The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It

Image of The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It
Author(s): 
Release Date: 
February 1, 2010
Publisher/Imprint: 
Crown Business
Pages: 
352
Reviewed by: 

Why do business writers have to try harder? Here is Scott Patterson with a terrific subject to write about—how the Quants stole Wall Street, and then helped to nearly destroy it in the financial crisis—and, instead of simply presenting it, he has to try to hype it desperately with painfully written descriptions and ludicrous references to “hubris” and “tragedy.” (A quant is a quantitative analyst who works in finance using numerical or quantitative techniques.)

Patterson is clearly a superb reporter, but he has been trained in the invariable and tedious style that characterized the Wall Street Journal before Murdoch took it over. There, they gave all the reporters a little book about what was “good” writing, how to use adjectives, where to put the most important paragraph, etc. Most of them never outgrew it. Happily the paper reads better today.

Patterson, also happily, allows his subject to overwhelm his prose a great deal of the time, and so has produced a really interesting book on a complex, but little-understood area of investing. Essentially, this area involves using arbitrages to trade, derived from mathematically determined relationships. Ed Thorp was the first, using formulae on random distribution to track convertible bond prices, and then creating a profitable arbitrage. What distinguishes Patterson’s book is that you get a detailed and understandable description of how Thorp put all that together.

Indeed, the best parts of the book are those that track the rise of individual quants and explain what their original contribution was. The story of Ken Griffin, for example, is carefully tracked, recounting how he started out trading convertible bonds from his Harvard dorm room with a couple of hundred thousand from his grandmother. With the help of an investor, he built the Citadel Investment Group, with his hawk’s eye for profitable arbitrages and trading strategies, into a $15 billion fund. There is a superb explanation of the rise and fall of Long-Term Capital Management (LTCM), which used a risk management model to make heavily leveraged trades with great success until a non-random event turned its mathematical models inside-out. There is even a close look at Renaissance Capital, a secretive fund that uses techniques from speech-recognition programming to make its bundle.

The mathematical models developed by the Quants weren’t responsible for the credit crunch and the apocalyptic recession that followed. Rather, they were part of a trend in which banks, funds, and just about everybody else, took on too much risk. As early as 2005, analysts at Dresdner Kleinwort wrote a paper warning that Citadel’s immense leverage of risk was a systemic threat. They compared Citadel to LTCM.

The problem, stated with complete accuracy, is that “shit happens.” Financial models track normal conditions, with subroutines for some abnormal behavior. But there is always the danger that something really abnormal, unforeseen by all the scenarios, will occur. Patterson cites finance professor Nassim Nicholas Taleb, who explained the issue in 2006:

“If ten thousand people flip a coin, after every ten flips the odds are there will be someone who has turned up heads every time. People will hail this man as a genius . . . some will even give him money. This is exactly what happened at LTCM. But it’s obvious that LTCM knew nothing about risk control. They were all charlatans.”

Patterson also provides a very clear explanation of how bankers used securitization to bundle messy subprime mortgages into triple-A rated tranches of CDOs (collateralized debt obligations), and into how credit default swaps work. The Quants contributed to this mess by creating something called a “synthetic” CDO. Yet another Quant, David X. Li, created a model for assigning correlations between CDO tranches—this meant there was a formulaic way to price them. “The result was a vicious feedback loop in which enthusiastic investors snapped up tranches of CDOs, creating demand for more CDOs, and that created demand for more mortgage loans.” Patterson relates the entire story, including the role that the massive build-up of carry trades played.

When the subprime debacle started, all of that fell apart, as we know. Patterson traces the fall of the Quants as each one piled up disastrous amounts of losses. Two quants even issued a kind of formal apology, called “The Financial Modeler’s Manifesto,” which included a kind of Hippocratic oath: “I will never sacrifice reality for elegance without explaining why I have done so. . . .” The book ends with a note about the menace of “dark pools,” suggesting that the same Quants have begun the same games again using these private securities exchanges.

There is a lot to be learned from Patterson’s book, and much of it is good reading. It is tough to slog through the hyperbolic prose at times, but when he gets down to business, Patterson writes well. The book is best described by the famous phrase of the French sixteenth century poet Rabelais: It’s a thin wire of gold in a puddle of merde.