Jim Simons wouldn't stop calling.
It was the fall of 1990 and Simons was in his office on the thirty-third floor of a midtown Manhattan high-rise, his eyes glued to a computer screen flashing the latest moves in global financial markets. Friends didn't understand why Simons was still at it. Fifty-two years old, Simons had already lived a full life, enjoying enough adventure, accomplishment, and prosperity to satisfy the ambitions of his peers. Yet, there he was, overseeing an investment fund, sweating the market's daily eruptions.
Simons stood nearly five foot ten, though a slight stoop and a head of graying, thinning hair suggested someone a bit shorter and older. Creases enveloped his brown eyes, the likely result of a smoking habit he couldn't kick—or just didn't want to. Simons's rugged, craggy features, and the glint of mischief in his eyes, reminded friends of the late actor Humphrey Bogart.
On Simons's uncluttered desk sat an oversize ashtray awaiting the next flick of his burning cigarette. On his wall was a rather gruesome painting of a lynx feasting on a rabbit. Nearby, on a coffee table next to a couch and two comfortable leather chairs, sat a complicated mathematics research paper, a reminder of the thriving academic career Simons had discarded to the bewilderment of his fellow mathematicians.
By then, Simons had spent twelve full years searching for a successful investing formula. Early on, he traded like others, relying on intuition and instinct, but the ups and downs left Simons sick to his stomach. At one point, Simons became so discouraged an employee worried he was contemplating suicide. Simons recruited two renowned and headstrong mathematicians to trade with him, but those partnerships crumbled amid losses and acrimony. A year earlier, Simons's results had been so awful he had been forced to halt his investing. Some expected him to pull the plug on his entire operation.
Now on his second marriage and third business partner, Simons decided to embrace a radical investing style. Working with Elwyn Berlekamp, a game theorist, Simons built a computer model capable of digesting torrents of data and selecting ideal trades, a scientific and systematic approach partly aimed at removing emotion from the investment process.
“If we have enough data, I know we can make predictions,”Simons told a colleague.
Those closest to Simons understood what really was driving him. Simons had earned a PhD at the age of twenty-three and then became an acclaimed government code-breaker, a renowned mathematician, and a groundbreaking university administrator. He needed a new challenge and a bigger canvas. Simons told a friend that solving the market's age-old riddle and conquering the world of investing“would be remarkable.”He wanted to be the one to use math to beat the market. If he could pull it off, Simons knew he could make millions of dollars, maybe even more, perhaps enough to influence the world beyond Wall Street, which some suspected was his true goal.
In trading, as in mathematics, it's rare to achieve breakthroughs in midlife. Yet, Simons was convinced he was on the verge of something special, maybe even historic. A Merit cigarette lodged between two fingers, Simons reached for the phone to call Berlekamp one more time.
“Have you seen gold?”Simons asked, the accent of his gravelly voice hinting at his Boston upbringing.
Yes, I've seen gold prices, Berlekamp responded. And, no, we don't need to adjust our trading system. Simons didn't push, hanging up politely, as usual. Berlekamp was becoming exasperated by Simons's pestering, however. Serious and slim with blue eyes behind thick glasses, Berlekamp worked on the other side of the country in an office that was a short walk from the campus of University of California, Berkeley, where he continued to teach. When Berlekamp discussed his trading with graduates of the university's business school, they sometimes mocked the methods he and Simons had embraced, calling them“quackery.”
“Oh, come on. Computers can't compete with human judgment,”one had told Berlekamp.
“We're gonna do things better than humans can,”Berlekamp responded.
Privately, Berlekamp understood why their approach screamed of modern-day alchemy. Even he couldn't fully explain why their model was recommending certain trades.
It wasn't just on campus where Simons's ideas seemed out of touch. A golden age for traditional investing had dawned as George Soros, Peter Lynch, Bill Gross, and others divined the direction of investments, financial markets, and global economies, producing enormous profits with intelligence, intuition, and old-fashioned economic and corporate research. Unlike his rivals, Simons didn't have a clue how to estimate cash flows, identify new products, or forecast interest rates. He was digging through reams of price information. There wasn't even a proper name for this kind of trading, which involved data cleansing , signals, and backtesting , terms most Wall Street pros were wholly unfamiliar with. Few used email in 1990, the internet browser hadn't been invented, and algorithms were best known, if at all, as the step-by-step procedures that had enabled Alan Turing's machine to break coded Nazi messages during World War II. The idea that these formulas might guide, or even help govern, the day-to-day lives of hundreds of millions of individuals, or that a couple of former math professors might employ computers to trounce seasoned and celebrated investors, seemed far-fetched if not outright ludicrous.
Simons was upbeat and confident by nature, though. He detected early signs of success for his computer system, sparking hope. Besides, Simons didn't have a lot of options. His once-thriving venture investments weren't going anywhere, and he sure didn't want to return to teaching.
“Let's work on the system,”Simons told Berlekamp in one more urgent phone call.“Next year, I know, we can be up 80 percent.”
Eighty percent in a year? Now he's really gone too far, Berlekamp thought.
Such enormous returns weren't likely, he told Simons. And you really don't need to call so much, Jim. Simons couldn't stop, though. Eventually, it all became too much—Berlekamp quit, a fresh blow for Simons.
“The hell with it, I'm just going to run it myself,”Simons told a friend.
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Around the same time, in a different part of New York State fifty miles away, a tall, handsome, middle-aged scientist stared at a whiteboard, grappling with his own challenges. Robert Mercer was working in a sprawling IBM research center in a Westchester suburb searching for ways to get computers to do a better job transcribing speech into text and even translate languages, among other tasks. Rather than follow conventional methods, Mercer was tackling his problems with an early form of large-scale machine learning. He and his colleagues were feeding their computers with enough data to enable them to perform tasks on their own. Mercer was nearing his second decade at the computer giant, however, and it still wasn't clear how much he and the team could accomplish.
Colleagues couldn't figure Mercer out, not even those who had spent years working closely with him. Mercer was unusually gifted. He was also odd and socially awkward. Every day for lunch, Mercer ate either a tuna or peanut-butter-and-jelly sandwich packed in a used brown paper bag. Around the office, Mercer constantly hummed or whistled, usually classical tunes, wearing a look of detached amusement.
Much of what came out of Mercer's mouth was brilliant, even profound, though it could also be utterly jarring. Once, Mercer told colleagues he believed he would live forever. The staffers thought he was serious, though historic precedent didn't seem on his side. Later, colleagues would learn of Mercer's deep-seated hostility toward government and of radical political views that would come to dominate his life and affect the lives of many others.
At IBM, Mercer spent long hours huddled with a younger colleague named Peter Brown, a charming, creative, and outgoing mathematician whose dark glasses, thick mane of unruly brown hair, and kinetic energy brought to mind a mad professor. The two men didn't spend much time discussing money or markets. Personal turmoil would lead Mercer and Brown to join forces with Simons, however. His unlikely quest to crack the market's code and lead an investing revolution would become theirs.
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Simons wasn't aware of the imposing obstacles in his way. Nor did he know that tragedy stalked him, or that political upheaval would upend his firm.
Looking out from his office onto the East River that day in the fall of 1990, Simons just knew he had a difficult problem to solve.
“There are patterns in the market,”Simons told a colleague.“I know we can find them.”