Image Credit: Christophe Vorlet
By Jason Zweig | May 5, 2017 10:10 am ET
Everywhere investors turn, mathematics and machines seem to be rendering human judgment obsolete.
BlackRock, the giant asset manager, recently announced it will rely more heavily on computers to pick stocks. Rob Arnott, a leading advocate of mechanical investing approaches, said this past week that it’s “actually relatively easy to beat the market” if you get the math right.
Not so fast, says Richard Bookstaber, author of an important and elegantly written new book, “The End of Theory.”
When you measure markets, you change them, Mr. Bookstaber says. When individuals become part of groups, their behavior changes — in ways that are hard to predict. Investors who forget these facts and conclude that all problems have been solved are, sooner or later, in for a shock.
Computers and mathematical models excel in environments “where they can be trained on history and variables will behave in the future the way they did in the past,” says Mr. Bookstaber in an interview.
But a financial market doesn’t consist only of digitized streams of information. A market is made of human beings. Some are patient and prudent; others trade as if the world will end in the next half-hour.
Mr. Bookstaber, who has a Ph.D. in economics from the Massachusetts Institute of Technology, criticizes the world of financial math from the inside. Formerly a senior risk manager at Salomon Brothers, Morgan Stanley and Bridgewater Associates, the world’s biggest hedge fund, he also has been an official at the U.S. Treasury Department and the Securities and Exchange Commission.
Now chief risk officer for the investments office of the University of California, which manages $106 billion, Mr. Bookstaber may be the only investment manager who has published a research paper in the Journal of Theoretical Biology and holds two U.S. patents, including one for a gun trigger and firing mechanism.
Mr. Bookstaber says several factors combine to make quantitative models, and the funds and risk-management techniques based on them, fatally flawed.
Mind you, unaided human judgment is painfully fallible. Think of the fund managers who overloaded on Valeant Pharmaceuticals International before that stock collapsed.
Human judgment coupled with the mathematical rigor of computer modeling can make better decisions than either alone. But, says Mr. Bookstaber, when humans put blind faith in quantitative models, that’s dangerous.
A crowd isn’t the simple sum of its parts. Individuals, acting as a group, behave differently than in isolation. As a crowd becomes ever-so-slightly larger or smaller, its behavior can change in big, and unpredictable, ways. Think of how a throng moving toward a door can suddenly start — or stop — shoving to get in or out. Financial markets do that, too.
The likelihood of events varies over time. Home prices had gone for decades without a severe nationwide drop until they collapsed in 2006-07, helping to set off the global financial crisis.
Next is what Mr. Bookstaber calls “radical uncertainty.” The world is a Pandora’s box of surprises. Think of the so-called flash crash of 2010, when $40 stocks momentarily traded at prices as low as one penny and then bounced right back.
Above all, “people act on what happens relative to their expectations, which changes the world in ways that change those expectations,” Mr. Bookstaber says in an interview. “And that, in turn, changes the world again, and so on.”
Say you discover that companies with three Ys in their corporate names have outperformed, and you share that information until investors put billions of dollars into such stocks. The triple-Y shares will shoot up until they become so expensive that no one else will want to buy them, at which point they are doomed to underperform.
The very act of identifying a source of extra return in the financial markets can often end up reducing or erasing it. When massive computing power and the promise of precision lure billions, or hundreds of billions, of dollars into a mathematical investing strategy, that paradox can unfold faster and go farther than it would by human action alone. Success carries the seeds of its own failure. No wonder Mr. Bookstaber writes, “If you can model it, you’re wrong.”
His message isn’t entirely pessimistic.
Novel “agent-based modeling” techniques that learn how individuals and groups interact in real time show promise, he argues — although he says development is roughly at the stage weather forecasting was at in, say, the 1950s.
You can apply Mr. Bookstaber’s warnings in a couple of ways.
First, be wary of investing in mathematical approaches that are coupled with floods of new money chasing recent performance. Sooner or later, the influx of capital will drive up prices to unsustainable levels — at which point a selling panic may ensue. The recent popularity of so-called minimum-volatility funds could turn out to be one such case.
You can also recognize that, during market crises, investors who were naively eager to buy become desperately anxious to sell.
Having the cash and courage to buy from them at bargain prices is a good way to raise your future returns. Not joining them as blind-faith buyers in the first place is an excellent way to reduce your risk, now and in the future.
Source: The Wall Street Journal, http://on.wsj.com/2qA3gYp
Richard Bookstaber’s earlier book, A Demon of Our Own Design
The Mathematical Investor (blog by Marcos Lopez de Prado and David Bailey on the limitations of quantitative investing)
Chapter Four, “Prediction,” in Your Money and Your Brain
Appendix Four, “The New Speculation in Common Stocks,” in Benjamin Graham, The Intelligent Investor
Definitions of BACKTEST, MODEL, and QUANT in The Devil’s Financial Dictionary