《The Man Who Solved The Market》中文版翻译连载44
The MAn Who Solved The Market (47)
Jim Simons’s pulse quickened as he approAChed Sixth Avenue.
It was a sultry summer afternoon, but Simons wore a jacket and tie, hoping to impress. He had his work cut out for him. By 1991, David Shaw and a few other upstarts were using computer models to trade stocks. Those few members of the Wall Street establishment aware of the approach mostly scoffed at it, however. Relying on inscrutable algorithms, as Simons was doing, seemed ludicrous, even dangerous. Some called it black box investing — hard to explain and likely masking serious risk. Huge sums of money were being made the old-fashioned way, blending thoughtful resEArch with honed instincts. Who needed Simons and his fancy computers?
Awaiting Simons in a tall midtown Manhattan office tower was Donald Sussman, a forty-fIVe-year-old Miami native who was something of a heretic on Wall Street. More than two decades earlier, as an undergraduate at Colombia UniveRSIty, Sussman took a leave of absence to work in a small brokerage firm. There, he stumbled upon an obscure strategy to trade convertible bonds, a particularly knotty investment. Sussman convinced his bosses to shell out $2,000 for an early-generation electronic calculator so he could quickly determine which bond was most attractive. Calculator in hand, Sussman made the firm millions of dollars in profits, a windfall that opened his eyes to how technology could render an advantage.
Now the six-foot-three, broad-shouldered, mustachioed Sussman ran a fund called Paloma Partners that was backing Shaw’s rapidly expanding hedge-fund firm, D.E.Shaw. Sussman suspected mathematicians and scientists might one day rival, or even best, the largest trADIng firms, no matter the conventional wisdom in the business. Word was out that he was open to investing in additional computer-focused traders, giving Simons hope he might gain Sussman’s support.
Simons had discarded a thriving academic career to do something special in the investing world. But, after a full decade in the business, he was managing barely more than $45 million, a mere quarter the assets of Shaw’s firm. The meeting had import — backing from Sussman could help Renaissance hire employees, upgrade technology, and become a force on Wall Street.
Sussman had been one of Simons’s earliest investors, but he suffered losses and withdrew his money, an experience that suggested Sussman might be skeptical of his visitor. Simons’s trading algorithms had recently been revamped, however, and he was bursting with confidence. He strode into Sussman’s building, a block from Carnegie Hall, rode an elevator to the thirty-first floor, and stepped into an expansive conference room with panoramic views of Central Park and a large white board for visiting Quants to scribble their equations.
Eyeing Simons across a long, narrow wooden table, Sussman couldn’t help smiling. His guest was bearded, balding, and graying, bearing little resemblance to most of the investors who made regular pilgrimages to his office asking for money. Simons’s tie was slightly askew, and his jacket tweed, a rarity on Wall Street. He came alone, without the usual entourage of handlers and advisors. Simons was just the kind of brainy investor Sussman enjoyed helping.
“He looked like an academic,” Sussman recalls.
Simons began his pitch, relaying how his Medallion hedge fund had refined its approach. Assured and plainspoken, Simons spent more than an hour outlining his firm’s performance, risks, and volatility, and he broadly described his new short-term model.
西蒙斯开始了宣讲，主要讲了他的大奖章波动性，并大致描述了他的新的短期操作模式。基金是如何改善 的。西蒙斯自信又直言不讳，花了一个多小时来介绍公司的业绩、 和
“Now I really have it,” Simons enthused. “We’ve had a breakthrough.”
He asked Sussman for a $10 million investmentin his hedge fund, expressing certainty he could generate big gains and grow Renaissance into a major investment firm.
“I’ve had a revelation,” Simons said. “I can do it in size.”
Sussman listened patiently. He was impressed. There was no way he was giving Simons any money, though. Privately, Sussman worried about potential conflicts of interests, since he was the sole source of capital for Shaw’s hedge fund. He was even helping Shaw’s firm hire academics and traders to extend its lead over Simons and other fledging quantitative traders. If Sussman had cash to spare, he figured, he probably should put it in D.E.Shaw. Besides, Shaw was scoring annual gains of 40 percent. Renaissance didn’t seem to have a shot at matching those gains.
“Why would I give money to a theoretical competitor?” Sussman asked Simons. “I’m sorry, but I already have David.”
They stood up, shook hands, and promised tostay in touch. As Simons turned to leave, Sussman noticed a fleeting look ofdisappointment on his face.
Simons didn’t have much more luck with other potential backers. Investors wouldn’t say it to his face, but most deemed it absurd to rely on trading models generated by computers. Just as preposterous were Simons’s fees, especially his requirement that investors hand over 5 percent of the money he managed for them each year, well above the 2 percent levied by most hedge funds.
“I pay the fees, too,” Simons told one potential investor, noting that he also was an investor in Medallion. “Why shouldn’t you?”
Simons didn’t get very far with that logic; the fees he paid went right back to his own firm, rendering his argument unconvincing. Simons was especially hamstrung by the fact that his fund had fewer than two years of impressive returns.
When a Wall Street veteran named Anita Rival met with Simons in his Manhattan office to discuss an investment from the firm she represented, she became the latest to snub him.
“He wouldn’t explain how the computer models worked,” she recalls. “You couldn’t understand what he was doing.”