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While the SEC is busy investigating Goldman Sachs, it might want to look into another Goldman-dominated fraud: computerized front running using high-frequency trading programs.
Market commentators are fond of talking about “free market capitalism,” but according to Wall Street commentator Max Keiser, it is no more. It has morphed into what his TV co-host Stacy Herbert calls “rigged market capitalism”: all markets today are subject to manipulation for private gain.
Also called High Frequency Trading (HFT) or “black box trading,” automated program trading uses high-speed computers governed by complex algorithms (instructions to the computer) to analyze data and transact orders in massive quantities at very high speeds. Like the poker player peeking in a mirror to see his opponent’s cards, HFT allows the program trader to peek at major incoming orders and jump in front of them to skim profits off the top. Note that these large institutional orders are our money — our pension funds, mutual funds, and 401Ks.
"Nearly everyone on Wall Street is wondering how hedge funds and large banks like Goldman Sachs are making so much money so soon after the financial system nearly collapsed," writes the New York Times' Charles Duhigg in a front page piece that’s been the talk of the town in New York and Washington. "High-frequency trading is one answer." Duhigg writes, “High-frequency trading systems are so fast they can outsmart or outrun other investors, humans and computers alike."
There are several possibilities about what’s going on here. One is that Goldman and others are literally using privileged information to make trades ahead of markets, in which case they are committing a felony. Specifically, this is known as "front-running," or trading ahead of customers, and it is an explicitly illegal form of market manipulation.
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.”
Some sophisticated hedge funds such as Renaissance Technologies LLC, based in East Setauket, N.Y., are said to have deployed AI to invest. But for years, these firms were the exception. Some firms that have dabbled in AI are skeptical it is anywhere close to working.
Rebellion is part of a new wave of firms using machine learning to trade. Cerebellum Capital, a San Francisco hedge fund with $10 million in assets, started using machine learning to invest in 2009. A number of high-frequency trading firms, such as RGM Advisors LLC in Austin, Texas, and Getco LLC in Chicago, are using machine learning to help their computer systems trade in and out of stocks efficiently, according to people familiar with the firms.