Dark Pools The Rise of the Machine Traders.pdf

Dark Pools The Rise of the Machine Traders.pdf - ALSO BY...

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Unformatted text preview: ALSO BY SCOTT PATTERSON THE QUANTS How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It Copyright © 2012 by Scott Patterson All rights reserved. Published in the United States by Crown Business, an imprint of the Crown Publishing Group, a division of Random House, Inc., New York. CROWN BUSINESS is a trademark and CROWN and the Rising Sun colophon are registered trademarks of Random House, Inc. Library of Congress Cataloging-in-Publication Data Patterson, Scott, 1969–. Dark pools : high-speed traders, AI bandits, and the threat to the global financial system / by Scott Patterson. — 1st ed. p. cm. 1. Electronic trading of securities. 2. Online stockbrokers. I. Title. HG4515.95.P284 2012 332.640973—dc23 2012003096 eISBN: 978-0-307-88719-1 Jacket design by Laura Duffy Jacket photography: (swirl) Design Pics/Ryan Briscall; (numbers) Mark Segal v3.1 For Eleanor Had there been full disclosure of what was being done in furtherance of these schemes, they could not long have survived the fierce light of publicity and criticism. Legal chicanery and pitch darkness were the banker’s stoutest allies. —FERDINAND PECORA CONTENTS Cover Other Books by This Author Title Page Copyright Dedication Epigraph PROLOGUE: LIGHT POOL PART I: MACHINE V. MACHINE 1: TRADING MACHINES 2: THE SIZE GAME 3: ALGO WARS 4: O+ PART II: BIRTH OF THE MACHINE 5: BANDITS 6: THE WATCHER 7: MONSTER KEY 8: THE ISLAND 9: THE GREEN MACHINE 10: ARCHIPELAGO 11: EVERYONE CARES 12: PALACE COUP 13: BAD PENNIES 14: DUMB MONEY 15: TRADE BOTS 16: CRAZY NUMBERS 17: “I DO NOT WANT TO BE A FAMOUS PERSON” PART III: TRIUMPH OF THE MACHINE 18: THE BEAST 19: THE PLATFORM 20: PANIC TICKS 21: VERY DANGEROUS PART IV: FUTURE OF THE MACHINE 22: A RIGGED GAME 23: THE BIG DATA 24: ADVANCED CHESS 25: STAR Acknowledgments Notes About the Author PROLOGUE LIGHT POOL L oudspeakers boomed Eminem’s hit single “Without Me” as Dan Mathisson stepped onto a low-slung dais in the Glitter Room of Miami Beach’s exclusive Fontainebleau Hotel. Greeting Mathisson: the applause of hundreds of hedge fund managers, electronic traders, and computer programmers, the driving force behind a digital revolution that had radically transformed the United States stock market. They had descended on the Fontainebleau for the annual Credit Suisse Equity Trading Forum to rub elbows, play golf, swap rumors, and bask in the faded glory of the hotel where stars such as Frank Sinatra, Elvis Presley, and Marlene Dietrich had once sipped cocktails and lounged in private poolside cabanas. Smartly clad in a light blue cotton shirt and charcoal-gray suit, sans tie, a soft pink Credit Suisse logo illuminated on the wall behind him, Mathisson was pumped. He loved the Miami Beach conference. Over the years, it had become the Woodstock of electronic trading. Closed to the press, the March 10, 2011, gathering was a private congress of wealthy market wonks who’d created a fantastic Blade Runner trading world few outsiders could imagine, a worldwide matrix of dazzlingly complex algorithms, interlinked computer hubs the size of football fields, and high-octane trading robots guided by the latest advances in artificial intelligence. Mathisson was an alpha male of the electronic pack. In another life, the bespectacled five-seven onetime trader would have been teaching students quantum physics or working for Mission Control at NASA. Instead, starting in 2001, he’d devoted himself to building a space-age trading platform for Credit Suisse called Advanced Electronic Systems. He was an elite market Plumber, an architect not of trading strategies or moneymaking schemes but of the pipes connecting the various pieces of the market and forming a massive computerized trading grid. Plumbers such as Mathisson had become incredibly powerful in recent years. Knowledge of the blueprints behind the market’s plumbing had become extremely valuable, worth hundreds of millions of dollars to those in the know. The reason: A new breed of trader had emerged who focused on gaming the plumbing itself, exploiting complex loopholes and quirks inside the blueprints like card counters ferreting out weaknesses in a blackjack dealer’s hand. Mathisson was keenly aware of this. Since launching AES, he’d been a firsthand witness of the powerful computer-driven forces that had irrevocably altered the face of the stock market. He’d created AES’s original matching engine—the computer system that matched buy and sell orders—which by early 2011 accounted for a whopping 14 percent of U.S. stock-trading volume, nearly one billion shares a day. He was the brains behind Guerilla, the first mass-marketed robot-trading algorithm that could deftly buy and sell stocks in ways that evaded the detection of other algos, a lethal weapon in the outbreak of what became known as the Algo Wars. Operating in forty countries across six continents, AES was a moneymaking machine. In 2008, a year when most of Wall Street was single-mindedly engaged in the act of self-destructing, AES had pulled in about $800 million, making it the most profitable arm of Credit Suisse. That number—that $800 million—was just one reason among many why Mathisson’s words on that Miami Beach stage meant serious business. But while the Miami confabs had always been about business, they were also about celebrating, and they typically involved a conga line of cocktail parties, pool parties, and dance clubs. In years past, after the day’s long string of speeches and presentations, Mathisson’s right-hand man, a charismatic, larger-than-life sales machine named Manny Santayana, would troll the local clubs, pick out the best-looking local girls, and tell them about the real party packed with millionaire traders looking for a good time. Santayana always joked that he never threw parties. He threw networking events at a socially accelerated pace. Santayana was king of the socially accelerated pace. He ran poker tournaments for traders in the exclusive Grand Havana Room in Manhattan, dinners for bankers at the Versace Mansion in Miami Beach. All year long, there were networking events at a socially accelerated pace around the world—in Tokyo, Singapore, Zurich, London, Oslo, Paris, Hong Kong. But an iron rule on Wall Street is that every party leads to the inevitable hangover. As Mathisson looked out over the audience, he knew Santayana wouldn’t be trolling clubs for bleach-blond babes this year. A freakish stock market crash on May 6, 2010—the so-called Flash Crash—had revealed that the computer-driven market was far more dangerous than anyone had realized. Regulators were angry, fund managers furious. Something had gone dramatically wrong. Senators were banging down Mathisson’s door wanting to know what the hell was going on. A harsh light was shining on an industry that had grown in the shadows. Mathisson was ready to confront the attack. He hit a button on the remote for his PowerPoint presentation. A graph appeared. A jagged line took a cliff-like plunge followed by a sharp vertical leap. It looked like a tilted V, the far righthand side just lower than the left. “There’s the Flash Crash,” he said. “We all remember that day, of course.” The chart showed the Dow Jones Industrial Average, which took an eighthundred-point swan dive in a matter of minutes on May 6 due to glitches deep in the plumbing of the nation’s computer-trading systems—the very systems built and run by many of the people sitting in the Glitter Room. The audience stirred. The Flash Crash was a downer, and they were restless. It was going to be a long day full of presentations. Later that night, they’d be treated to a speech by the Right Honorable Gordon Brown, former prime minister of the United Kingdom. Ex–Clinton aide James Carville would address the group the following morning. (It was nothing unusual. Past keynote speakers at the conference had included luminaries such as former Federal Reserve chairman Alan Greenspan, former secretary of state Colin Powell, and the onetime junkbond king Michael Milken.) Mathisson hit the button, calling up a chart showing that cash had flowed out of mutual funds every single month through 2010, following the Flash Crash. Legions of regular investors had become fed up, convinced the market had become either far too dangerous to entrust with their retirement savings, or just outright rigged to the benefit of an elite technorati. “This is pretty damning,” Mathisson said soberly, noting that the outflows continued even as the market surged higher later in the year. “Even with a historic rally, mutual fund outflows continued through December. This is cause for concern in the U.S.” Mathisson hit the button. A grainy photo of President Barack Obama appeared, along with his notorious quote from a December 2009 episode of 60 Minutes: “I did not run for office to be helping out a bunch of fat cat bankers on Wall Street.” Mathisson’s point was clear: The feds are going to come down on this industry like a sledgehammer if we don’t fix the system from within, fast. “We have to do something,” he said. The heart of the problem, Mathisson explained, was that fast-moving robot trading machines were front-running long-term investors on exchanges such as the New York Stock Exchange and the Nasdaq Stock Market. For instance, if Fidelity wanted to buy a million shares of IBM, the Bots could detect the order and start buying IBM themselves, in the process driving up the price and making IBM more expensive. If Fidelity wanted to sell a million shares of IBM, the Bots would also sell, pushing the price down and causing Fidelity to sell on the cheap. To escape, the victims of the front running were turning to dark pools. “Why are people choosing to send orders to dark pools instead of the displayed markets?” Mathisson asked his audience. “They’re choosing dark pools because of a problem in the lit markets.” A controversial force in the market in the 2000s, dark pools were private markets hidden from investors who traded on the “lit” pools such as the NYSE and Nasdaq (in the industry, any venue where trading takes place, including an exchange, is known as a pool). Large traders used dark pools like a cloaking device in their efforts to hide from robo algos programmed to ruthlessly hunt down their intentions like single-minded Terminators on exchanges. But unlike exchanges, dark pools were virtually unregulated. And the blueprints for how they worked were a closely guarded secret. As such, there were highly paid people on Wall Street, often sporting Ph.D.s in fields such as quantum physics and electrical engineering, who did nothing all day long but try to divine those secrets and ruthlessly exploit them. The new wave of dark pools epitomized a driving force in finance as old as time: secrecy. In part a solution to a problem, they were also the symptom of a disease. The lit market had become a playground for highly sophisticated traders —many of the very traders sitting in Mathisson’s audience—who’d designed and deployed the robo algos that hacked the market’s plumbing. Sadly, the exchanges had helped make all of this possible. They provided to the high-speed trading firms expensive, data-rich feeds that broadcast terabytes of information about specific buy and sell orders from giant mutual funds to the Bot algos. So much information that it could be used to engage in the hit-and-run tactics regulators, fund managers, and senators were screaming about. This was all playing out every day, every nanosecond, in the lit markets—a frenzied dance of predator and prey, with Mathisson’s peers playing the part of the swarming piranha. Every single investor in the United States was involved—and at risk. Mathisson was all too aware of this dynamic. Indeed, in 2004, he’d created a dark pool of his own called Crossfinder. It was so successful that it had gone on to become the largest dark pool in the world. By 2011, roughly 10 to 15 percent of all trading took place in dark pools, and Crossfinder accounted for a significant chunk of that volume. Why? The exchanges had gotten in bed with the Bots. Now investors were fed up, Mathisson argued. “The policies of today’s exchanges cater to the needs of high-volume, shortterm opportunistic traders,” he said. “The pick-off artists.” The audience visibly tensed. To an outsider, Mathisson’s statement would have seemed relatively innocuous. To the insiders—those sitting in the room—it was a shocker. It was an outrage. It wasn’t what Mathisson said. Others had been attacking the speed Bots. What was shocking was that Dan Mathisson was saying it. Mathisson, one of the architects of the electronic system itself, one of the elite Plumbers—he was trashing it. Pick-off artists! Mathisson knew what he was talking about. Because the dirty little secret of most dark pools was that they relied on those very same pick-off traders he was trashing. Indeed, they’d been AES’s bread and butter for years. In Wall Street parlance, the Bots helped provide the liquidity behind the massive AES pool, the rivers of buy and sell orders the turtle-slow average traders—the mutual funds, the pension funds—relied on when they wanted to buy or sell a stock. While Credit Suisse monitored Crossfinder for manipulative Bot behavior, it still depended on the Bots’ steady flow. Mathisson’s promise to clients running away from the Bots in the lit pools was that over-the-top hit-and-run gaming activity would be kept to a minimum. Egregious violators were kicked out of the pool. But there was little he could do to entirely stop it. In short, the dark pools themselves were swarming with predator algos. The dynamic spoke to how powerful the Bots had become. And there was no place to hide. Mathisson’s kind of straight talk was not heard on Wall Street unless something very troubling was going on behind the scenes. He knew that regulators were zeroing in on the industry. He wanted to be ready. Mathisson laid out his case. Before electronic trading came along in the 1990s, most markets operated on a floor. Market makers—the people who buy and sell all day long on behalf of investors, collecting a small slice of the deal for their troubles—were able to sense which way the market was going simply by looking around them, staring into the nervous eyes of another trader, watching a competitor frantically rush into a pit and start selling—or buying. General Electric is in trouble. IBM is about to surge. With electronic trading, a placeless, faceless, postmodern cyber-market in which computers communicated at warpspeeds, that physical sense of the market’s flow had vanished. The market gained new eyes—electronic eyes. Computer programmers designed hunter-seeker algorithms that could detect, like radar, which way the market was going. The big game in this hunt became known as a whale—an order from a leviathan fund company such as Fidelity, Vanguard, or Legg Mason. If the algos could detect the whales, they could then have a very good sense for whether a stock was going to rise or fall in the next few minutes or even seconds. They could either trade ahead of it or get out of its way. The bottom line: Mom and Pop’s retirement accounts were full of mutual funds handing over billions of dollars a year to the Bots. Dark pools like Crossfinder had (for a while at least) evened the game in the Algo Wars, giving traditional investors a place to hide. But the evidence was now all too clear: The Bots in their relentless quest for the whales had thoroughly infiltrated the dark pools. And it was all cloaked in the darkness of a market mired in complexity and electronic smoke screens. Mathisson, for his part, had decided to fight back. To beat the speed traders at their own game, in 2009 he’d launched a turbocharged trading algorithm called Blast. Blast pounded its fleet-footed high-speed opponents with simultaneous buy and sell orders like a machine gun. The firepower of Blast was so overwhelming that it forced high-speed traders—who controlled upwards of 70 percent or more of all stock-market volume by the late 2000s—to cut bait and run for cover. Blast was effective. But Mathisson needed more. Now Mathisson had a new weapon in his arsenal. He wasn’t attacking the very firms that had been AES’s meal ticket for nothing. He had an angle: yet another extraordinary machine. He called it Light Pool. Light Pool would weed out the “opportunistic” traders, he told the audience. Using metrics that could detect the pick-off artists, Light Pool would provide a clean market where natural traders—investors who actually wanted to buy a stock and hold it for longer than two seconds—could meet and do business. The information about buy and sell orders inside Light Pool wouldn’t be distributed through a private feed. It would go directly to the consolidated tape that all investors could see, not just the turbo traders who paid for the high-bandwidth feeds from the exchanges. “All those sleazy hidden order types won’t be there,” Mathisson said. “We’ll create criteria like ‘Are you a pick-off artist?’ This is effectively going to eliminate the pick-off flow. We’re going to be transparent.” Mathisson looked meaningfully at the audience—packed with the very pick-off artists he was attacking—and said something he knew would get their attention. “There will be no black box.” MATHISSON knew, of course, that he was fighting against time, and he secretly worried that there was nothing he could do to close the Pandora’s box that had been opened in the past decade. The Plumbers had always believed that a problem with the machine could be fixed with a better machine. But what if the problem wasn’t inside the machine? What if it was the all-toohuman arms race itself, a race that had gripped the market and launched it on an unstoppable and completely unpredictable path? Because with inscrutable algos blasting away across high-speed electronic networks around the world, with trading venues splintering into dozens of pieces, with secretive trading firms spreading their tentacles across the globe, the entire market had descended into one vast pool of darkness. It wasn’t only the everyday investors who were in the dark—even the architects of the system itself, the Plumbers, were losing the ability to keep track of the manic activity. And as trading grew more frenetic and managed by mindless robots, a new risk had emerged. Insiders were slowly realizing that the push-button turbo-trading market in which algos battled algos inside massive data centers and dark pools at speeds measured in billionths of a second had a fatal flaw. The hunter-seeker Bots that controlled trading came equipped with sensors designed to detect rapid, volatile swings in prices. When the swings passed a certain threshold—say, a downturn of 5 percent in five minutes—the algorithms would instantly sell, shut down, and wait for the market to stabilize. The trouble was that when a large number of algorithms sold and shut down, the market became more volatile, triggering more selling. In other words, a vicious self-reinforcing feedback loop. The Flash Crash had proven this wasn’t merely a fanciful nightmare scenario bandied about by apocalyptic market Luddites. The question tormenting experts was how far the loop would go next time. Progress Software, a firm that tracks algorithmic trading, predicted that a financial institution would lose one billion dollars or more in 2012 when a rogue algorithm went “into an infinite loop … which cannot be shut down.” And since the computer programs were now linked across markets—stock trades were synced to currencies and commodities and futures and bonds—and since many of the programs were very similar and were massively leveraged, the fear haunting the minds of the Plumbers was that the entire system could snap like a brittle twig in a matter of minutes. A chaotic butterfly effect could erase everyone’s hard-earned savings in an eyeblink and, for kicks, throw the global econ...
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  • Fall '16
  • Finance, Wall Street Crash of 1929, algorithmic trading, Trading Machines, Haim Bodek, TRADING MACHINES

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