A Wall Street Journal reporter evaluates the cost and consequences of high-speed trading, arguing that the development of automatic, super-intelligent trading machines is eliminating necessary human interests and compromising regulation measures. 50,000 first printing.
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SCOTT PATTERSON is a staff reporter at the Wall Street Journal, covering government regulation from the nation's capital.
Chapter One
Trading Machines
A rising winter sun cast pale golden light into the otherwise dark and quiet office in downtown Stamford, Connecticut. Haim Bodek, the founder of Trading Machines LLC, squinted at the light through red-thatched eyes and returned his gaze to a stack of five flat-screens on his desk. The only sound in the room was the low hum of dozens of Dell computer towers and several Alienware Area-51 gaming computers.
The sound of the Machine.
It was December 2009. Bodek hadn’t been up all night swilling fine wines and schmoozing with deep-pocketed clients at four-star restaurants in Manhattan. He didn’t need to. His firm traded for its own account, and Bodek answered only to himself and to a few wealthy partners who’d bankrolled the firm.
He wouldn’t have it any other way. No twitchy investors pulling cash every time the market dipped. And no prying questions about the state-of-the-art Machine he’d created.
No one knew how the Machine worked but Bodek.
But now the Machine wasn’t working. Even worse, Bodek wasn’t sure why. That’s why he’d been up all night. If he didn’t solve the problem, it could destroy Trading Machines--and his career.
What made the Machine tick was a series of complex algorithms that collectively reflected a two decades’ tradition of elite trading strategies. Bodek had personally designed the algos using a branch of artificial intelligence called expert systems. The approach boiled down the knowledge gained by experts in market analysis and crunched incoming market data in order to make incredibly accurate predictions. It combined various models that financial engineers had used over the years to price options--contracts that give the holder the “option” to buy or sell a stock at a particular price within a certain time frame--with new twists on strategies that savvy traders had once used to -haggle over prices in the pits.
But many of those old-school strategies, geared with cutting-edge AI upgrades that permitted them to compete head-to-head in the electronic crowd, were nearly unrecognizable now. The market had entered a phase of such rapid mind-throttling change that even the most advanced traders were in a fog.
The problem that threatened Trading Machines, Bodek believed, was a bug hidden in the data driving his ranks of algos, hundreds of thousands of lines of code used by the computer-driven trading outfit that he’d launched with sky’s-the-limit dreams in late 2007. The code told the Machine when to trade, what to trade, and how to trade it, all with split-second timing.
Bodek, whose seriously pale skin, high forehead, and piercing blue eyes gave him the appearance of a Russian chess master, was a wizard of data. It was the air he breathed, the currency of his profession. An expert in artificial intelligence, he’d made a career of crunching masses of numbers, finding form inside chaos. To discover order in the ocean of information that made up the market required incredible computer power and ingenious trading systems.
Bodek had both. He was so skilled at discovering patterns in the market’s daily ebb and flow that he’d risen to the top of the trading world, working first at an elite Chicago firm, packed with math and physics Ph.D.s, called Hull Trading, then inside an elite quantitative derivatives operation at Goldman Sachs, before taking over a powerful global desk at UBS, the giant Swiss bank. In 2007, he broke out on his own and convinced twenty-five top-notch traders, programmers, and quants (an industry term for mathematicians who use quantitative techniques to predict markets) from across Wall Street to join him. He set up shop in Stamford and launched Trading Machines just as signs emerged of an impending global financial crisis. It had amounted to one of the most ambitious trading projects outside a large investment bank in years.
Despite the bad timing, Trading Machines had fared well in its debut, posting a tidy profit during a time when most of Wall Street was imploding.
Then something went wrong with the Machine. Bodek was on a mission to fix it. Whatever it was.
As the morning progressed, Bodek’s team of traders and programmers filed into Trading Machines’ third-floor office space. They stepped gingerly around Bodek as if he were a hair-trigger land mine.
The slightest pressure could set off an explosion. Not of anger--Bodek was as levelheaded as a fighter pilot--but of talk. Bodek was a legendary talker, a deep well of stories and analogies and long digressions and digressions on digressions. His was a mind trained to focus on minutiae, and it could be exhausting for listeners exposed to its relentless probing, like a powerful searchlight that never stopped sweeping the ground for new information. He could rarely get far into a conversation before he would say with extreme urgency something along the lines of “What I’m trying to say is there are five points I need to make before we can address the first of those ten points I mentioned earlier.” Inside the firm, this was known as “getting Haimed.”
Bodek wasn’t in the mood to talk that morning. His eyes darkly circled, he sat frozen in his chair, staring at his stacked monitors, mumbling to himself in fits and starts, his hands rising on occasion from his keyboard to pincer his blade-shaved head above the ears as if he were trying to squeeze more juice from his sleep-deprived brain. All the stress had taken a toll. While he was just thirty-eight years old, he appeared a good decade older.
Bodek’s entire Wall Street career, from Hull to Goldman Sachs to his own trading desk at UBS, had been one long march from victory to victory. Whenever faced with an obstacle no one thought he could overcome, he’d pull off a miracle. Failure had never seemed possible.
And yet here it was. He could see it, there, on his five screens, in the data that tallied up the firm’s dwindling profits. As Bodek sat there, mystified by the behavior of an electronic trading ecosystem he’d helped invent, he focused his formidable brain power on figuring out what the hell was going on.
The answer that would solve his problems was also there, he thought, on those screens, hiding amid all the data.
But where?
Shortly before 9 a.m., Bodek’s partner, Thong-Wei Koh, a six-foot-two crack mathematician from Singapore, took his seat a few desks away from Bodek. The two founders didn’t exchange a word. They’d been fighting tooth and nail for the past few months. A partnership that had started with visions of glory had descended into a bitter daily feud.
TW was obsessed with mastering risk. At UBS, he’d designed a trading system so ingenious that it could never lose a large amount of money--at least according to the math. But now, at Trading Machines, risk was everywhere. He was drowning in it. He’d become so stressed out by the firm’s problems that he’d come down with chronic stomach cramps. Bodek, for his part, was wracked by headaches and insomnia.
He began to stir out of his morning torpor as the start of the trading day neared. It was 9:15 a.m.
Time for the War Song.
Bodek plugged his iPod into a dock and pressed the play button. Pounding electric guitar chords screeched from the dock’s speakers: the manic Viking heavy metal he loved--and everyone else in the room loathed. As a teenager, Bodek had played drums in a thrash band. Ever since, his taste in music had gone one way: loud, angry, violent.
He was trying to teach his team a lesson with the music. It was how he viewed trading: It was war. Us against them. The market was the field of battle. The weapons: brains...
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