Focus on fundamentals rather than “expert” forecasts
A cura di John Reese, Validea Capital Management
American philosopher and educator Nicholas Murray Butler once said, ” An expert is one who knows more and more about less and less until he knows absolutely everything about nothing.” His words, both wise and timeless, could apply to “expert” market forecasters.
Butler (1862-1947) was president of both Columbia University and the Carnegie Endowment for International Peace, as well as a recipient of the Nobel Peace Prize–distinctions which would make his comment a self-deprecating one, to say the least. But if we take a look back at the “expert” market predictions made at the end of 2016 and compare them to what actually happened during the course of the past year, Butler’s words seem to ring true.
In 2005, Wharton professor Philip Tetlock studied how successful experts were at forecasting and discovered that they could explain only 20 percent of the variability in the outcomes in their own predictions, regardless of their educational backgrounds, experience or access to information. In fact, he found that the more famous the expert, the less accurate their predictions.
James O’Shaughnessy, a market guru who inspired one of the stock screening models I created for Validea, wrote in his book What Works on Wall Street that human forecasters fall short of statistical models because they are affected by emotion, make inconsistent judgements, act in short-sighted ways or suffer from overconfidence. Benjamin Graham, whose investment strategy was the basis for another Validea model, wrote in his book The Intelligent Investor, “Investing isn’t about beating others at their game. It’s about controlling yourself at your own game.” A good thing to keep in mind when listening to the advice of “expert” prognosticators.
So, how did last year’s predictions fare? Not too well. The dollar is down, contrary to expectations. Inflation hasn’t really reared its head, and Treasury yields, which many had predicted would inch up, are down. Not to mention the continued upward march of the S&P 500 amidst much bullish grousing. But the individual misses aren’t really the point; the overriding truism is that economic forecasts and predictions regarding how the market will behave—in a day, a month or a year–is an exercise in futility.
In his book Expert Political Judgement, Tetlock wrote, “Learning from the past is hard, in part, because history is a terrible teacher.” Although the human brain can be drawn to history as an indicator of what’s to come, this can be a source of great disappointment. That said, we also can’t rule out the possibility that it will repeat itself. Among the many parallels we can draw between life’s macro issues and the world of finance, this could be one of the most compelling—that, no matter how much insight we think we have, there is no way to accurately predict what’s ahead. Dangerous in any context, this can be particularly costly given the ease with which today’s investors can tap into vast amounts of data and newsfeeds, and become deluded into thinking they possess the knowledge and insight necessary to make sound investment decisions.
As author, columnist and equity analyst Barry Ritholtz put it—bluntly—in a recent Bloomberg article, “We are very bad at forecasting. Examples are everywhere: Economic forecasts, earnings estimates, market forecasts, expectations of future technologies, not to mention election predictions. The data overwhelmingly show that as a species, we are simply awful at this.”
That’s not to say that all forecasts are wrong, because some turn out to be true—often those most touted in the media. But even when a forecaster hits the mark in one way or another, chances are good that their assumptions didn’t take into account all the factors that ended up influencing the event–if they are even known or quantifiable. And therein lies yet another layer of frailty in the prognosticative process, that of unknown unknowns. There is no possible way to predict the vagaries of the market, nor to fully understand what you fail to understand. Therefore, the best defense for investors is to stick to concrete data and the analysis of fundamentals—the “known knowns.”
Quantitative stock screening models take the emotion out of investing and help us avoid buying or selling equities at the worst possible times. That’s why at Validea we have designed portfolios that track the quantitative strategies of successful investors who look for strong companies with sustainable operations. By focusing on known metrics and removing emotion and/or “hunches” from the process, we are able to identify stable businesses well-poised to endure the inevitable market ups and downs over the long term. A good strategy when trying to minimize the effect of unknowns on your investment portfolio.