Wall Street is notorious for not learning from its mistakes. Maybe machines can do better.
That is the hope of an increasing number of investors who are turning to the science of artificial intelligence to make investment decisions.
With artificial intelligence, programmers don’t just set up computers to make decisions in response to certain inputs. They attempt to enable the systems to learn from decisions, and adapt. Most investors trying the approach are using “machine learning,” a branch of artificial intelligence in which a computer program analyzes huge chunks of data and makes predictions about the future. It is used by tech companies such as Google Inc. to match Web searches with results and NetFlix Inc. to predict which movies users are likely to rent.
One upstart in the AI race on Wall Street is Rebellion Research, a tiny New York hedge fund with about $7 million in capital that has been using a machine-learning program it developed to invest in stocks. Run by a small team of twentysomething math and computer whizzes, Rebellion has a solid track record, topping the Standard & Poor’s 500-stock index by an average of 10% a year, after fees, since its 2007 launch through June, according to people familiar with the fund. Like many hedge funds, its goal is to beat the broader market year after year.
“It’s pretty clear that human beings aren’t improving,” said Spencer Greenberg, 27 years old and the brains behind Rebellion’s AI system. “But computers and algorithms are only getting faster and more robust.”