Technology is Revolutionizing Wall Street
With stronger computing power, and other recent technological advances, Wall Street is seeing a revolution in how business is conducted.
Published November 1, 2000
By Fred Moreno and Jill Stolarik
Academy Contributors
Technology’s hand in shaping financial markets is undeniable: tickertape has gone the way of the dodo, everyone in a suit these days seems to be talking on a cell phone, and online brokerages are opening almost as fast as you can point and click. But the technological revolution on Wall Street and in the rest of the world’s markets is merely the beginning, according to a panel assembled by The New York Academy of Sciences (the Academy).
At a seminar scheduled as part of the Academy’s Annual Business Meeting, a panel of three experts identified the impact that information technology and mathematics have had in the marketplace, pinpointed what lies ahead, and issued warnings about what to watch out for on the trading floors of the future.
The increase in speed and efficiency of processing trades in today’s market goes hand in hand with new ways of managing the financial data that informs an investor’s trading decision, said Martin L. Leibowitz, Vice Chairman and Chief Investment Officer of TIAA-CREF, and a former Chairman of the Academy. Traditionally, it was only the select few who were able to obtain information on particular securities, especially bonds.
“Those were the days when traders could afford the time to have three-martini lunches because they had information on all kinds of things that weren’t generally available,” said Leibowitz. “But these days, Bloomberg terminals on traders’ desks keep them apprised of fluctuations in any given market in almost real-time.”
“Pervasive Computing”
That food chain will be getting shorter and broader still according to panelist William R. Pulleyblank director of mathematical sciences at IBM’s T. J. Watson Research Center and director of their Deep Computing Institute, predicts that “pervasive computing” will soon revolutionize the way traders, and even home investors, get their hands on the information they need to make money in the markets.
“We’re about to undergo a transformation in our lives that will be as profound in its effect as the industrial revolution,” said Pulleyblank as he held up a state-of-the-art computer memory card. About one inch square, the card can store 140 megabytes of data and Pulleyblank used it to demonstrate the portability of computing power in the future.
By combining miniature data storage and processing power with space-age eyepieces that project a full-screen image into the eye of the wearer, people will be able to take their virtual Dow Jones terminal wherever they go. Soon, according to Pulleyblank, the notebook computer will be consigned to the bookshelf, as the wearable PC becomes haute couture both on and off the trading floor.
Better Information, and More of It
Not only will the quantity of information reaching investors of the future be greater, it will also be better. There has been an increasing trend on Wall Street toward applying mathematics and statistical models to the analysis of market data, a move away from traditional “value based” decision-making.
“The investment world will become more a creature of the geeks than the martini drinkers,” said James H. Simons, President of Renaissance Technologies Corporation, and past chairman of the Department of Mathematics at the State University of New York at Stony Brook. Using a purely mathematical approach to investing, Simons’ company is not limited by their qualitative understanding of a particular financial instrument in order to invest in it.
“We don’t do value type investing,” said Simons. “We predict the behavior of everything, from currencies, to stocks, to bonds, to foreign stocks.” Simons’ method involves a broad statistical approach. His models are balanced long and short, and predictions do not deviate much from random, making them stable.
“The big advantages of mathematically-based trading is that the quantity of data allows predictions to be made at any scale,” he said.
Powerful predictive models can do more than advise investors of the right decisions to make; they can also let an investor know how to avoid a disaster. The pervasive computing envisioned by IBM’s Pulleyblank, will be supported by “deep computing,” particularly a product under development at IBM called “Deep Green,” named after IBM’s famed chess-playing machine, “Deep Blue.”
“Deep Green”
“Deep Green” is designed to watch financial instruments—stocks, bonds, mortgage derivatives, etc.—and predict whether there is about to be a “disaster” with that particular instrument. It works by examining huge volumes of ticker-like data from previous months and years and relates the rises and falls of any given instrument to various factors that influence the market. These include seasonal fluctuations in price and the type of instrument involved.
With fail-safe statistical models, “Deep Green” machines and instant information via wearable PCs, what kind of a place will the marketplace of the future be?
“If all info were disseminated immediately and all individuals understood it the same way, basically there would be no trading,” mused Leibowitz. Worse still, the markets would also move in erratic jumps as everybody moved to make the same trades their computers told them to make. But this scenario will never occur because, in the unlikely event that the dissemination of information becomes “perfect,” the information itself will never be.
“All this information has an inherent ambiguity,” said Leibowitz.
The Real Danger
The real danger, according to the panel, is not the markets seizing up in an information stalemate, but rather investors becoming too confident in basing decisions on data alone.
Leibowitz calls this overconfidence in data the “airbag effect”—namely, when people think they have something to protect them, they start taking greater risks.
“With all these advantages, the markets still contain a high degree of uncertainty,” he said. The underlying message is not to ignore any source of information, be it statistically derived, the product of “Deep Green,” or something you overheard in a restaurant.
“One should use all the tools available, and access all the information available,” said Leibowitz. “Then you’re in a much better position to make decisions; above all, a little humility is in order.”
