says Prof. Tetlock.
First, participants got training materials explaining the basics of how to think about probabilities in an uncertain world.
The forecasters were urged to forage for information that might disprove their assumptions—and to change their minds at will, tweaking their predictions as often as new evidence emerged.
One wrote a software program that sorted his online sources of news and opinion by ideology, topic and geographic origin, then told him what to read next in order to get the most-diverse points of view.
After each outcome, the superforecasters analyzed not just whether their forecasts had been right, but also whether their reasoning was right and the odds they had set were too high or low.
Warren Hatch, an analyst at McAlinden Research Partners, an investment-research firm in New York, says he learned that “just because you know a lot about something doesn’t mean you’ll be a good forecaster in that area.” He says “it was humbling” for him to realize that he “blew almost all” the questions closely related to finance.
Joshua Frankel, a filmmaker and opera director in Brooklyn, N.Y., says the tournament taught him to “look at the world in a less binary way, to think much more in terms of probabilities.”
You can cultivate these same skills by visiting GJOpen.com and joining the next round of the tournament. Or you can try refining your own thinking.
Start by zeroing in on the “base rate” — the average historical experience. If you’re considering whether to invest in an initial public offering, don’t first bury yourself in the details of why this particular company might be the next Google. Instead, begin with the assumption that it will match the returns of the typical IPO—which underperforms the rest of the stock market by two to three percentage points annually in the long run.
Next, ask what the company would have to do to outperform that average by, say, four percentage points annually—enough to beat the market overall. Work up a list of all the companies in the past that have done so and see which factors they seem to have in common. Does this IPO have the same forces in its favor? Write down your reasoning in detail and estimate the numerical odds, as precisely as you can, that you are correct.
Then do what the great investor Charles Munger, Warren Buffett’s business partner, calls “inverting”: Ask what this IPO would have to do to underperform the typical offering. How much does it have in common with past failures?
Finally, as new information comes in, ratchet your expectations up or down.
If you think all this sounds like a lot of work, you’re right. And there’s no guarantee that your forecast will be accurate. But it will be vastly better than a hunch — and very likely at least as reliable as Wall Street’s guesswork.
Source: The Wall Street Journal
What Are the Secrets of Better Intuitive Forecasts? [slides courtesy of the Good Judgment Project]
good judgment [PDF]