Brad suspected that the culprit was the technology from Carlin that RBC had more or less bolted onto the side of his trading machines. “As the market problem got worse,” he said, “I started to just assume my real problem was with how bad their technology was.” A pattern was established: The moment he attempted to react to the market on his screens, the market moved. And it wasn’t just him: The exact same thing was happening to all of the RBC stock market traders who worked for him. In addition, for reasons he couldn’t fathom, the fees that RBC was paying to stock exchanges were suddenly skyrocketing. At the end of 2007 Brad conducted a study to compare what had happened on his trading books to what should have happened, or what used to happen, when the stock market as stated on his trading screens was the market he experienced. “The difference to us was tens of millions of dollars” in losses plus fees, he said. “We were hemorrhaging money.” His bosses in Toronto called him in and told him to figure out how to reduce his rising trading costs.
Up till then, Brad had taken the stock exchanges for granted. When he’d arrived in New York, in 2002, 85 percent of all stock market trading happened on the New York Stock Exchange, and some human being processed every order. The stocks that didn’t trade on the New York Stock Exchange traded on Nasdaq. No stocks traded on both exchanges. At the behest of the SEC, in turn responding to public protests about cronyism, the exchanges themselves, in 2005, went from being utilities owned by their members to public corporations run for profit. Once competition was introduced, the exchanges multiplied. By early 2008 there were thirteen different public exchanges, most of them in northern New Jersey. Virtually every stock now traded on all of these exchanges: You could still buy and sell Intel on the New York Stock Exchange, but you could also buy and sell it on BATS, Direct Edge, Nasdaq, Nasdaq BX, and so on. The idea that a human being needed to stand between investors and the market was dead. The “exchange” at Nasdaq or at the New York Stock Exchange, or at their new competitors, such as BATS and Direct Edge, was a stack of computer servers that contained the program called the “matching engine.” There was no one inside the exchange to talk to. You submitted an order to the exchange by typing it into a computer and sending it into the exchange’s matching engine. At the big Wall Street banks, the guys who once peddled stocks to big investors had been reprogrammed. They now sold algorithms, or encoded trading rules designed by the banks, that investors used to submit their stock market orders. The departments that created these trading algorithms were dubbed “electronic trading.”
That was why the Royal Bank of Canada had panicked and bought Carlin. There was still a role for Brad and traders like Brad—to sit between buyers and sellers of giant blocks of stock and the market. But the space was shrinking.
At the same time, the exchanges were changing the way they made money. In 2002 they charged every Wall Street broker who submitted a stock market order the same simple fixed commission per share traded. Replacing people with machines enabled the markets to become not just faster but more complicated. The exchanges rolled out an incredibly complicated system of fees and kickbacks. The system was called the “maker-taker model” and, like a lot of Wall Street creations, was understood by almost no one. Even professional investors’ eyes glazed over when Brad tried to explain it to them. “It was the one thing I’d skip, because a lot of people just didn’t get it,” he said. Say you wanted to buy shares in Apple, and the market in Apple was 400–400.05. If you simply went in and bought the shares at $400.05, you were said to be “crossing the spread.” The trader who crossed the spread was classified as the “taker.” If you instead rested your order to buy Apple at $400, and someone came along and sold the shares to you at $400, you were designated a “maker.” In general, the exchanges charged takers a few pennies a share, paid makers somewhat less, and pocketed the difference—on the dubious theory that whoever resisted the urge to cross the spread was performing some kind of service. But there were exceptions. For instance, the BATS exchange, in Weehawken, New Jersey, perversely paid takers and charged makers.
In early 2008 all of this came as news to Brad Katsuyama. “I thought all the exchanges just charged us a flat fee,” he said. “I’m like, ‘Holy shit, you mean someone will pay us to trade?’ ” Thinking he was being clever, he had all of RBC’s trading algorithms direct the bank’s stock market orders to whatever exchange would pay them the most for what they wanted to do—which, at that moment, happened to be the BATS exchange. “It was a total disaster,” said Brad. When he tried to buy or sell stock and seize the payment from the BATS exchange, the market for that stock simply vanished, and the price of the stock moved away from him. Instead of being paid, he wound up hemorrhaging even more money.
It was not obvious to Brad why some exchanges paid you to be a taker and charged you to be a maker, while others charged you to be a taker and paid you to be a maker. No one he asked could explain it, either. “It wasn’t like there was anyone saying, ‘Hey, you should really be paying attention to this.’ Because no one was paying attention to this.” To further bewilder the Wall Street brokers who sent stock market orders to the exchanges, the amounts that were charged varied from exchange to exchange, and the exchanges often changed their pricing. To Brad this all just seemed bizarre and unnecessarily complicated—and it raised all sorts of questions. “Why would you pay anyone to be a taker? I mean, who is willing to pay to make a market? Why would anyone do that?”
He took to asking people around the bank who might know more than he did. He tried Googling, but there wasn’t really anything to Google. One day he was talking to a guy who worked on the retail end in Toronto selling stocks to individual Canadians. “I said, ‘I’m getting screwed, but I can’t figure out who is screwing me.’ And he says, ‘You know, there are more players out there in the market now.’ And I say, ‘What do you mean more players?’ He says, ‘You know, there’s this new firm that’s now ten percent of the U.S. market.’ ” The guy mentioned the firm’s name, but Brad didn’t fully catch it. It sounded like Gekko. (The name was Getco.) “I’d never even heard of Getco. I didn’t even know the name. I’m like, ‘WHAT??’ They were ten percent of the market. How can that be true? It’s insane that someone could be ten percent of the U.S. stock market and I’m running a Wall Street trading desk and I’ve never heard of the place.” And why, he wondered, would a guy from retail in Canada know about them first?
He was now running a stock market trading department unable to trade properly in the U.S. stock market. He was forced to watch people he cared for harassed and upset by a bunch of 1980s Wall Street throwbacks. And then, in the fall of 2008, as he sat and wondered what else might go wrong, the entire U.S. financial system went into a freefall. The way Americans handled their money had led to market chaos, and the market chaos created life chaos: The jobs and careers of everyone around him were suddenly on the line. “Every day I’d walk home and feel as if I had just got hit by a car.”
He wasn’t naïve. He knew that there were good guys and bad guys, and that sometimes the bad guys win; but he also believed that usually they did not. That view was now challenged. When he began to grasp, along with the rest of the world, what big American firms had done—rigged credit ratings to make bad loans seem like good loans, created subprime bonds designed to fail, sold them to their customers and then bet against them, and so on—his mind hit some kind of wall. For the first time in his career, he felt that he could only win if someone else lost, or, more likely, that someone else could only win if he lost. He was not by nature a zero-sum person, but he had somehow wound up in the middle of a zero-sum business.
His body had always tended to register stress before his mind. It was as if his mind refused to accept the possibility of conflict even as his body was engaged in that conflict. Now he bounced from one illness to another. His sinuses became infected and required surgery. His blood pressure, chronically high, skyrocketed. His doctors had him seeing a kidney specialist.
By early 2009 he’d decided t
o quit Wall Street. He’d just become engaged. After work every day he’d sit down with his fiancée, Ashley Hooper—a recent Ole Miss graduate who’d grown up in Jacksonville, Florida—to decide where to live. They’d whittled the list down to San Diego, Atlanta, Toronto, Orlando, and San Francisco. He had no idea what he was going to do; he just wanted out. “I thought I could just sell pharmaceuticals or whatever.” He’d never felt a need to be on Wall Street. “It was never a calling,” he said. “I didn’t think about money or the stock market when I was growing up. So the attachment was not strong.” Maybe more oddly, he hadn’t become all that wedded to money, even though RBC was now paying him almost $2 million a year. His heart had been in his job, but mainly because he really liked the people he worked for and the people who worked for him. What he liked about RBC was that it had never pressured him to be anyone but himself. The bank—or the markets, or perhaps both—was now pushing him to be someone else.
Then the bank, on its own, changed its mind. In February 2009 RBC parted ways with Jeremy Frommer and asked Brad to help find someone to replace him. Even as he had one foot out the door, Brad found himself interviewing candidates from all over Wall Street—and he saw that basically none of the people who held themselves out as knowledgeable about electronic trading understood it. “The problem was that the electronic people facing clients were just front men,” he said. “They had no clue how the technology worked.”
He withdrew his foot from the doorway and thought about it. Every day, the markets were driven less directly by human beings and more directly by machines. The machines were overseen by people, of course, but few of them knew how the machines worked. He knew that RBC’s machines—not the computers themselves, but the instructions to run them—were third-rate, but he had assumed it was because the company’s new electronic trading unit was bumbling and inept. As he interviewed people from the major banks on Wall Street, he came to realize that they had more in common with RBC than he had supposed. “I’d always been a trader,” he said. “And as a trader you’re kind of inside a bubble. You’re just watching your screens all day. Now I stepped back and for the first time started to watch other traders.” He had a good friend who traded stocks at a big-time hedge fund in Stamford, Connecticut, called SAC Capital. SAC Capital was famous (and soon to be infamous) for being one step ahead of the U.S. stock market. If anyone was going to know something about the market that Brad didn’t know, he figured, it would be them. One spring morning he took the train up to Stamford and spent the day watching his friend trade. Right away he saw that, even though his friend was using technology given to him by Goldman Sachs and Morgan Stanley and the other big firms, he was experiencing exactly the same problem as RBC: The market on his screens was no longer the market. His friend would hit a button to buy or sell a stock and the market would move away from him. “When I see this guy trading and he was getting screwed—I now see that it isn’t just me. My frustration is the market’s frustration. And I was like, Whoa, this is serious.”
Brad’s problem wasn’t just Brad’s problem. What people saw when they looked at the U.S. stock market—the numbers on the screens of the professional traders, the ticker tape running across the bottom of the CNBC screen—was an illusion. “That’s when I realized the markets are rigged. And I knew it had to do with the technology. That the answer lay beneath the surface of the technology. I had absolutely no idea where. But that’s when the lightbulb went off that the only way I’m going to find out what’s going on is if I go beneath the surface.”
THERE WAS NO way he, Brad Katsuyama, was going to go below the surface of the technology. People always assumed, because he was an Asian male, that he must be a computer wizard. He couldn’t (or wouldn’t) program his own VCR. What he had was an ability to distinguish between computer people who didn’t actually know what they were talking about and those who did. The very best example of the latter, he thought, was Rob Park.
Park, a fellow Canadian, was a legend at RBC. In college in the late 1990s he’d become entranced by what was then a novel idea: to teach a machine to behave like a very smart trader. “The thing that interested me was taking a trader’s thought process and replicating it,” Park said. He and Brad had worked together at RBC only briefly, back in 2004, before he left to start his own business, but they had hit it off. Rob took an interest in the way Brad thought when he traded. Rob then turned those thoughts into code. The result was RBC’s most popular trading algorithm. Here’s how it worked: Say the trader wanted to buy 100,000 shares in General Motors. The algo scanned the market; it saw that there were only 100 shares offered. No smart trader seeking to buy 100,000 shares would tip his desire for a mere 100 shares. The market was too thin. But what was the point at which the trader should buy GM stock? The algorithm Rob built had a trigger point: It only bought stock if the amount on offer was greater than the historical average of the amount offered. That is, if the market was thick. “The decisions he makes make sense,” Brad said of Rob. “He puts an incredible amount of thought into them. And since he puts so much thought into his decisions, he’s capable of explaining those decisions to others.”
After Brad persuaded Rob to return to RBC, he had the perfect person to figure out what had happened to the U.S. stock market. And in Brad, Rob saw the perfect person to grasp and explain to others whatever he discovered. “All Brad needs is a translator from computer language to human language,” said Park. “Once he has a translator, he completely understands it.”
Brad wasn’t exactly shocked when RBC finally gave up looking for someone to run its mess of an electronic trading operation and asked him if he would take it over and fix it. Everyone else was shocked when he agreed to do it, as (a) he had a safe and cushy $2-million-a-year job running the human traders and (b) RBC had nothing to add to electronic trading. The market was cluttered; big investors had only so much space on their desks for trading algorithms sold by brokers; and Goldman Sachs and Morgan Stanley and Credit Suisse had long since overrun that space and colonized it. All that was left of RBC’s purchase of Carlin was the Golden Goose. Thus Brad’s first question to the Golden Goose: How do we plan to make money? They had an answer: They planned to open RBC’s first “dark pool.” That, as it turned out, was what the Golden Goose had been up to all along, writing the software for the dark pool.
Dark pools were another rogue spawn of the new financial marketplace. Private stock exchanges, run by the big brokers, they were not required to reveal to the public what happened inside them. They reported any trade they executed, but they did so with sufficient delay that it was impossible to know exactly what was happening in the broader market at the moment the trade occurred. Their internal rules were a mystery, and only the broker who ran a dark pool knew for sure whose buy and sell orders were allowed inside. The amazing idea the big Wall Street banks had sold to big investors was that transparency was their enemy. If, say, Fidelity wanted to sell a million shares of Microsoft Corp.—so the argument ran—they were better off putting them into a dark pool run by, say, Credit Suisse than going directly to the public exchanges. On the public exchanges, everyone would notice a big seller had entered the market, and the market price of Microsoft would plunge. Inside a dark pool, no one but the broker who ran it had any idea what was happening.
The cost of RBC’s creating and running its own dark pool, Brad now learned, would be nearly $4 million a year. Thus his second question for the Golden Goose: How will we make more than $4 million from our own dark pool? The Golden Goose explained that they’d save all sorts of money in fees they paid to the public exchanges—by putting together buyers and sellers of the same stocks who came to RBC at the same time. If RBC had some investor who wanted to buy a million shares of Microsoft, and another who wanted to sell a million shares of Microsoft, they could simply pair them off in the dark pool rather than pay Nasdaq or the New York Stock Exchange to do it. In theory this made sense; in practice, not so much. “The problem,” said Brad, “was RBC was two percent
of the market. I asked how often we were likely to have buyers and sellers to cross. No one had done the analysis.” The analysis, once finished, showed that RBC, if it opened a dark pool and routed all its clients’ orders into it first, would save about $200,000 a year in exchange fees. “So I said, ‘Okay, how else will we make money?’ ”
The answer that came back explained why no one had bothered to do any analysis on dark pools in the first place. There was a lot of free money to be made, the computer programmers explained, by selling access to the RBC dark pool to outside traders. “They said there were all these people who will pay to be in our dark pool,” recalled Brad. “And I said, ‘Who would pay to be in our dark pool?’ And they said, ‘High-frequency traders.’ ” Brad tried to think of good reasons why traders of any sort would pay RBC for access to RBC’s customers’ stock market orders, but he came up with none. “It just felt weird,” he said. “I had a feeling of why and the feeling didn’t feel good. So I said, ‘Okay, none of this sounds like a good idea. Kill the dark pool.’ ”
That just pissed off a lot of people and fueled suspicions that Brad Katsuyama was engaged in some activity other than the search for corporate profits. Now he was in charge of a business called electronic trading—with nothing to sell. What he had, instead, was a fast-growing pile of unanswered questions. Why, between the dark pools and the public exchanges, were there nearly sixty different places, most of them in New Jersey, where you could buy any listed stock? Why did the public exchanges fiddle with their own pricing so often—and why did you get paid by one exchange to do exactly the same thing for which another exchange might charge you? How did a firm he’d never heard of—Getco—trade 10 percent of the entire volume of the stock market? How had this guy in the middle of nowhere—in retail in Canada—learned of Getco’s existence before him? Why was the market displayed on Wall Street trading screens an illusion?
Flash Boys: A Wall Street Revolt Page 4
