Early in The Signal and the Noise, Silver alludes to Isaiah Berlin’s trope about hedgehogs and foxes. Hedgehogs know “one big thing,” while foxes know “many little things.” But there’s more. Hedgehogs display a disconcerting certainty that their one idea will put everything straight, whether on intellectual questions or in the working world. Moreover, Berlin warned, hedgehogs can cause a lot of damage when their nostrums are applied. Silver sees himself as a more modest fox, willing to draw on varied approaches to get his job done. So The Signal and the Noise doesn’t end with a crescendo, but actually stresses the quite limited ambit of our power to predict.
James Weatherall is an unabashed hedgehog, propounding a single idea with an uncommon confidence. After training in physics, philosophy, and mathematics, he now teaches logic and the philosophy of science at the University of California’s Irvine campus. With The Physics of Wall Street, he is taking his training even further: to finance in its preeminent location.
He is a man with a mission: to bring a heightened rationality to investment decisions. His book opens with an admiring visit to a hedge fund where a third of the employees have doctorates in physics, mathematics, statistics, even astronomy. Indeed, their rarefied insights are what’s wanted; “PhDs in finance need not apply.” In fact, there’s a niche Wall Street sector called “quant firms,” which reserve key positions for holders of advanced degrees.
Weatherall would have this perspective pervade the entire financial industry. He succinctly states his one big idea: “Insights that are commonplace in physics…are useful in studying virtually anything.” In one sense, Wall Street’s products have a physical character. Collateralized debt obligations, credit default swaps, and initial public offerings appear on paper or as electronic impulses. But Weatherall means more than this. Markets, he believes, are subject to physical laws. His star witness is Louis Bachelier, a French mathematician at the turn of the last century, who used Brownian motion to evaluate stock options. After that, we hear how ideas from such mathematicians as Jacob Bernoulli and Benoît Mandelbrot can be applied to mitigating risks and minimizing uncertainty. Not least of their influence has been to entrench mathematics in MBA programs, Wall Street’s principal recruiting pool.
But the book is less a celebration of the past than a prospectus for the future. Weatherall anticipates “a breakthrough in our ability to identify the underlying chaotic patterns lurking in market data,” that is, to impose order on the “noise” that bedevils Silver. In a similar vein, he foresees strides “in predicting financial calamity using mathematical techniques,” perhaps like Russia’s default in 1998, which some Nobel economists didn’t see coming. He also hopes that “studies of psychology and human behavior” can be framed so that they are “symbiotic with mathematical approaches to economics.” Here he foresees doing better than Newton, who confessed, “I can calculate the movements of stars, but not the madness of man.” Almost everyone favors rigor and unlocking more mysteries. That’s why most of us support science. Can there be anything amiss in feeling optimistic about crossing new frontiers?
What isn’t explained is whether melding physics with finance will bring more benefits for everyone, or only give an advantage to those who use the techniques—like high-speed trading, if you own a mainframe computer. We can agree there’s a lot of irrationality—not to say exuberance—in the investment world. But it’s not clear if Weatherall is saying that decisions based on Bernoulli will allocate capital more efficiently, and hence serve the commonweal. When physics enters medicine, as with MRIs, we can have a reasonable hope that patients will benefit as much as their doctors. But when quants were riding high on Wall Street, they were hired only to give their own firms an edge over the competition.
Alluding to the collapse of Bear Stearns and Lehman Brothers, the housing bubble, and the October 2008 crash, Weatherall concedes that “the misuse of mathematical models played a role in this crisis.” Still, his implication here is that the models themselves didn’t contribute to the downfall; it was that they were somehow mishandled. The ultimate problem with hedgehogs is hubris. In this case, it’s the assumption that the quality of our thought can be enhanced by new methodologies. The word “sophistication” recurs on almost every page of The Physics of Wall Street, as if to affirm that higher powers are present.
True, the discovery of the calculus enabled us to build planes that travel faster than the speed of sound. But thus far I’ve found scant evidence that mathematics and physics have a capacity to give us a deeper understanding of human and social behavior. Of course, we should be open to new findings. Still, that differs from proclaiming that “what we do know for sure is that there will be a next major advance, and…we will understand markets more clearly than we do today.” Here he seems to be saying that the physical sciences can tell us how to avoid the crashes and crises we now periodically face. If that’s so, I wish Weatherall had listed some warnings of coming “calamities” based on his physical laws, such as the impending college loan bubble: When will it burst, and how widespread will the fallout be?
Nassim Nicholas Taleb in Antifragile calls such certainty “the error of naive rationalism.” And it’s a naiveté with consequences. There’s no doubt that the quants who bundled bad mortages, adding algorithms to rate them AAA, helped to give us the current recession.4 But just as culpable were their nonmathematical superiors who allowed them such rein. So there’s a broader issue. Financial firms want to be at the cutting edge, which now means having a bevy of Ph.D.s, just as at other times and places, enterprises might feel they should have an accredited gypsy with tarot cards. We are coming close to deifying anything smacking of STEM—science, technology, engineering, and mathematics—whether for staying ahead of China or cutting-edge careers for our young people. If firms need workers adept in algebra, then such instruction should be available. But to rely on physics and mathematics for deciphering human behavior, in markets or elsewhere, can only bring blind alleys. Less of the world than we might like is, as Taleb puts it, “academizable, rationalizable, formalizable, theoretizable.” When such rubrics crowd out more discursive thinking, we all lose.
4 Weatherall barely mentions Scott Patterson’s indispensable The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It (Crown Business, 2010). And some stories worth reading: Felix Salmon, “Recipe for Disaster: The Formula That Killed Wall Street,” Wired, March 2009; Dennis Overbye, “They Tried to Outsmart Wall Street,” The New York Times, March 9, 2009; Julie Creswell, “The Quants are Reeling,” The New York Times, August 20, 2010; Pablo Triana, “The Flawed Maths of Financial Models,” Financial Times, November 29, 2010. ↩
‘The Physics of Wall St.’ February 7, 2013
Weatherall barely mentions Scott Patterson’s indispensable The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It (Crown Business, 2010). And some stories worth reading: Felix Salmon, “Recipe for Disaster: The Formula That Killed Wall Street,” Wired, March 2009; Dennis Overbye, “They Tried to Outsmart Wall Street,” The New York Times, March 9, 2009; Julie Creswell, “The Quants are Reeling,” The New York Times, August 20, 2010; Pablo Triana, “The Flawed Maths of Financial Models,” Financial Times, November 29, 2010. ↩