Collective Intellect Inc., a Boulder, Colorado-based startup, already employs basic NLP programs to comb through 55 million Web logs and turn up information that might make money for hedge funds. “There’s some nuggets of wisdom in the sea,” says Collective Intellect chief technology officer Tim Wolters.
The hope is that these systems will ape living neurons, think like people and, like traders, understand that some things are neither black nor white but rather in varying shades of gray. The computers have done well. A November 2005 study by Darien, Connecticut-based Casey, Quirk & Associates, an investment management consulting firm, says that from 2001 to 2005, big-cap US stock funds run by quants beat those run by nonquants.
Quants rise
The quants posted a median annualized return of 5.6%, while nonquants returned an annualized 4.5%. Both groups beat the Standard & Poor’s 500 Index, which returned an annualized negative 0.5% during that period.
Rex Macey, director of equity management at Wilmington Trust Corp. in Atlanta, says computers can mine data and see relationships that humans can’t. Quantitative investing is on the rise, and that’s bound to spur interest in AI, says Macey, who previously developed computer models at Marietta, Georgia-based American Financial Advisors LLC, to weigh investment risk and project clients’ wealth. “It’s all over the place and, greed being what it will, people will try anything to get an edge,” Macey, 46, says. “Quant is everywhere, and it’s seeping into everything.”
AI proponents are positioning themselves to become Wall Street’s hyperquants. Kearns, who previously ran the quant team within the equity strategies group at Lehman Brothers, splits his time between the University of Pennsylvania in Philadelphia, where he teaches computer science, and the New York investment bank, where he tries to put theory into practice.
Inside Lehman
Neither he nor Lehman executives would discuss how the firm uses computers to trade, saying the programs are proprietary and that divulging information about them would cost the firm its edge in the markets. At Lehman, Kearns is the big thinker on AI. He leaves most of the actual programming to a handful of Ph.D.s, most of whom he’s recruited at universities or computer conferences.
Kearns himself was plucked from Penn. Ian Lowitt, who studied with Kearns at the University of Oxford and is now co-chief administrative officer of Lehman Brothers, persuaded him to come to the firm as a consultant in 2002.
Kearns hardly looks the part of a professor. He has closely cropped black hair and sports a charcoal gray suit and a crisp blue shirt and tie. At Penn, his students compete to design trading strategies for the Penn-Lehman Automated Trading Project, which uses a computerized trading simulator.
Kearns says AI’s failure to live up to its sci-fi hype has created many doubters on Wall Street. He says people should be sceptical: Trading requires institutional knowledge that is difficult, if not impossible, to program into a computer.
Chasing dreams: Lehman Brothers’ Michael Kearns, a computer scientist, poses at the University of Pennsylvania
AI holds perils as well as promise for Wall Street, Kearns says. Right now, even sophisticated AI programs lack common sense, he says.