How the Robots Lost: High-Frequency Trading's Rise and Fall

Via Businessweek

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Steve Swanson was a typical 21-year-old computer nerd with a very atypical job. It was the summer of 1989, and he’d just earned a math degree from the College of Charleston. He tended toward T-shirts and flip-flops and liked Star Trek: The Next Generation. He also spent most of his time in the garage of his college statistics professor, Jim Hawkes, programming algorithms for what would become the world’s first high-frequency trading firm, Automated Trading Desk. Hawkes had hit on an idea to make money on the stock market using predictive formulas designed by his friend David Whitcomb, who taught finance at Rutgers University. It was Swanson’s job to turn Whitcomb’s formulas into computer code. By tapping market data beamed in through a satellite dish bolted to the roof of Hawkes’s garage, the system could predict stock prices 30 to 60 seconds into the future and automatically jump in and out of trades. They named it BORG, which stood for Brokered Order Routing Gateway. It was also a reference to the evil alien race in Star Trek that absorbed entire species into its cybernetic hive mind.

Among the BORG’s first prey were the market makers on the floors of the exchanges who manually posted offers to buy and sell stocks with handwritten tickets. Not only did ATD have a better idea of where prices were headed, it executed trades within one second—a snail’s pace by today’s standards, but far faster than what anyone else was doing then. Whenever a stock’s price changed, ATD’s computers would trade on the offers humans had entered in the exchange’s order book before they could adjust them, and then moments later either buy or sell the shares back to them at the correct price. Bernie Madoff’s firm was then Nasdaq’s (NDAQ) largest market maker. “Madoff hated us,” says Whitcomb. “We ate his lunch in those days.” On average, ATD made less than a penny on every share it traded, but it was trading hundreds of millions of shares a day. Eventually the firm moved out of Hawkes’s garage and into a $36 million modernist campus on the swampy outskirts of Charleston, S.C., some 650 miles from Wall Street.

By 2006 the firm traded between 700 million and 800 million shares a day, accounting for upwards of 9 percent of all stock market volume in the U.S. And it wasn’t alone anymore. A handful of other big electronic trading firms such as Getco, Knight Capital Group, and Citadel were on the scene, having grown out of the trading floors of the mercantile and futures exchanges in Chicago and the stock exchanges in New York. High-frequency trading was becoming more pervasive.

The definition of HFT varies, depending on whom you ask. Essentially, it’s the use of automated strategies to churn through large volumes of orders in fractions of seconds. Some firms can trade in microseconds. (Usually, these shops are trading for themselves rather than clients.) And HFT isn’t just for stocks: Speed traders have made inroads in futures, fixed income, and foreign currencies. Options, not so much.

Graphic by Stamen - Graphic: Sixty Seconds of Chaos

Back in 2007, traditional trading firms were rushing to automate. That year, Citigroup (C) bought ATD for $680 million. Swanson, then 40, was named head of Citi’s entire electronic stock trading operation and charged with integrating ATD’s systems into the bank globally.

By 2010, HFT accounted for more than 60 percent of all U.S. equity volume and seemed positioned to swallow the rest. Swanson, tired of Citi’s bureaucracy, left, and in mid-2011 opened his own HFT firm. The private equity firm Technology Crossover Ventures gave him tens of millions to open a trading shop, which he called Eladian Partners. If things went well, TCV would kick in another multimillion-dollar round in 2012. But things didn’t go well.

For the first time since its inception, high-frequency trading, the bogey machine of the markets, is in retreat. According to estimates from Rosenblatt Securities, as much as two-thirds of all stock trades in the U.S. from 2008 to 2011 were executed by high-frequency firms; today it’s about half. In 2009, high-frequency traders moved about 3.25 billion shares a day. In 2012, it was 1.6 billion a day. Speed traders aren’t just trading fewer shares, they’re making less money on each trade. Average profits have fallen from about a tenth of a penny per share to a twentieth of a penny.

According to Rosenblatt, in 2009 the entire HFT industry made around $5 billion trading stocks. Last year it made closer to $1 billion. By comparison, JPMorgan Chase (JPM) earned more than six times that in the first quarter of this year. The “profits have collapsed,” says Mark Gorton, the founder of Tower Research Capital, one of the largest and fastest high-frequency trading firms. “The easy money’s gone. We’re doing more things better than ever before and making less money doing it.”

“The margins on trades have gotten to the point where it’s not even paying the bills for a lot of firms,” says Raj Fernando, chief executive officer and founder of Chopper Trading, a large firm in Chicago that uses high-frequency strategies. “No one’s laughing while running to the bank now, that’s for sure.” A number of high-frequency shops have shut down in the past year. According to Fernando, many asked Chopper to buy them before going out of business. He declined in every instance.

One of HFT’s objectives has always been to make the market more efficient. Speed traders have done such an excellent job of wringing waste out of buying and selling stocks that they’re having a hard time making money themselves. HFT also lacks the two things it needs the most: trading volume and price volatility. Compared with the deep, choppy waters of 2009 and 2010, the stock market is now a shallow, placid pool. Trading volumes in U.S. equities are around 6 billion shares a day, roughly where they were in 2006. Volatility, a measure of the extent to which a share’s price jumps around, is about half what it was a few years ago. By seeking out price disparities across assets and exchanges, speed traders ensure that when things do get out of whack, they’re quickly brought back into harmony. As a result, they tamp down volatility, suffocating their two most common strategies: market making and statistical arbitrage.

Market-making firms facilitate trading by quoting both a bid and a sell price. They profit off the spread in between, which these days is rarely more than a penny per share, so they rely on volume to make money. Arbitrage firms take advantage of small price differences between related assets. If shares of Apple (AAPL) are trading for slightly different prices across any of the 13 U.S. stock exchanges, HFT firms will buy the cheaper shares or sell the more expensive ones. The more prices change, the more chances there are for disparities to ripple through the market. As things have calmed, arbitrage trading has become less profitable.

To some extent, the drop in volume may be the result of high-frequency trading scaring investors away from stocks, particularly after the so-called Flash Crash of May 6, 2010, when a big futures sell order filled by computers unleashed a massive selloff. The Dow Jones industrial average dropped 600 points in about five minutes. As volatility spiked, most high-frequency traders that stayed in the market that day made a fortune. Those that turned their machines off were blamed for accelerating the selloff by drying up liquidity, since there were fewer speed traders willing to buy all those cascading sell orders triggered by falling prices.

For two years, the Flash Crash was HFT’s biggest black eye. Then last August, Knight Capital crippled itself. Traders have taken to calling the implosion “the Knightmare.” Until about 9:30 a.m. on the morning of Aug. 1, 2012, Knight was arguably one of the kings of HFT and the largest trader of U.S. stocks. It accounted for 17 percent of all trading volume in New York Stock Exchange (NYX)-listed stocks, and about 16 percent in Nasdaq listings among securities firms.

When the market opened on Aug. 1, a new piece of trading software that Knight had just installed went haywire and started aggressively buying shares in 140 NYSE-listed stocks. Over about 45 minutes that morning, Knight accidentally bought and sold $7 billion worth of shares—about $2.6 million a second. Each time it bought, Knight’s algorithm would raise the price it was offering into the market. Other firms were happy to sell to it at those prices. By the end of Aug. 2, Knight had spent $440 million unwinding its trades, or about 40 percent of the company’s value before the glitch.