Courtesy of the author, we present to our readers the following excerpt from Dark Pools: High-Speed Traders, AI Bandits, and the Threat to the Global Financial System, by Scott Patterson, author of The Quants.

In early December 2009, Haim Bodek finally solved the riddle of the stock-trading problem that was killing Trading Machines, the high-frequency firm he’d help launch in 2007. The former Goldman Sachs and UBS trader was attending a party in New York City sponsored by a computer-driven trading venue. He’d been complaining for months to the venue about all the bad trades—the runaway prices, the fees—that were bleeding his firm dry. But he’d gotten little help.

At the bar, he cornered a representative of the firm and pushed for answers. The rep asked Bodek what order types he’d been using to buy and sell stocks. Bodek told him Trading Machines used limit orders.

The rep smirked and took a sip of his drink. “You can’t use those,” he told Bodek.

“Why not?”

“You have to use other orders. Those limit orders are going to get run over.”

“But that’s what everyone uses,” Bodek said, incredulous. “That’s what Schwab uses.”

“I know. You shouldn’t.”

As the rep started to explain undocumented features about how limit orders were treated inside the venue’s matching engine, Bodek started to scribble an order on a napkin, detailing how it worked. “You’re fucked in that case?” he said, shoving the napkin at the guy.

“Yeah.”

He scribbled another. “You’re fucked in that case?” “Yeah.”

“Are you telling me you’re fucked in every case?” “Yeah.”

“Why are you telling me this?”

“We want you to turn us back on again,” the rep replied. “You see, you don’t have a bug.”

Bodek’s jaw dropped. He’d suspected something was going on in- side the market that was killing his trades, that it wasn’t a bug, but it had been only a vague suspicion with little proof.

“I’ll show you how it works.”

The rep told Bodek about the kind of orders he should use— orders that wouldn’t get abused like the plain vanilla limit orders; orders that seemed to Bodek specifically designed to abuse the limit orders by exploiting complex loopholes in the market’s plumbing. The orders Bodek had been using were child’s play, simple declarative sentences sent to exchanges such as “Buy up to $20.” These new order types were compound sentences, with multiple clauses, virtually Faulknerian in their rambling complexity.

The end result, however, was simple: Everyday investors and even sophisticated firms like Trading Machines were buying stocks for a slightly higher price than they should, and selling for a slightly lower price and paying billions in “take” fees along the way.

The special order types that gave Bodek the most trouble—the kind the trading-venue rep told him about—allowed high-frequency traders to post orders that remained hidden at a specific price point at the front of the trading queue when the market was moving, while at the same time pushing other traders back. Even as the market ticked up and down, the order wouldn’t move. It was locked and hidden. It was dark. This got around the problem of reshuffling and rerouting. The sitting-duck limit orders, meanwhile, lost their priority in the queue when the market shifted, even as the special orders maintained their priority.

Why would the high-speed firms wish to do this? Maker-taker fees that generate billions in revenue for the speed Bots every year. By staying at the front of the queue and hidden as the market shifted, the firm could place orders that, time and again, were paid the fee. Other traders had no way of knowing that the orders were there. Over and over again, their orders stepped on the hidden trades, which acted effectively as an invisible trap that made other firms pay the “take” fee.

It was fiendishly complex. The order types were pinned to a specific price, such as $20.05, and were hidden from the rest of the market until the stock hit that price. As the orders shifted around in the queue, the trap was set and the orders pounced. In ways, the venue had created a dark pool inside the lit pool.

“You’re totally screwed unless you do that,” the rep at the bar said. Bodek was astonished—and outraged. He’d been complaining for months about the bad executions he’d been getting, and had been told nothing about the hidden properties of the order types until he’d punished the it by reducing the flow he send to it. He was certain they’d known the answer all along. But they couldn’t tell everyone—because if everyone started using the abusive order types, no one would use limit orders, the food the new order types fed on.

Bodek felt sick to his stomach. “How can you do that?” he said.

The rep laughed. “If we changed things, the high-frequency traders wouldn’t send us their orders,” he said.

Courtesy of the author, we present to our readers the following excerpt from Dark Pools: High-Speed Traders, AI Bandits, and the Threat to the Global Financial System, by Scott Patterson, author of The Quants. Part 1 can be found here.

Haim Bodek thought practically nonstop for days about what the trade-venue representative had told him that night at the New York party.
The way that the abusive order types worked made him think back to a document he’d been given by a colleague that summer as he researched what was going wrong at Trading Machines. The document was a detailed blueprint of a high-frequency method that was said to be popular in Chicago’s trading circles.

It was called the “0+ Scalping Strategy.”

Bodek suspected that there might be a link between the order types and the strategy.

Riffling through his files, he quickly found it. While the document didn’t say which firm used the strategy, he’d been told by the colleague who’d given it to him that one of the most successful high-speed firms employed it, or something closely akin to it. Due to the sophistication of the strategy, he’d guessed from the start that it was probably written by a Plumber.

There was another giveaway that it had originated in Chicago, where Bodek had worked for several years at Hull Trading: “scalping.” To a trader, scalping didn’t mean the same thing it meant to most people—a suspicious-looking guy peddling tickets for a sporting event or rock concert outside a stadium. In trading, scalping was an age-old strategy of buying low and selling high—very quickly. It was a common practice on the floors of futures exchanges that populated the Midwest—the Kansas City Board of Trade or the Chicago Mercantile Exchange. The 0+ Scalping Strategy was apparently a futures-trading technique that had been transformed into a computer program.

Bodek started reading. Page two of the document laid out the purpose of the 0+ strategy. “Simple Goal: use market depth and our order’s priority in the Q to create scalping opportunities where the loss on any one trade is limited to ‘0’ (exclusive of commissions).”

He paused at that. Essentially, the author of the strategy was saying that its primary goal was to never lose money—the loss on any trade was “0.” In theory, this could be done through a scalping strategy. By being first in the “Q”—shorthand for the queue in which orders are stacked up, like theatergoers waiting in line for their tickets—the firm could always get the best trade at the best time.

But what happened when the firm didn’t want to buy or sell? Bodek kept reading.

“GOAL RESTATEMENT: use the market depth and our order’s priority in the Q to create scalping opportunities where the probability of a +1 tic gain on any given trade is substantially greater than the probability of a –1 tic loss on any given trade.”

Aha, Bodek thought, market depth. That was a reference to the orders behind this firm’s orders, the other theatergoers waiting in line. The 0+ trader is assuming that his firm is so fast and so skilled that it can almost always get priority in the trading queue—be the first to buy and the first to sell. The depth behind it, the other orders, is the rest of the market.

The author is saying I always want to win (or rather, I never want to lose). His probability of winning—a +1 tick—is “substantially greater” than a –1 tick loss.

But how?

The rest of the market—suckers like Trading Machines or every- day mutual funds—was insurance. Under the next heading, called SIMPLE PREMISES, the exact meaning of what insurance meant was spelled out.

“If we have sufficient depth behind our order at a given price level, then we are effectively self-insured against losing money. Why? If we get elected on our order, we could immediately exit our risk for a scratch by trading against one of the orders behind us.”

In other words, if the 0+ trader buys a stock (gets “elected”), and his algos suddenly detect that the price is likely to fall—they can see a large number of sell orders stacking up in the trading queue—he can flip and sell to the sucker standing behind him, resulting in a “scratch” (no gain and no loss). He can do this because his computer systems can “react fast enough to changing market conditions . . . to ‘always’ achieve, in the worst-case, a scratch or a cancel of our orders.”

It was the Holy Grail of trading. The 0+ trader was describing a strategy that effectively never lost. The rest of the market protected it whenever the firm’s algorithms detected the slightest chance that the market was moving against it.

It’s brilliant—and diabolical. A firm that has found a strategy that is virtually guaranteed to win on every trade has discovered a hole in the market. Trading is all about taking risk, but this author was describing a virtually riskless trade.

The situation confronting Bodek and other investors not using the 0+ strategy was challenging, to say the least. It was like driving a car down the freeway, and every time you tried to speed up, another, faster car was in front of you. No matter how many tricks you pulled, this car (a 0+ symbol stamped on its hood, of course) was always leading the pack. The only time you could get around it—when it would suddenly hit the brakes and vanish in the crowd behind you—was when a Mack truck was speeding right at you. Worse, the 0+ trader was the Mack truck!
The upshot: Regular investors, the suckers using those stupid limit orders, buy high and sell low—all the time.

The game had changed. Bodek became increasingly convinced that the stock market—the United States stock market—was rigged. Exchanges appeared to be providing mechanisms to favored clients that allowed them to circumvent Reg NMS rules in ways that abused regular investors. It was complicated, a fact that helped hide the abuses, just as giant banks used complex mortgage trades to bilk clients out of billions, in the process triggering a global financial panic in 2008. Bodek wasn’t sure if it was an outright conspiracy or simply an ecosystem that had evolved to protect a single type of organism that had become critical to the survival of the pools themselves.

Whatever it was, he thought, it was wrong.

Dark Pools: Good Book, Bad Title
Scott Patterson's new book Dark Pools: High-Speed Traders, A.I. Bandits, and the Threat to the Global Financial System suggests a Rolling Stone type expose of vampire squids sucking the vital fluids out of widows and orphans. In contrast, most of the book was about the development of electronic exchanges from 1990 through 2007, especially focused on the firms Archapelego and Island. It reminds me of Justin Fox's Myth of the Rational Market which suggested a rather slanted and damning hatchet job but then did nothing of the sort. I suppose the marginal business book buyer is on the way to an Occupy rally.

I work on tactics related to these tactics and technologies, so found it very enjoyable. The real hero of this book, rightly, is Joshua Levine, who started Island. He pioneered paying for flow, where one pays those making markets, and charges those crossing the spread. He was on the bleeding edge in cloud computing, creating more robust infrastructure with a fraction of the budget than his big-time competitors. I know people who dealt with him, and they highlight how thoughtful he was about sharing information back in the day on order strategies, technical stuff that others might guard in a paranoid fashion. Levine thought if his customers could make more money, they would trade more, and this would breed even more liquidity. In other words, a classic business mensch.

There are lots of numbers thrown around, but it's good to remember that electrons move about 1 foot per nanosecond, so there's a basic limit to how fast these things can get. It is true that humans generally take a couple hundred milliseconds to process information and push a button, so clearly computers that can turn around info in a couple milliseconds beat humans in any whack-a-mole game. But all that pico-stuff is pretty silly. Consider the S&P minis futures contracts trades 400k times a day, so every 60 milliseconds (thousandth of a second) represents the highest frequency relevant for any contract. Stocks like IBM trade about once a second. Thus, all that super speed below a millisecond is not for trading so much as 'lining the book', market makers playing games in the queue to provide liquidity. Your average trader should think about this as much as they think about what's going on underground at Disney World.

There's a theme that originally the innovators wanted to cut out the middlemen, but then discovered there were new middlemen. Meet the new boss, as The Who would say. The bottom line is that spreads on big stocks like MSFT and ORCL used to be ¼ in the good old days before ECNs, which allowed lots of traders to make a fortune via their monopoly access to customer flow and the various barriers to competitors. That these specialists are now unemployed should be considered classic creative destruction. I knew several of them; they were lucky while it lasted, and it lasted too long.

The book is a bit light on actual tactics, making some strategies sound a lot more effective than they are. For example, Patterson describes a strategy he calls "0+", that supposedly makes money with zero risk. In fact, this strategy does have risk, because it presumes that you can always exit your position before the queue behind disappears. Often a level gets 'taken out' by an order and so the queue behind you is gone within any possible time to place new order and get out at scratch (pre-fees, I should add). Indeed, the trader plying this strategy is presented later pathetically fishing for 10 minute stock predictors like thousands of other punters, highlighting this was no money pump.

A lot of the conspiracy talk around algorithms presumes a market price reflects 'true value', like the mass of something, and that algorithms are keeping others from it. Market prices approximate value, but a price is really an aggregate compromise, one that almost everyone disagrees with. If you want to buy more, now, you will pay a higher price because you need to convince more people to take the other side. Jehova shouldn't care because 'true value' is unaffected by such concerns, but the market does, and so comparing prices to some assumed point estimate of 'true value' just leads to meaningless disquisitions. If you want to think about such issues just remember all those theologians who wrote about the 'just price' for about one thousand years and whose work is now totally ignored for good reason, to give you a sense of your futility.

The bottom line is that those buyers and sellers with big orders have always moved markets from their 'last price', and in the old days this was all done via a coalition of partners over a phone, but now algorithms sniff out these orders by noting a higher-than-usual buy crossing rate, or sense a really big iceberg limit order, and so basically have expropriated the front-running revenue from the traditional recipient of this value. A large order will move prices so it's going to be exploited, and this is better done competitively via electronic markets than by a specialist with monopoly access to the flow.

There's some funny other stuff in there, like how regulator are pretty irrelevant to all the innovations. Indeed, the regulators appear more interested in protecting the status quo, as George Stigler noted 50 years prior in his work on the industry capture of regulators. Mary Schapiro gets her standard uncritical mention, as she is always presented as the righteous regulator who would have prevented the 2008 crisis if it weren't for Lawrence Summers and his cabal. Her big idea after the flash crash was 'circuit breakers', aka limit price moves. This doesn't help much, as decades of experience with these in futures has shown, though it does 'work' if you merely want to prevent prices from moving more than 5% a day (why not solve the Greek budget deficit by not reporting it?).

The Flash Crash of May 6 2010 included an order to buy 75000 contracts when your average price level had only 5000 contracts there, so it pushed the 'market price' into uncharted territory. Its understandable these things happen, it's a new technology, lots of users, and lots of new emergent properties, most coming down to problems related to idiots placing large 'market orders' that wipe out several 'levels' of prices. I bet the exchanges will figure out a governor in spite of what the SEC does, but such issues are really irrelevant to what caused the crisis of 2008 or the 'Global Financial System.'

Part of a popular work on technical issues seems to involve building up the major players as geniuses, going over their rocket science background. In this case it's like pointing out how every professional football player was an outstanding high school athlete--financial innovators tend to have done well in math and science, so that whole physicist turned financier story isn't rare or intellectually sexy. I suppose that's how to get your hooks into the masses, because people like to read about geniuses.

In spite of the scary title, it's simply a good story of how innovators destroy the old guard. If you are worried about high frequency traders you almost surely trade too much, and would be better focused on asset markets built on things that are truly unsustainable. High frequency traders are very sensitive to cash flow (note Trading Machines shut down pretty quickly after not finding a niche), so they aren't building palaces based on unrealistic expectations like, say, California or or NYU journalism majors.