The Frailty of Market Predictions

The unexpected Brexit vote and Donald Trump’s presidential election victory both occurred despite overwhelming predictions to the contrary, writes John Reese in a recent article for The Globe and Mail. The CEO of Validea illustrates how forecasting in the world of investing is “equally fraught with unpredictable outcomes despite seemingly reasonable expectations.”

Reese supports his argument with the research findings of psychology professor Philip Tetlock, who conducted a study of the predictive success of both experts and non-experts and analyzed upwards of 80,000 forecasts regarding various political and economic events. Tetlock found that, regardless of educational background, experience or access to information, “the more famous the expert, the less accurate he or she tended to be.”

Using a metaphor of hedgehogs and foxes, Tetlock divides forecasters into two groups: Hedgehogs, who have bold ideas and are afforded media attention and headlines; and foxes, who are more flexible and skeptical in their thinking and who, Tetlock found, “tend to do better than hedgehogs” when predicting outcomes. In a 2010 paper, Tetlock argued that while experts generally have a higher predictive success rate than complete novices, “experts do not know nearly as much as they think they do, and they work hard to cover up mistakes.”

Reese explains Tetlock’s finding that computer models “tend to be better predictors than humans,” and that Validea’s use of quantitative models based on the philosophies of guru investors such as Benjamin Graham and Warren Buffett help identify companies with solid fundamentals.