New York: Way up in a New York skyscraper, inside the headquarters of Lehman Brothers Holdings Inc., Michael Kearns is trying to teach a computer to do something other machines can’t: think like a Wall Street trader.
In his cubicle overlooking the trading floor, Kearns, 44, consults with Lehman Brothers traders as Ph.D.s tap away at secret software. The programs they’re writing are designed to sift through billions of trades and spot subtle patterns in world markets.
Kearns, a computer scientist who has a doctorate from Harvard University, says the code is part of a dream he’s been chasing for more than two decades: to imbue computers with artificial intelligence, or AI.
His vision of Wall Street conjures up science fiction fantasies of HAL 9000, the sentient computer in 2001: A Space Odyssey. Instead of mindlessly crunching numbers, AI-powered circuitry one day will mimic our brains and understand our emotions—and outsmart human stock pickers, he says.
“This is going to change the world, and it’s going to change Wall Street,” says Kearns, who spent the 1990s researching AI at Murray Hill, New Jersey-based Bell Laboratories, birthplace of the laser and the transistor.
Human-intelligent: Vasant Dhar, a former Morgan Stanley quant, at New York University's Stern School of Business in New York, where he now teaches
As finance Ph.D.s, mathematicians and other computer-loving disciples of quantitative analysis challenge traditional traders and money managers, Kearns and a small band of AI scientists have set out to build the ultimate money machine.
For decades, investment banks and hedge-fund firms have employed quants and their computers to uncover relationships in the markets and exploit them with rapid-fire trades.
Investment prospects
Quants seek to strip human emotions such as fear and greed out of investing. Today, their brand of computer-guided trading has reached levels undreamed of a decade ago. A third of all US stock trades in 2006 were driven by automatic programs, or algorithms, according to Boston-based consulting firm Aite Group LLC. By 2010, that figure will reach 50%, according to Aite.
AI proponents say their time is at hand. Vasant Dhar, a former Morgan Stanley quant who teaches at New York University’s Stern School of Business in Manhattan’s Greenwich Village, is trying to program a computer to predict the ways in which unexpected events, such as the sudden death of an executive, might affect a company’s stock price.
To believers such as Dhar and Kearns, all of this is only the beginning. One day, a subfield of AI known as machine learning, Kearns’s speciality, may give computers the ability to develop their own smarts and extract rules from massive data sets. Another branch, called natural language processing, or NLP, holds out the prospect of software that can understand human language, read up on companies, listen to executives and distil what it learns into trading programs.