The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It (21 page)

He’d set up shop on the thirty-third floor of Morgan’s headquarters inside the Exxon Building at 1251 Avenue of the Americas, the same skyscraper that had housed Bamberger and Tartaglia’s stat-arb experiment, with several Unix workstations, high-end computers designed for technical applications and complex graphics. His first hire was Kim Elsesser, a programmer with a master’s degree in operations research from MIT. Elsesser was thin, tall, blond, and blue-eyed: a perfect target for the testosterone-soaked Morgan traders. She was also a highly gifted mathematician and computer programmer. She’d first joined Morgan in January 1987 before leaving for grad school in Cambridge, then returned to the bank in 1992. Within a few months, she signed up with Muller. He dubbed his new trading outfit Process Driven Trading, PDT for short. “Process-driven” was essentially shorthand for the use of complex mathematical algorithms that only a few thousand people in the world understood at the time.

Muller and Elsesser built the operation from scratch. They wrote trading models in computer code and hooked up their Unix workstations to Morgan’s mainframe infrastructure, which was plugged into major exchanges around the world. Muller designed the models, and Elsesser, familiar with Morgan’s system, did most of the programming.
They started trading in the United States, then added Japan, followed by London and Paris. They would trade once a day, based on their models. They worked crazy hours, but it all seemed for naught.

Muller was able to glean tidbits of information from other fledgling groups of mathematicians who were trying to crack the market’s code. In 1993, he paid a visit to a little-known group of physicists and scientists running a cutting-edge computerized trading outfit from a small building in Santa Fe, New Mexico. They called themselves Prediction Company, and they were reaching out to Wall Street firms, including Morgan Stanley, for seed capital. Muller’s job was to check them out.

A founder of Prediction Company was Doyne Farmer, a tall, ropy physicist and early innovator in an obscure science called chaos theory. Given more to tie-dyed T-shirts and flip-flops than the standard-issue Wall Street suit and tie, Farmer had followed in Ed Thorp’s footsteps in the 1980s, creating a system to predict roulette using cutting-edge computers wedged into elaborate “magic” shoes. Also like Thorp, Farmer moved on from gambling in casinos to making money using mathematics and computers in financial markets around the world.

Muller and Farmer met at the company’s office on 123 Griffin Street in Santa Fe, otherwise known as the “Science Hut.” Muller’s questions came quick and fast. When Farmer would ask for information in return, Muller, poker player that he was, held his cards close to his vest. Eventually Farmer had enough.

“We had to kick him out,” Farmer later recalled. “If you give someone a piece of information that they can use, you expect to get something in return that you can use. It makes sense. But Pete didn’t give us anything.”

Farmer didn’t realize that Muller didn’t have much of anything to give. Not yet.

Later that year, Morgan’s management was looking to trim the fat. PDT was in the crosshairs. The firm had paid a lot of money to Muller, and he wasn’t delivering. John Mack, the bond trader who’d recently been named president, called a meeting to hear managers defend their businesses.

Muller wore a suit to the meeting. His hair was oiled and combed,
rather than in its usual floppy-banged tangle. A team of tight-lipped Morgan execs sat around a long table in a warm, dusky conference room. Muller had to wait as several managers made their survival pitches. Their desperation was evident. Muller made a mental note:
Stay calm, look cool, be confident
. When his turn came, he flatly admitted that PDT hadn’t succeeded yet. But it was on the edge of great things. Computerized trading was the future. He just needed more time.

As he stopped speaking, he looked at Mack, who gave him a confident nod back. Mack had bought in.

Perseverance paid off, and soon there were signs PDT was beginning to grasp the Truth, or at least a small corner of it—they turned a profit. The day they made their first million dollars, Muller and Elsesser tossed themselves a party (consisting of cheap wine in plastic cups). In short order, a million would be a sleepy morning yawn, a blink of the eye.

In early 1994, Muller put together his dream team of math and computer aces: Mike Reed, soft-spoken geophysicist with a Ph.D. in electrical engineering from Princeton; Ken Nickerson, the ultimate number cruncher, a tall, brooding math expert with a Ph.D. in operations research from Stanford; Shakil Ahmed, a skin-and-bones computer programming whiz from Princeton; and Amy Wong, who sported a master’s in electrical engineering from MIT. This small group would form the core of what soon became one of the most profitable, and little known, trading operations in the world.

Aside from deep pockets, Muller had another advantage in working for a giant investment bank. Other trading outfits, such as hedge funds, funneled their trades to exchanges such as the NYSE through regulated broker dealers, including Morgan. One hedge fund that used Morgan as its brokerage for stocks was a trading group at Renaissance Technologies called Nova, run by Robert Frey, the mathematician who’d worked under Nunzio Tartaglia at Morgan Stanley.

In the mid 1990s, the Nova fund had a bad stretch. PDT took the positions off Renaissance’s hands and folded them into its own fund. It worked out quite well, as the positions eventually became profitable and also gave Muller a rare glimpse inside Renaissance’s secret architecture. Renaissance, for its part, retooled Nova into a profit-generating machine.

By
1994, the stage was set. Muller had the money and the talent to go to work. They didn’t have much time. Mack would slam the door shut in a heartbeat if he thought the group wasn’t delivering.

Working late hours and weekends, PDT’s dream team built an automatic trading machine, a robot for making money. They called their robot Midas—as if everything it touched would turn to gold. Nickerson and Ahmed did the fine-grained number crunching, searching for hidden signals in the market that would tell the computer which stocks to buy and sell. Nickerson focused on the U.S. market, Ahmed overseas. Reed built up the supercomputer infrastructure, mainlining it into financial markets around the world. The strategy was statistical arbitrage—the same strategy Bamberger had devised at Morgan Stanley in the 1980s. PDT’s quants had largely discovered how to implement the strategy on their own, but there’s little question that by the time Midas was up and running, the idea of stat arb was in the air. Doyne Farmer’s Prediction Company was running a stat arb book in Sante Fe, as were D. E. Shaw, Renaissance, and a number of other funds. Over the years, however, few stat arb funds would do nearly as well as PDT, which in time became the most successful proprietary trading desk on Wall Street in terms of consistency, longevity, and profitability.

Midas focused on specific industries: oil drillers such as Exxon and Chevron, or airline stocks such as American Airlines and United. If four airline companies were going up and three were going down, Midas would short the stocks going up and buy the stocks going down, exiting the position in a matter of days or even hours. The tricky part was determining exactly when to buy and when to sell. Midas could do these trades automatically and continuously throughout the day. Better yet, Midas didn’t ask for a fat bonus at year’s end.

By the fourth quarter of 1994, the money started piling up. Midas was king. Just flip on the switch and
zzip-zip-zip … zap … zap … zooing … bapbapbapbap … zing … zing … zap!
The digitized computerized trades popped off like firecrackers, an electronic gold mine
captured in upward-flying digits on PDT’s computer screens as the money rolled in like magic.

It was amazing, exhilarating, and at times terrifying. One night Elsesser was riding home in a taxicab, exhausted after a long day’s work. The buildings and lights of the city flashed by in a blue blur. The driver’s radio was an annoying fuzz in the background. A piece of news broke through the static: a radio announcer was describing unusual trading activity that was wreaking havoc in Tokyo’s markets.

Elsesser’s ears pricked up.
Could that be us? Shit
.

Frantic, she ordered the taxi to take her back to Morgan’s headquarters. She was always worried that some glitch in their computer program could unleash tsunamis of buy or sell orders. You never knew if the system would go haywire like some kind of computerized Frankenstein. PDT wasn’t responsible for the chaos in Tokyo that day, but the possibility always lurked in the background. It could be hard to sleep at night with the computers whirring away.

But those were worries for another day. PDT’s performance was so incredible, it matched and at times even outpaced Renaissance’s Medallion fund. In 1997, however, Medallion’s returns leapt to a new dimension. The gains were unbelievable. Jim Simons had left everyone behind, and no one knew how he’d done it. Eventually, Renaissance stopped trading through Morgan, concerned that Muller’s operation was eyeballing its strategies. True to the spymaster culture they’d come from, the quants on Long Island were becoming increasingly paranoid, worried that rivals such as Muller would steal their special sauce. Likewise, Muller grew increasingly nervous about spies inside Morgan Stanley. PDT’s own traders were kept in silos, familiar only with their own positions and in the dark about the rest of PDT’s growing strategies.

Even as he reveled in PDT’s success, Muller was wary of over-confidence. “Keep your emotions in check,” Muller said to his traders over and over again. He knew from experience. After he and Elsesser first started trading in the early 1990s, they made several snap decisions to bypass the computer models. An unexpected economic report or surprise move by the Fed would send the market into chaos. Better to override the models, they thought, or simply shut everything down.

But they quickly concluded that the computers were more reliable than people. Every time they tried to outsmart the computer, it turned out to be a bad move. “Always trust the machine” was the mantra.

One day in 1994, Muller came across some old records from a quantitative trading group at Morgan Stanley that had briefly shot the moon in the 1980s. He’d heard stories about the group, trading-floor legends about a wild Italian quant named Nunzio Tartaglia, the astrophysicist and onetime Jesuit seminarian. Much of the history of the group had been lost. The rising young quants at PDT had little idea that the group was the originator of stat arb. While Muller and his team had developed the strategy on their own and had added their own unique bells and whistles to it, the earlier Morgan group was the first to discover it. By the 1990s, the strategy was spreading rapidly, and quants such as Muller and Farmer were trying to crack its code.

Knowing about stat arb and actually applying it were two different propositions, however. PDT had pulled it off.

The records from APT also taught Muller a valuable lesson. APT had piled up huge returns for a few years. Then, suddenly, the music stopped. It meant he could never let his guard down; he had to always keep moving, improving, fine-tuning the system.

In 1995, a young quant named Jaipal Tuttle arrived at PDT. Tuttle, who sported a Ph.D. in physics from the University of California at Santa Cruz, had been trading Japanese warrants in Morgan’s London offices for the previous few years. But Japan’s stock market and economy collapsed in the early 1990s, and so did the Japanese warrant business.

Tuttle’s physics background gave him the tools to understand many of the complex trades PDT executed. But since he didn’t have any computer programming skills, it limited his ability to design and implement models. Instead, he became PDT’s “human trader.” At the time, there were still certain markets, such as stock index futures, that weren’t fully automatic. Trades spat out by PDT’s models had to be called in over the telephone to other desks at Morgan. That was Tuttle’s job.

The automated trading system didn’t always go smoothly. Once
PDT mistakenly sold roughly $80 million worth of stock in about fifteen minutes due to a bug in the system. Another time Reed, who was running the Japanese stock system at the time, asked another trader to cover for him. “Just hit
Y
every time it signals a trade,” he said. He failed to mention the need to also hit enter. None of the trades went through properly.

PDT often hired outside consultants to work for the group temporarily, typically academics out to make an extra buck in between teaching gigs. One day a consultant named Matt was implementing an arbitrage strategy on S&P 500 index options. The trade involved selling an option tied to the S&P 500 for one month, such as May, and buying an option for another month, such as June, to capitalize on an inefficiency between the two options. Tuttle had to process the trades over the phone. The consultant was in another room in PDT’s office, methodically reading trade orders to Tuttle. It was a large order, in the tens of millions of dollars.

Tuttle suddenly heard a faint scream somewhere in the office. He looked up and saw the consultant racing down the hall, flailing his arms in the air and screeching, “Stop!
Stoooppp!
Don’t buy, sell,
seeelll!”