The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It (47 page)

Wilmott wanted this bright-eyed group to know he wasn’t any ordinary quant—if they hadn’t already picked up on that from his getup, which seemed more beach bum than Wall Street. Most quants, he
said, were navel-gazing screwups, socially dysfunctional eggheads entranced by the crystalline world of math, completely unfit for the messy, meaty world of finance.

“The hard part is the human side,” he said. “We’re modeling humans, not machines.”

It was a message Wilmott had been trying to pound into the fevered brains of his number-crunching colleagues for years, mostly in vain. In a March 2008 post on his website,
Wilmott.com
, he lambasted Wall Street’s myopic quant culture. “Banks and hedge funds employ mathematicians with no financial-market experience to build models that no one is testing scientifically for use in situations where they were not intended by traders who don’t understand them,” he wrote. “And people are surprised by the losses!”

Wilmott had long been a gadfly of the quants. And he had the mathematical firepower to back up his attacks. He’d written numerous books on quantitative finance and published a widely read magazine for quants under his own name. In 1992, he started teaching the first financial engineering courses at Oxford University. Single-handedly he founded Oxford’s mathematical finance program in 1999.

He’d also warned that quants might someday blow the financial system to smithereens. In “The Use, Misuse and Abuse of Mathematics in Finance,” published in 2000 in
Philosophical Transactions of the Royal Society
, the official journal of the United Kingdom’s national academy of science, he wrote: “It is clear that a major rethink is desperately required if the world is to avoid a mathematician-led market meltdown.” Financial markets were once run by “the old-boy network,” he added. “But lately, only those with Ph.D.’s in mathematics or physics are considered suitable to master the complexities of the financial market.”

That was a problem. The Ph.D.’s might know their sines from their cosines, but they often had little idea how to distinguish the fundamental realities behind why the market behaved as it did. They got bogged down in the fine-grained details of their whiz-bang models. Worse, they believed their models were perfect reflections of how the market works. To them, their models
were
the Truth. Such blind faith, he warned, was extremely dangerous.

In 2003, after leaving Oxford, he launched the CQF program, which trained financial engineers in cities from London to New York to Beijing. He’d grown almost panicky about the dangers he saw percolating inside the banking system as head-in-the-clouds financial engineers unleashed trillions of complex derivatives into the system like a time-release poison. With the new CQF program, he hoped to challenge the old guard and train a new cadre of quants who actually understood the way financial markets worked—or, at the very least, understood what was and wasn’t possible when trying to predict the real market using mathematical formulas.

It was a race against time, and he’d lost. The mad scientists who’d been running wild in the heart of the financial system for decades had finally done it: they’d blown it up.

On a
frigid day in early January 2009, several weeks after addressing the crowd of hopeful quants at the Renaissance Hotel, Wilmott boarded a plane at Heathrow Airport in London and returned to New York City.

In New York, he met with über-quant Emanuel Derman. A lanky, white-haired South African, Derman headed up Columbia University’s financial engineering program. He was one of the original quants on Wall Street and had spent decades designing derivatives for Goldman Sachs, working alongside legends such as Fischer Black.

Wilmott and Derman had become alarmed by the chaotic state of their profession and by the mind-boggling destruction it had helped bring about. Derman believed too many quants confused their elegant models with reality. Yet, a quant to the core, he still held firmly that there was a central place for the profession on Wall Street.

Wilmott was convinced his profession had run off track, and he was growing bitter about its future. Like Derman, he believed that there was still a place for well-trained, and wise, financial engineers.

Together that January, they wrote “The Financial Modelers’ Manifesto.” It was a cross between a call to arms and a self-help guide, but it also amounted to something of a confession:
We have met the enemy, and he is us
. Bad quants were the source of the meltdown.

“A spectre is haunting markets—the spectre of illiquidity, frozen
credit, and the failure of financial models,” they began, ironically echoing Marx and Engels’s
Communist Manifesto
of 1848.

What followed was a flat denunciation of the idea that quant models can approximate the Truth:

In other words, there is no single truth in the chaotic world of finance, where panics, manias, and chaotic crowd behavior can overwhelm all expectations of rationality. Models designed on the premise that the market is predictable and rational are doomed to fail. When hundreds of billions of highly leveraged dollars are riding on those models, catastrophe is looming.

To ensure that the quant-driven meltdown that began in August 2007 would never happen again, the two über-quants developed a “modelers’ Hippocratic Oath”:

• I will remember that I didn’t make the world, and it doesn’t satisfy my equations.
  

• Though I will use models boldly to estimate value, I will not be overly impressed by mathematics.
  

• I will never sacrifice reality for elegance without explaining why I have done so.
  

• Nor will I give the people who use my model false comfort about its accuracy. Instead, I will make explicit its assumptions and oversights.
  

• I understand that my work may have enormous effects on
  society and the economy, many of them beyond my comprehension.
  

While the manifesto was well-intentioned, there was little reason to believe it would keep the quants, in years to come, from convincing themselves that they’d perfected their models and once again bringing destruction to the financial system. As Warren Buffett wrote in Berkshire Hathaway’s annual report in late February 2009, Wall Street needs to tread lightly around quants and their models. “Beware of geeks bearing formulas,” Buffett warned.

“People assume that if they use higher mathematics and computer models they’re doing the Lord’s work,” observed Buffett’s longtime partner, the cerebral Charlie Munger. “They’re usually doing the devil’s work.”

For years, critics on the fringes of the quant world had warned that trouble was brewing. Benoit Mandelbrot, for instance, the mathematician who decades earlier had warned the quants of the wild side of their mathematical models—the seismic fat tails on the edges of the bell curve—watched the financial panic of 2008 with a grim sense of recognition.

Even before the fury of the meltdown hit with its full force, Mandelbrot could tell that the quantitative underpinnings of the financial system were unraveling. In the summer of 2008, Mandelbrot—a distinctly European man with a thick accent, patchy tufts of white hair on his enormous high-browed head, and pink blossoms on his full cheeks—was hard at work on his memoirs in his Cambridge, Massachusetts, apartment, perched on the banks of the Charles River. As he watched the meltdown spread through the financial system, he still chafed at the quants’ failure to listen to his alarums nearly half a century before.

His apartment contained bookshelves packed with his own writings as well as the weighty tomes of others. One day that summer he pulled an old, frayed book from the shelf and, cradling it in his hands, opened the cover and proceeded to leaf through it. The book, edited by MIT finance professor Paul Cootner, was called
The Random Character of Stock Market Prices
, a classic collection of essays about
market theory published in 1964. It was the same book that helped Ed Thorp derive a formula for pricing stock warrants in the 1960s, and the first collection to include Bachelier’s 1900 thesis on Brownian motion. The book also contained the essay by Mandelbrot detailing his discovery of wild, erratic moves by cotton prices.

The pages of the copy he held in his hand were crisp and ochered with age. He quickly found the page he was looking for and started to read.

“Mandelbrot, like Prime Minister Churchill before him, promises us not utopia but blood, sweat, toil, and tears,” he read. “If he is right, almost all of our statistical tools are obsolete. … Surely, before consigning centuries of work to the ash pile, we should like to have some assurance that all our work is truly useless.”