Nerds on Wall Street: Math, Machines, and Wired Markets

Chapter 7. A Little AI Goes a Long Way on Wall Street

"If you give someone a program, you will frustrate them for a day; if you teach them how to program, you will frustrate them for a lifetime."

This is a history and technical overview of one of the earliest artificial intelligence (AI) successes in securities trading. In the Introduction, I described the early experiences in the late 1980s at the MIT Artificial Intelligence Laboratory spin-offs LISP Machines and Inference to apply their tools and techniques on Wall Street. Once we stopped blowing air at the subject and tried doing something useful with real market data, it became obvious that the LISP world and Wall Street were far from compatible.

LISP was (and is) an elegant, mathematically pure approach to computation that made for some remarkable feats of programming. My very first exposure to anything from the AI world came in 1971, when I was a newbie at MIT. Up in the truly strange Technology Square AI Lab machine room, filled with humming PDP-10s programmed to push the boundaries of computer science (and to operate the vending machines in the hall), someone showed me Macsyma, the first symbolic math program, developed by Joel Moses. Computers had been doing math in the sense of calculations from the beginning. ENIAC did ballistics. Big science machines did big numerical science problems from nuclear physics to meteorology.^[] In all cases, what was going on was that the formulas were in the program; then the machine read ...