They didn’t all behave this way: A couple of the big banks followed up their 100-share orders by forking over the meat of the buy order, and executed the trade their customer had asked them to execute. (The Royal Bank of Canada was by far the best behaved.) But, in general, the big Wall Street banks who had connected to IEX—a group that in the first week of trading excluded Bank of America and Goldman Sachs—connected disingenuously. It was as if they wished to appear to be interacting with the entire stock market, while actually they were trying to prevent any trades from happening outside their own dark pools.
Brad now explained to the investors, who were of course paying the price for this behavior, the reasons that the banks behaved as they did. The most obvious was to maximize the chance of executing the stock market orders given to them by investors in their own dark pools. The less honestly a bank looked for P&G stock outside of its own dark pool, the less likely it was to find it. This evasiveness explained the banks’ incredible ability to find, eventually, the other side of any trade inside their own dark pools. A bank that controlled less than 10 percent of all U.S. stock market orders was somehow able to satisfy more than half of its customers’ orders without ever leaving its own dark pool. Collectively, the banks had managed to move 38 percent of the entire U.S. stock market now traded inside their dark pools—and this is how they had done it. “It’s a façade that the market is interconnected,” said Brad.
The big Wall Street banks wanted to trade in their own dark pools not only because they made more money—on top of their commissions—by selling the right to HFT to exploit orders inside their dark pools. They wanted to trade their orders inside their dark pools to boost the volumes in those pools, for appearances’ sake. The statistics used to measure the performance of the dark pools, as well as the performance of the public stock exchanges, were more than a little screwy. A stock market was judged by the volume of trading that occurred on it, and the nature of that volume. It was widely believed, for example, that the bigger the average trade size on an exchange, the better the market was for an investor. (By requiring fewer trades to complete his purchase or sale, the exchange reduced the likelihood of revealing an investor’s intentions to high-frequency traders.) Every dark pool and every stock exchange found ways to cook its own flattering statistics; the art of torturing data may never have been so finely practiced. For example, to show that they were capable of hosting big trades, the exchanges published the number of “block” trades of more than 10,000 shares they facilitated. The New York Stock Exchange sent IEX a record of 26 small trades it had made after IEX had routed an order to it—and then published the result on the ticker tape as a single 15,000-share block. The dark pools were even worse, as no one but the banks that ran them had a clear view of what happened inside them. The banks all published their own self-generated stats on their own dark pools: Every bank ranked itself #1. “It’s an entire industry that overglorifies data, because data is so easy to game, and the true data is so hard to obtain,” said Brad.
The banks did not merely manipulate the relevant statistics in their own dark pools; they often sought to undermine the stats of their competitors. That was another reason the banks were sending IEX orders in tiny 100-share lots: to lower the average trade size in a market that competed with the banks’ dark pools. A lower average trade size made IEX’s stats look bad—as if IEX were heavily populated by high-frequency traders. “When the customer goes to his broker and says, ‘What the hell happened? Why am I getting all these hundred-share fills?,’ his broker could easily say, ‘Well, I put the order on IEX,’ ” said Brad. The strategy cost their customers money, and the opportunity to buy and sell shares, but the customers wouldn’t know about it: All they would see was IEX’s average trade size falling.
Soon after it opened for trading, IEX published its own statistics—to describe, in a general way, what was happening in its market. “Since everyone is behaving in a particular way, you can’t see if anyone is behaving particularly badly,” said Brad. Now you could see. Despite the best efforts of Wall Street banks, the average size of IEX’s trades was by far the biggest of any stock exchange, public or private. More importantly, the trading that occurred was more random, unlinked to activity elsewhere in the stock market: For instance, the percentage of trades on IEX that followed the change in the price of some stock was half that of the other exchanges. (Investors were being picked off—as West Chester, Pennsylvania, money manager Rich Gates had been picked off—on exchanges that failed to move their standing orders quickly enough to keep up when stock prices changed.) Trades on IEX were also four times more likely than those elsewhere to trade at the midpoint between the current market bid and offer—which is to say, the price that most would agree was fair. Despite the reluctance of the big Wall Street banks to send them orders, the new exchange was already making the dark pools and public exchanges look bad, even by their own screwed-up standards.‡‡
Brad’s biggest weakness, as a strategist, was his inability to imagine just how badly others might behave. He had expected that the big banks would resist sending orders to IEX. He hadn’t imagined they would use their customers’ stock market orders to actively try at their customers’ expense to sabotage an exchange created to help their customers. “You want to create a system where behaving correctly would be rewarded,” he concluded. “And the system has been doing the opposite. It’s rational for a broker to behave badly.”
The bad behavior played right into the hands of high-frequency traders in the most extraordinary ways. One day while watching the pictures Josh Blackburn had created for him, Brad saw a bank machine-gun IEX with 100-share lots and drive up a stock price 5 cents inside of 232 milliseconds. IEX’s delay—one-third of a millisecond—was of little use in disguising an investor’s stock market order if a broker insisted on broadcasting a big order he controlled over a far longer period: HFT picked up the signal and was getting out in front of it. Wondering if the broker was spreading news of his buy order elsewhere, Brad turned his attention to the consolidated tape of all the trades that occurred in the U.S. stock market. “I just wondered: Is this broker peppering the whole Street, or is it just us?” he told the room full of investors. “What we found blew our minds.”
For each trade on IEX, he’d spotted a nearly identical trade that had occurred at nearly the same time in some other market. “I noticed the odd trade sizes,” he said. He’d see a trade on IEX for 131 shares of, say, Procter & Gamble, and then he’d see, in some other market, exactly the same trade—131 shares of Procter & Gamble—within a few milliseconds, but at a slightly different price. It happened over and over again. He also noticed that, in each case, on one side of the trade was a broker who had rented out his pipes to a high-frequency trader.
Up till that point, most of the predation they had uncovered occurred when stock prices moved. A stock went up or down; the high-frequency guys found out before everyone else and took advantage of them. Roughly two-thirds of all stock market trades took place without moving the price of the stock—the trade happened at the seller’s offering price, or the buyer’s bidding price, or in between; afterwards, the bid and offering price remained the same as they had been before. What Brad now saw was how HFT, with the help of the banks, might exploit investors even when the stock price was stable. Say the market for Procter & Gamble’s shares was 80.50–80.52, and the quote was stable—the price wasn’t about to change. The National Best Bid was $80.50, and the National Best Offer was $80.52, and the stock was just sitting there. A seller of 10,000 Procter & Gamble shares appeared on IEX. IEX tried to price the orders that rested on it at the midpoint (the fair price), and so the 10,000 shares were being offered at $80.51. Some high-frequency trader would come into IEX—it was always a high-frequency trader—and chip away at the order: 131 shares here, 189 shares there. But elsewhere in the market, the same HFT was selling the shares—131 shares here, 189 shares there—at $80.52. On the surface, HFT was performing a useful function, building
a bridge between buyer and seller. But the bridge was itself absurd. Why didn’t the broker who controlled the buy order simply come to IEX on behalf of his customer and buy, more cheaply, the shares offered?
Back when Rich Gates conducted his experiments, he had managed to get himself robbed inside Wall Street’s dark pools, but only after he had changed the price of the stock (because the dark pools were so slow to move the price of his order resting inside of them). These trades that Brad was now noticing had happened without the market moving at all. He knew exactly why they were happening: The Wall Street banks were failing to send their customers’ orders to the rest of the marketplace. An investor had given a Wall Street bank an order, say, to buy 10,000 shares of P&G. The bank had sent it to its dark pool with instructions for the order to stay there, aggressively priced, at $80.52. The bank was boosting its dark pool stats—and also charging some HFT a fee rather than paying a fee to another exchange—but it was also ignoring whatever else was happening in the market. In a functional market, the investors would simply have met in the middle and traded with each other at a price of $80.51. The price of the stock needn’t have moved a penny. The unnecessary price movement—caused by the screwed-up stock market—also played into HFT’s hands. Because high-frequency traders were always the first to detect any stock price movements, they were able to exploit, with other strategies, ordinary investors’ ignorance of the fact that the market price had changed. The original false note struck by the big Wall Street bank—the act of avoiding making trades outside of its own dark pool—became the prelude to a symphony of scalping.§§ “We’re calling this ‘dark pool arbitrage,’ ” said Brad.
IEX had built an exchange to eliminate the possibility of predatory trading—to prevent investors from being treated as prey. In the first two months of its existence, IEX had seen no activity from high-frequency traders except this. It was astonishing, when you stopped to think about it, how aggressively capitalism protected its financial middleman, even when he was totally unnecessary. Almost magically, the banks had generated the need for financial intermediation—to compensate for their own unwillingness to do the job honestly.
Brad opened the floor for questions. For the first few minutes, the investors vied with each other to see who could best control his anger and exhibit the sort of measured behavior investors are famous for.
“Do you think of HFT differently than you did before you opened?” asked one.
That question might have been better answered by Ronan, who had just returned from a tour of the big HFT firms, and now leaned against a wall on the side of the room. Brad had asked Ronan to explain to the investors the technical end of things—how IEX had created its 350-microsecond delay, the magic shoebox, and so on—and to relate the details of his tour. He’d done it. But on the subject of HFT he held himself back. To speak his mind, Ronan needed to feel like himself, which, imprisoned in a gray suit and addressing a semiformal audience, he clearly did not. Put another way: It was just extremely difficult for Ronan to say what he felt without using the word “fuck.” Watching him string together sentences without profanity was like watching someone try to swim across a river without using his arms or his legs. Curiously, he later admitted, he wasn’t worried that the audience would be offended by bad language. “It was because some of them want to be the alpha male cursing in the room,” he said. “When I say ‘fuck,’ they think I’m stealing the show—so when I’m in front of a group I go as straight as I can.”
“I hate them a lot less than before we started,” said Brad. “This is not their fault. I think most of them have just rationalized that the market is creating the inefficiencies and they are just capitalizing on them. Really, it’s brilliant what they have done within the bounds of the regulation. They are much less of a villain than I thought. The system has let down the investor.”
A forgiving sentiment. But at that moment the investors in the conference room did not seem in a forgiving mood. “It’s still shocking to me to see how the banks are colluding against us,” one of the investors later said. “It shows everyone is a bad actor. And then when you add in that you ask them to route to IEX and they refuse, it’s even worse. Even though I had heard some of it before, I was still incensed. If that was the first time I was hearing it, I think I’d have gone bonkers.”
An investor raised his hand and motioned to some numbers Brad had scribbled on a whiteboard to illustrate how a particular bank had enabled dark pool arbitrage.
“Who is that?” he asked, and not calmly.
An uneasy look crossed Brad’s face. He was now hearing that question more and more. Just that morning, an outraged investor listening to a dry run of his presentation had stopped him to ask: “Which bank is the worst?” “I can’t tell you,” he said, and explained that the agreements the big Wall Street banks signed with IEX forbade IEX from speaking about any bank without its permission.
“Do you know how frustrating it is to sit here and hear this and not know who that broker is?” said another investor.
It wasn’t easy being Brad Katsuyama—to try to effect some practical change without a great deal of fuss, when the change in question was, when you got right down to it, a radical overhaul of a social order. Brad was not by nature a radical. He was simply in possession of radical truths.
“What we want to do is highlight the good brokers,” said Brad. “We need the brokers who are doing the right thing to get rewarded.” That was the only way around the problem. Brad had asked for the banks’ permission to highlight the virtue of the ones that behaved relatively well, and they had granted it. “Speaking about someone in a positive light does not violate the terms of not speaking about someone in a negative light,” he said.
The audience considered this.
“How many good brokers are there?” asked an investor at length.
“Ten,” said Brad. (IEX had dealings with ninety-four.) The ten included the Royal Bank of Canada, Sanford Bernstein, and a bunch of even smaller outfits. “Three are meaningful,” he added. Morgan Stanley, J.P. Morgan, and Goldman Sachs.
“Why would any broker behave well?”
“The long-term benefit is that when the shit hits the fan, it will quickly become clear who made good decisions and who made bad decisions,” said Brad.
He wondered, often, what it would look like if and when the shit in question hit the fan: The stock market at bottom was rigged. The icon of global capitalism was a fraud. How would enterprising politicians and plaintiffs’ lawyers and state attorneys general respond to that news? The thought of it actually didn’t give him all that much pleasure. Really, he just wanted to fix the problem. At some level, he still didn’t understand why Wall Street banks needed to make his task so difficult.
“Is there a concern from you that the publicity will create even more hostility?” asked another. He wanted to know if telling the world who the good brokers were would make the bad ones worse.
“The bad brokers can’t try harder at being bad,” said Brad. “Some of these brokers are doing everything they can not to do what the client wants them to do.”
An investor wanted to return to the scribbled numbers that illustrated how one particular bank had enabled dark pool arbitrage. “So what do these guys say when you show them that?
“Some of them say, ‘You’re one hundred percent right,’ ” said Brad. “ ‘This shit happens.’ One even said, ‘We used to sit around all the time talking about how to fuck up other people’s dark pools.’ Some of them say, ‘I have no idea what you’re talking about. We have heuristic data bullshit and other mumbo jumbo to determine our routing.’ ”
“That’s a technical term—‘heuristic data bullshit and other mumbo jumbo’?” an investor asked. A few guys laughed.
Technology had collided with Wall Street in a peculiar way. It had been used, as it should have been used, to increase efficiency. But it had also been used to introduce a peculiar sort of market inefficiency. This new inefficiency was not like the
inefficiencies that financial markets can easily correct. After a big buyer enters the market and drives up the price of Brent crude oil, for example, it’s healthy and good when speculators jump in and drive up the price of North Texas crude, too. It’s healthy and good when traders see the relationship between the price of crude oil and the price of oil company stocks, and drive these stocks higher. It’s even healthy and good when some clever high-frequency trader divines a necessary statistical relationship between the share prices of Chevron and Exxon, and responds when it gets out of whack. It was neither healthy nor good when public stock exchanges introduced order types and speed advantages that high-frequency traders could use to exploit everyone else. This sort of inefficiency didn’t vanish the moment it was spotted and acted upon. It was like a broken slot machine in the casino that pays off every time. It would keep paying off until someone said something about it; but no one who played the slot machine had any interest in pointing out that it was broken.
Some large amount of what Wall Street had done with technology had been done simply so that someone inside the financial markets would know something that the outside world did not. The same system that once gave us subprime mortgage collateralized debt obligations no investor could possibly truly understand now gave us stock market trades that occurred at fractions of a penny at unsafe speeds using order types that no investor could possibly truly understand. That is why Brad Katsuyama’s most distinctive trait—his desire to explain things not so he would be understood but so that others would understand—was so seditious. He attacked the newly automated financial system at its core: the money it made from its incomprehensibility.
Flash Boys: A Wall Street Revolt Page 22
