My Stock Broker is an ANN

Its seems like Artificial Neural Networks (ANN) are ready to invade the stock markets;

“Artificial intelligence is becoming so deeply integrated into our economic ecostructure that some day computers will exceed human intelligence,” Mr. Kurzweil tells a room of investors who oversee enormous pools of capital. “Machines can observe billions of market transactions to see patterns we could never see.”…

But some are aware that a former Microsoft executive and chairman of the Nasdaq stock market, Michael W. Brown, is an investor in Mr. Kurzweil’s new hedge fund, FatKat, and that Bill Gates once described him as “the best person I know at predicting the future of artificial intelligence.” …

“Five years ago it would have taken $500,000 and 12 people to do what today takes a few computers and co-workers,” said Louis Morgan, managing director of HG Trading, a three-person hedge fund in Wisconsin. “I’m executing 1,500 to 2,000 trades a day and monitoring 1,500 pairs of stocks. My software can automatically execute a trade within 20 milliseconds — five times faster than it would take for my finger to hit the buy button.”

Studies estimate that a third of all stock trades in the United States were driven by automatic algorithms last year, contributing to an explosion in stock market activity. Between 1995 and 2005, the average daily volume of shares traded on the New York Stock Exchange increased to 1.6 billion from 346 million….

For years, computer scientists had tried to help machines perform mundane tasks like reading printed words or telling faces apart. With algorithms similar to those used by stock pickers, programmers created millions of rules designed to tell an “A” from an “a.” But no machine could read a page of text as well as the average child.

So Mr. Kurzweil and others took a different tack: instead of creating sequential rules to instruct a computer to read, they thought, why not create thousands of random rules and let the computer figure out what works?

The result was nonlinear decision making processes more akin to how a brain operates. So-called “neural networks” and “genetic algorithms” have become common in higher-level computer science. Neural networks permit computers to create new rules and automatically change underlying assumptions by experimenting with thousands of random sequences and processes. Genetic algorithms encourage software to “evolve” by letting different rules compete, and combining the most successful outcomes….

But as these new techniques proliferate, some worry that promotion is outpacing reality. These techniques may be better for marketing than stock picking.

“Investment firms fall over themselves advertising their latest, most esoteric systems,” said Mr. Lo of M.I.T., who was asked by a $20 billion pension fund to design a neural network. He declined after discovering the investors had no real idea how such networks work.

“There are some pretty substantial misconceptions about what these things can and cannot do,” he said. “As with any black box, if you don’t know why it works, you won’t realize when it’s stopped working. Even a broken watch is right twice a day.”

Via Information Processing

Related;

The Economist Asks: Are Hedge Funds Necessary?
Inventor Ray Kurzweil on TEDTalks or listen to the podcast
When Genius Failed: The Rise and Fall of Long-Term Capital Management By Roger Lowenstein (book review)

Some posts by Arnold Kling; Nonlinear Thinking, Kurzweil interview, The Age of Radical Enhancement, Why inherited wealth is less important
Kurzweil and Human Capital

Kramnik vs. the computer

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This page contains a single entry by Paul published on November 26, 2006 6:33 AM.

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