At 9:30 A.M. on August 1, a software executive in a spread-collar shirt and a flashy watch pressed a button at the New York Stock Exchange, triggering a bell that signaled the start of the trading day. Milliseconds after the opening trade, buy and sell orders began zapping across the market's servers with alarming speed. The trades were obviously unusual. They came in small batches of 100 shares that involved nearly 150 different financial products, including many stocks that normally don't see anywhere near as much activity. Within three minutes, the trade volume had more than doubled from the previous week's average.
Soon complex computer programs deployed by financial firms swooped in. They bought undervalued stocks as the unusual sales drove their prices down and sold overvalued ones as the purchases drove their prices up. The algorithms were making a killing, and human traders got in on the bounty too.
Within minutes, a wave of urgent email alerts deluged top officials at the Securities and Exchange Commission. On Wall Street, NYSE officials scrambled to isolate the source of the bizarre trades. Meanwhile, across the Hudson River, in the Jersey City offices of a midsize financial firm called Knight Capital, panic was setting in. A program that was supposed to have been deactivated had instead gone rogue, blasting out trade orders that were costing Knight nearly $10 million per minute. And no one knew how to shut it down. At this rate, the firm would be insolvent within an hour. Knight's horrified employees spent an agonizing 45 minutes digging through eight sets of trading and routing software before they found the runaway code and neutralized it.
By then it was shortly after 10 a.m., and officials from the NYSE, other major exchanges, and the Financial Industry Regulatory Authority were gathering for an emergency conference call. It didn't end until 4 p.m.
In the four years since the collapse of Lehman Brothers drove the global financial system to the brink of oblivion, new technologies have changed Wall Street beyond recognition. Despite efforts at reform, today's markets are wilder, less transparent, and, most importantly, faster than ever before. Stock exchanges can now execute trades in less than a half a millionth of a second—more than a million times faster than the human mind can make a decision. Financial firms deploy sophisticated algorithms to battle for fractions of a cent. Designed by the physics nerds and math geniuses known as quants, these programs exploit minute movements and long-term patterns in the markets, buying a stock at $1.00 and selling it at $1.0001, for example. Do this 10,000 times a second and the proceeds add up. Constantly moving into and out of securities for those tiny slivers of profit—and ending the day owning nothing—is known as high-frequency trading.
This rapid churn has reduced the average holding period of a stock: Half a century ago it was eight years; today it is around five days. Most experts agree that high-speed trading algorithms are now responsible for more than half of US trading. Computer programs send and cancel orders tirelessly in a never-ending campaign to deceive and outrace each other, or sometimes just to slow each other down. They might also flood the market with bogus trade orders to throw off competitors, or stealthily liquidate a large stock position in a manner that doesn't provoke a price swing. It's a world where investing—if that's what you call buying and selling a company's stock within a matter of seconds—often comes down to how fast you can purchase or offload it, not how much the company is actually worth.
As technology has ushered in a brave new world on Wall Street, the nation's watchdogs remain behind the curve, unable to effectively monitor, much less regulate, today's markets. As in 2008, when regulators only seemed to realize after the fact the threat posed by the toxic stew of securitization, the financial whiz kids are again one step—or leap—ahead.
The Knight episode was "a canary in the mine," says Michael Greenberger, a University of Maryland law professor and former regulator at the Commodity Futures Trading Commission (CFTC). "We've been lucky so far that this hasn't been more serious."
Knight wasn't the worst-case scenario. Not even close. A lot of high-frequency trading is done by small proprietary trading firms, subject to less oversight than brand name financial institutions. But big banks have also tried to get in on the act. Imagine a runaway algorithm at a too-big-to-fail company like Bank of America, which manages trillions, not billions, in assets. Or, says Bill Black, a former federal regulator who helped investigate the S&L crisis of the '80s and '90s, imagine trading algorithms causing "a series of cascade failures"—like the domino effect that followed Lehman's collapse. "If enough of these bad things occur at the same time," he says, "financial institutions can begin to fail, even very large ones." It's not a question of whether this will happen, Black warns. "It is a question of when."
Years of mistakes and bad decisions led to the 2008 collapse. But when the next crisis happens, it may not develop over months, weeks, or even days. It could take seconds.
Alpha, New Jersey, is a sleepy hamlet in the Lehigh Valley, near the Delaware River. Somewhere in town (the owners won't say exactly where) is one of 10 2,000-square-foot amplifier facilities that dot the landscape every 75-or-so miles between Chicago and New York City, ensuring that fiber-optic signals travel between the two points as clearly and quickly as possible. Spread Networks, the firm that operates the facility, may have seen some poetry in the community's name—"alpha" is the term investment managers use to describe the performance of an investment after adjusting for risk.
Spread is part of a growing industry dedicated to providing hyperspeed connections for financial firms. A faster trader can sell at a higher price and buy at a lower one because he gets there first. A connection that's just one millisecond faster than the competition's could boost a high-speed firm's earnings by as much as $100 million per year, according to one estimate.
Because of this, trading firms are increasingly pushing the limits to establish the fastest connections between trading hubs like New York, Chicago, and London. Every extra foot of fiber-optic cable adds about 1.5 nanoseconds of delay; each additional mile adds 8 microseconds. That's why companies like Spread have linked financial centers to each other by the shortest routes possible. Spread's Alpha facility is one of more than a dozen similar centers arrayed along the path of its 825-mile-long, $300 million fiber-optic cable between Wall Street and the Chicago Mercantile Exchange. Spread reportedly charges traders as much as $300,000 a month to use its network. Exchanges like the NYSE charge thousands of dollars per month to firms that want to place their servers as close to the exchanges as possible in order to boost transaction speeds. Industry experts estimate that high-speed traders spent well over $2 billion on infrastructure in 2010 alone.
Traders' need for speed has grown so voracious that two companies are currently building underwater cables (price tag: around $300 million each) across the Atlantic, in an attempt to join Wall Street and the London Stock Exchange by the shortest, fastest route possible. When completed in 2014, one of the cables is expected to shave five to six milliseconds off trans-Atlantic trades.
But why stop there? One trading engineer has proposed positioning a line of drones over the ocean, where they would flash microwave data from one to the next like the chain of mountaintop signal fires in The Lord of the Rings. "At what point do you say, 'This is fast enough'?" asks Brent Weisenborn, a former NASDAQ vice president.
The acceleration of Wall Street cannot be separated from the automation of Wall Street. Since the dawn of the computer age, humans have worried about sophisticated artificial intelligence—HAL, Skynet, the Matrix—seizing control. But traders, in their quest for that million-dollar millisecond, have willingly handed over the reins. Although humans still run the banks and write the code, algorithms now make millions of moment-to-moment calls in the global markets. Some can even learn from their mistakes. Unfortunately, notes Weisenborn, "one thing you can't teach a computer is judgment."
One set of signals the programs have to weigh are countless trade orders other algorithms send out and then quickly rescind. There's a fierce debate about what these abortive trades might be. Some speculate they are new algorithms being tested or strategic feints, the equivalent of sonar pings probing the market for a response. Some of the fake trades could be aimed purely at gobbling up bandwidth to slow down competitors. "There are doubtless former [high-speed traders] who could tell us," Black says. "If I worked for the CFTC or the SEC I would be seeking them out to try to learn what was going on."
On the afternoon of May 6, 2010, CNBC viewers could have mistaken the channel's programming for an apocalyptic blockbuster. The Dow, already down 400 points on bad news from Europe, had suddenly plummeted another 600. Erin Burnett, wide-eyed, gesticulated at charts to illustrate the "unprecedented" 1,000-point drop. The typically manic Jim Cramer reached a new level of frenzy, shouting at viewers to buy—BUY!—Procter & Gamble, which had fallen 25 percent, and wagging his finger at the screen: "If that stock is there, you just go and buy it. It can't be there. That's not a real price!"
Prices of nearly every stock and exchange-traded fund had plunged in minutes. Some 300 securities experienced wild gyrations, with trades executed at prices as low as a penny and as high as $100,000 a share. During the same second, shares of the consulting firm Accenture traded at both $0.01 and $30.
In what was later dubbed the "flash crash," nearly $1 trillion in shareholder value was wiped out in a matter of minutes before the market rebounded, eventually closing down 3 percent from the previous day. Almost five months later, regulators would conclude that, on a day when traders had already been shaken by the Greek debt numbers, a single massive sell order executed by an algorithm belonging to a firm in Kansas had triggered a series of knock-on events that sent the market into a tailspin. The analysis portrayed "a market so fragmented and fragile that a single large trade could send stocks into a sudden spiral," the Wall Street Journal reported.
This GIF shows the rise of high-frequency trading in the stock market from January 2007 through January 2012. Source: Nanex.
The flash crash spurred regulators to action—but spurs can only make a horse gallop so fast. No one in Washington makes an extra million bucks a year for moving a millisecond faster, and it shows. So far, Congress and the nation's financial watchdogs have done more hand-wringing than regulating. In classic Washington fashion, when a Senate subcommittee held a hearing in late September on the "rules of the road" for algorithmic trading, the only consensus to emerge was that more hearings were needed.
"Thanks to technology, our securities markets are more efficient and accessible than ever before," then-SEC chair Mary Schapiro said at an October market technology roundtable. "But we also know that technology has pitfalls. And when it doesn't work quite right, the consequences can be severe. Just imagine what can happen if an automated traffic light flashes green rather than red, if a wing flap on a plane goes up rather than down, if a railroad track switches and sends the train right rather than left."