Monday, November 25, 2013

The Wall Street Code?

Jeffrey MacIntosh, Toronto Stock Exchange Professor of Capital Markets, Faculty of Law, University of Toronto, and author of C.D. Howe Institute’s “High Frequency Traders: Angels or Devils?” wrote a special for the National Post, In praise of high frequency traders:
On Thursday, the Investment Industry Regulatory Organization of Canada (IIROC) is scheduled to release its much-awaited study on high frequency traders. The standard image of the high frequency trader (HF trader) is that of a slavering troll working assiduously to destabilize world stock markets and laughing gleefully while prying gold fillings out of retail traders’ mouths. In the minds of many, HF traders caused or greatly contributed to the infamous U.S. “Flash Crash” of May 2010, when the Dow Jones plunged (and then recovered) 1000 points (roughly 9%) in a matter of minutes. HF traders also stand accused of increasing trading costs for both retail and institutional traders.

Academic evidence, however, suggests that HF traders sport toes, not cloven hoofs. Indeed, as noted by the European Commission, “HFT is typically not a strategy in itself but the use of very sophisticated technology to implement traditional trading strategies.” The essence of the “sophisticated technology” is speed. HF traders use highly refined computer algorithms to wade through reams and reams of data, spot profit opportunities, and execute trades to exploit these opportunities. HF traders also use “co-location” to enhance speed. This refers to the now-common practice of paying for the privilege of locating one’s servers in the same building as a trading venue’s computer matching engine (where trades actually get executed). This reduces system “latency” (the time it takes for a message to travel from the HF trader’s computer to the trading venue’s computer, and vice-versa) to a bare minimum.

The HF trader’s speed advantage in general, and co-location in particular, have been much vilified. But superior speed is neither new nor objectionable. Savvy stock traders have long enlisted the latest information technologies to gain an advantage over their rivals. At one time, carrier pigeons and optical semaphore systems were the preferred tools.These gave way, in succession, to the telegraph, the telephone, the Internet, dedicated data lines, and now, co-location. Being the first in line has been a source of profit as long as there have been tradable assets. That goes back not merely decades or centuries, but millennia.

While the clay-footed are never amused to see more fleet-of-foot rivals steal their business, a simple self-help strategy awaits – go out and get your own carrier pigeons. And indeed, more and more traditional players, such as sell-side institutions, are doing just that, putting their own servers in co-location facilities and competing head-to-head with HF traders.

But in any case, the corpus of academic evidence suggests that both retail and institutional traders have benefited from the presence of HF traders. Market making is a case in point. HF traders effectively “make a market” in particular stocks by posting limit orders to buy and sell on the books of various trading venues. However, they are able to quote much narrower bid/ask spreads than traditional market makers.

This is a direct result of their speed. HF traders have no interest in holding stock overnight. As soon as they purchase shares in a given company, they look to sell these shares, and often do so within milliseconds. The extremely short interval between the two legs of any round trip transaction (buy/sell or sell/buy) minimizes the extent to which the HF trader is exposed to what economists call “adverse selection risk,” which is the risk of adverse price movements between the first and the second leg of the round trip. This enables them to effectively quote very tight bid/ask spreads. The academic studies are virtually unanimous in suggesting that when HF traders arrive, bid/ask spreads shrink by a material amount. This benefits all other traders, whether retail or institutional.

HF traders have benefited from the now common practice of “maker/taker” pricing. This involves paying a rebate to the “passive” side of a transaction (the party who enters a limit buy or sell order on the books of a given trading venue) and charging a fee to the “active” side (a later-arriving order that is matched to the passive order, resulting in a completed trade). Speedy HF traders are more likely than others to be on the passive side of a transaction, and thus go home with the lion’s share of the trading rebates.

On the other hand, many non-HF traders (i.e. the ones who now disproportionately end up on the active side of the transaction) have seen their trading costs increase. Nonetheless, it is not clear if this increased trading cost is passed on to the client, as opposed to being partly or wholly absorbed by the market professional (as we would expect in a competitive market). But even if all of the cost is passed on to the trading client, reductions in bid/ask spreads more than compensate.
HF traders are associated with other improvements in market microstructure. For example, studies show that HF traders are more likely to be “informed” traders, and that their presence in a given market improves price discovery (the rapidity with which new information is impounded in the public share price). As against the charge that HF traders make financial markets more volatile, the studies show that when HF traders come calling, intraday price volatility (the degree to which stock prices fluctuate during the course of the day) actually diminishes.

And what of the Flash Crash? The Crash was triggered when a single U.S. mutual fund decided to liquidate $4.1-billion of something called the E-Mini S&P 500 (an equity futures contract based on the value of the S&P 500). Initially, HF traders absorbed some of this volume. However, when it came to executing the second leg of the round trip and selling the E-Mini to someone else, there was trouble. The volume of the mutual fund’s sale order was so large that it exerted a continual downward pressure on the price of the E-Mini. HF traders – just like traditional market makers – found that they could not buy cheap and sell dear. Many withdrew from the market, causing E-Mini liquidity to dry up. Even worse, the liquidity drought was transmitted broadly throughout the market, since the falling value of the E-Mini implied lower values of the stocks underlying the E-Mini contract – namely, the entire S&P 500. These stocks (and others) also went into a death spiral. The imbroglio was ended by a trading halt. Five minutes later, trading was restored, and the market recovered and marched stoically onward.

The Flash Crash is in indictment of HF traders only if we can conclude that they bailed from the market faster than traditional market makers. In fact, the evidence is precisely the opposite; some HF traders hung in until the bitter end. Moreover, numerous studies show that HF traders are slower than traditional players to run for the exits when the going gets rough. A market populated only by traditional market makers would not have avoided the Flash Crash.

Despite all of the favourable academic reviews, many institutional traders swear up and down that HF traders engage in a bevy of manipulative or otherwise unfair trading practices. One Canadian study by Cumming et al., however,finds that HF traders reduce the incidence of end-of-day price manipulation. A U.S. study finds that HF traders do not “front run” institutional orders, as has often been alleged. Nonetheless, the empirical record in this respect is not well developed, and there is certainly anecdotal evidence of dirty tricks being played by HF traders. Academics need to sharpen their pencils in this regard and Canadian regulators need to stay sharp and devise means of detecting these dirty deeds and punishing them accordingly.

A further caveat is that HF trading has led to an increasingly intense arms race with a view to shaving not merely milliseconds, but microseconds off system latency. At some point, the commitment of ever-larger sums of money to slicing ever-smaller fractions of time off trading times, just to be first in line, becomes socially counter-productive. In other words, the last chapter on HF trading has not yet been written.
On the same subject, Matt Levine, a Bloomberg columnist reports, High Frequency Traders Are a Little Too Slow:
High frequency trading is a wonderful subject for study because nobody agrees on what would make it Good or Bad. So academics and practitioners can write papers about how it is Good, or how it is Bad, and they don't particularly contradict each other because they measure different things and the actual thing that one wants to measure is hard to nail down and would probably be hard to measure even if you knew what it was.

So here we are with an interesting European Central Bank working paper from Jonathan Brogaard, Terrence Hendershott and Ryan Riordan about high frequency trading.* They're mostly for it, which has naturally gotten them some attention. They think that the things you should measure are along the lines of "does high frequency trading improve market price discovery?" and "does it provide liquidity?" and I guess if they thought it was Bad, they'd be asking different questions. But they answer yes to their questions: They find that high frequency trading improves price discovery, and that it does not cause instability by withdrawing liquidity during volatile periods.

You can quibble with these points if that's what you like to do with academic papers, and I don't know what else one would do with them, really. The "improves price discovery" thing comes with the important caveat, "for about three or four seconds"; after that the information is incorporated into the market. So HFT makes markets three seconds more efficient. Is that good?That question plummets quickly into metaphysics and, thus, into this footnote.**

You can quibble with the instability point too, but not up here.***

But here is an oddity. The authors look at what happens when negative macroeconomic news is announced, and then draw this chart (click on image below):


So: Starting about one second before the bad news is announced, HFT firms are actively selling (that is, demanding liquidity to sell shares -- red line). Starting at around the same time, stock prices are going down (gold line, right axis). On the other hand, starting about two seconds before the bad news is announced, HFT firms are passively buying. That is, they're supplying liquidity: They've posted bids and offers, and their bids are getting hit. That's the gray-green-blue-whatever-ish dotted line. The blue dashed line is the net HFT activity. In aggregate, HFTs buy on negative macro news, and would seem to lose money doing so.

The opposite happens on positive news: HFTs end up selling into positive news and losing money. As with negative news, the price changes and HFT liquidity demand occur about a second after the HFT liquidity supply (click on image below):


This is broadly consistent with the authors' view of HFT as a useful provider of liquidity -- basically, HFT firms are acting like market-makers here, taking the opposite side of trades that people want to make on news -- but the timing is quite weird. The apparent interpretation is that HFT firms are being beaten to the punch on economic news, by about one second, and losing money because of it. They leave their bids and offers up going into the news, and someone gets the news just before they do,**** and that someone trades against them and makes money off of them.

An important function of high frequency traders, apparently, is to get taken advantage of by people who are just a bit faster than them.

So that's odd, no?

But it seems to be basically true. The authors' sample of "HFT" is a Nasdaq data set of 26 large independent high frequency trading firms, which excludes big broker-dealers like Goldman who have some HFT strategies, as well as proprietary algorithmic trading firms that trade quickly but don't make a business out of trading constantly. Those firms might be more likely to react to fundamental news than the big pure-HFT firms, who trade based mainly on statistical-arbitrage-type market data (prices and order books) than on actual news releases.***** So the speedy algo traders profit off the ever-so-slightly-less-speedy-in-this-particular-case HFT traders.

What can you conclude from that? Well, for one thing, if your view of "high frequency trading" embraces "anyone who trades real fast with a computer," then you may not find this paper's positive conclusions about HFT entirely soothing. They're really about only one category of high frequency traders -- and the other category seems to be trading against them. If this paper's fast computer traders are Good, then it stands to reason that the fast computer traders on the other side might be Bad. The net effect remains murky.

Also, though, we have talked before about enforcement efforts to crack down on the sorts of fast computer traders who get economic data milliseconds before everyone else. At the time I found that crackdown puzzling, since it seems to protect not individual investors but other, slightly slower fast computer traders. If information comes out at 2 p.m. and your computer gets it at 1:59:59.999 and you try to buy with your information advantage, the only person who's selling to you at 2:00:00.006 is another computer. The little guy or Fidelity portfolio manager or whoever is actually reading the news with human eyeballs is whole seconds behind and thus totally safe.

And here you go. The people getting picked off by "high frequency traders," in the loose sense, when news is announced, are "high frequency traders," in the strict sense. Algorithmic market-makers get picked off by algorithmic speculators. A whole financial-markets drama occurs in the blink of an eye, and all you have to do to avoid it is blink.

* Like a lot of things in financial academia, this has been floating around online for a while in various forms, but it came out today under the ECB's quasi-imprimatur, which is a valuable quasi-imprimatur, so now we are talking about it.

** From the paper:

The fact that HFTs predict price movements for mere seconds does not demonstrate that the information would inevitably become public. It could be the case that HFTs compete with each other to get information not obviously public into prices. If HFTs were absent, it is unclear how such information would get into prices unless some other market participant played a similar role. This is a general issue in how to define what information is public and how it gets into prices, e.g., the incentives to invest in information acquisition in Grossman and Stiglitz (1980).

You might wonder what fundamental research HFT firms are doing to ferret out new information and make it public.

A thought experiment might be, if you delayed HFT access to economic events by three seconds, would they still have three-second advantage over non-HFT traders? What if you delayed them by five minutes?

*** The authors look at HFT behavior in the top 10 percent most volatile days, compare it to the bottom 90 percent most volatile days, and find that HFTs provide similar amounts of liquidity. A plausible model of HFT might be "volatility is profitable but blind panic is bad," meaning that you'd supply more liquidity in the 90-to-99.5 tranche of days but much, much less in the top 0.5 percent. That model would lead to yearly, not biweekly, flash crashes, which is kind of what happens, but the paper looks at the more modest top-10-percent-of-volatility-days thing.

**** And before it comes out? The authors use Bloomberg time-stamps to measure second 0 (the time the news comes out), so arguably second -1 or whatever is the actual time it comes out and it takes some time to get up on Bloomberg, but the trading 2 seconds before the measured announcement time does seem weird.

***** I owe this point to a conversation with Terrence Hendershott, one of the paper's authors. Incidentally, if you accept that HFT firms react only to market prices and orders, and not to fundamental news, then that Grossman-Stiglitz point in footnote ** gets especially metaphysical.
William Barker and Anna Pomeranets of the Bank of Canada also published a brief research paper back in June 2011, The Growth of High-Frequency Trading: Implications for Financial Stability, and concluded:
HFT is playing a significant role in markets today. It began in equities and rapidly spread to other asset classes, such as FX, linking these markets through cross-asset-class trading strategies and heightening  concerns about its relative merits.Yet the overall impact of HFT on financial markets and its ability to penetrate further into financial systems remains unclear.

Although there are benefits associated with HFT, its effects are not yet fully understood, in terms of either growing market penetration or stressed markets. HFT has therefore created new challenges for public policy-makers, who will have to monitor and address the potential risks that HFT poses to financial markets and financial stability. While self-regulated markets may be more likely to address these risks independently, other markets may require a regulatory push in either case, public input and coordination between various financial markets.
Finally, Chris Sorensen of Maclean's reports, The dangers of high-frequency traders:
Greg Mills, the co-head of RBC Capital Market’s global equities division, is sitting in a dimly lit conference room in the bank’s downtown Toronto headquarters. He’s attempting to demonstrate how high-frequency traders, or HFTs, frustrate even the most routine of RBC’s stock trades. “Are you ready?” he asks. Mills taps the spacebar on his MacBook Air and launches a simulation of a hypothetical buy order. Dozens of little squares, each representing a bid or ask order, suddenly begin to fly around the screen.

Mills explains that HFTs launched a flurry of split-second trades the moment RBC hit the send button. “In some instances, the HFTs who we had expected to buy stock from, bought stock ahead of us, and then began to sell stock back to us,” Mills says. The take-home point is RBC paid a fraction of a penny more for each share than it expected to—and that can quickly add up. “We’re trading hundreds of millions of shares a day, and this implicit tax is constantly being extracted,” he says. “It’s being extracted from real investors.”

Mills is far from the first to raise concerns about the impact of HFTs. Their controversial approach relies on super-fast computers and complex algorithms to make hundreds of rapid-fire trades in the blink of an eye, collecting a few pennies each time. Though the technique is most closely associated with firms like Citadel and Jump Trading, it’s also used by a host of other financial players, including RBC (although Mills argues that RBC doesn’t engage in any “predatory” behaviour). Either way, high-frequency trading has become a major force in the stock markets, accounting for about half of all trades in the U.S. and slightly less in Canada.

Yet, despite its rapid growth over the past decade, the impact of high-frequency trading on the overall market is poorly understood. HFTs have been blamed for exacerbating the 2010 “flash crash,” when the Dow briefly plummeted 1,000 points in just a few minutes, and they’re at the centre of a recent scandal involving Thomson Reuters, which was selling key market data to high-paying clients two seconds before everyone else. “Who’s going to invest knowing they’re set up to lose?” New York Attorney General Eric Schneiderman recently asked.

Proponents of the highly automated approach point out that HFTs mostly compete with other computers, and that the benefits HFTs bring—like increased liquidity—far outweigh any costs. A fraction of a penny, it’s argued, will hardly make a difference to average investors who measure returns in weeks, months or years. But the same can’t easily be said for the giant pension funds and mutual funds where most regular folks park their retirement savings. Equally troubling, the rise of HFTs has called into question the role of stock exchanges, which benefit from the huge volume HFTs trade on their platforms. “I would say the exchanges are complicit in enabling the activities of HFTs,” says Mills, who is one of several people proposing a rival stock market to the Toronto Stock Exchange that promises to clamp down on the practice. “It allows them to execute their strategies and give them an advantage over traditional investors.”

The stock market has always been a great place to lose one’s shirt, but the rise of HFTs offers yet another troubling example of how the system increasingly favours a few sophisticated insiders—more than likely, at the expense of ordinary investors.

High frequency traders employ a variety of strategies, but the common thread in their algorithms, or “algos,” is sheer speed. One common technique is latency arbitrage. It aims to capitalize on the fact it takes digital information longer to reach some places than others. It may take a few milliseconds more for trades on, say, the NASDAQ’s servers in New Jersey to be crunched by America’s clearing house for stock trades and reflected in the National Best Bid and Offer, which is the best available price for a given security. If the HFTs can grab the data and make the calculations before it’s posted on the NBBO feed, they are in a position to make a quick profit—especially if they do it a few thousand times.

How do they get the data before everyone else? For one thing, most HFTs pay big money to “co-locate” their servers in the same buildings as major exchanges, ensuring they have direct access to market information. They have also sparked an arms race in fibre optic and other electronic connections between major trading centres around the globe. Due to demand from HFTs and other electronic traders, new fibre optic cables were laid between Chicago and New York that went through the Allegheny Mountains instead of following railroad right-of-ways. HFTs are also increasingly looking to above-ground microwave transmitters to carry their signals since, unlike fiber-optic cables, microwaves promise a direct, line-of-sight route that avoids the curvature of the Earth. One company, Perseus Telecom, is even proposing a network of microwave transmitters over the Atlantic held aloft by a network of weather balloons—suggesting no idea is too crazy when there’s potentially millions to be made with little or no risk.

While the strategy—speed—is simple, HFTs’ methods can be complex. Rebate arbitrage takes advantage of the rebate incentives stock exchanges pay out to liquidity providers—anyone who stands ready to buy or sell securities at a quoted price. It doesn’t matter if the HFTs make money in the trades themselves—as long as they don’t lose more than the value of the rebate. Another approach attempts to quietly detect patterns—a big block of shares being unloaded in small chunks—and then rapidly trade on the information. Still others attempt to trick other computers into launching a flurry of trades in the hopes of capitalizing on a rapid price movement.

Of particular concern for securities regulators is whether all of this light-speed trading has increased the volatility of equity markets, contributing to reduced investor confidence. In addition to the “flash crash,” there have been a growing number of painful stock market glitches in recent years that were either related to, or exacerbated by, computers run amok. In August 2012, Knight Capital lost nearly $440 million after buggy software flooded the market with orders during a 45-minute period. Stuck with its huge position, Knight was later forced to unload the shares at a massive loss. The firm nearly went bankrupt and was bought by Getco Holding Co., another high-frequency shop, earlier this year. Then, in August, a trading glitch shut down the NASDAQ for three hours. Another NASDAQ glitch also marred last year’s Facebook IPO. “These events involved relatively basic, albeit serious errors,” Mary Jo White, the chairman of the U.S. Securities and Exchange Commission, said in a recent speech. “Many could have happened in a less complex market structure. But the persistent recurrence of these events can undermine the confidence of investors and public companies in the integrity of the U.S. equity market structure as a whole.”

That waning confidence may be among the reasons 2013 is shaping up to be the slowest year for stock trades since 2007, according to some estimates.

Not everyone agrees high-frequency trading is a problem that needs solving. Rishi Narang, a co-founder of high-frequency trading firm Tradeworx, argues that it makes no sense to denigrate HFTs and lionize investors like Warren Buffet for fundamentally doing the same thing: betting on the future of stock prices. “People have jumped to a very questionable conclusion that predicting further out into the future—à la Warren Buffett—is okay, while predicting into the extremely near-term future isn’t okay,” Narang told financial blogger Jeffrey Dow Jones. “There is a sort of ‘holier-than-thou’ attitude taken on by many people in the press, the public, and even the tax man about longer-term holding periods.”

Kevan Cowan, the president of TSX Markets and the head of TMX Group’s equities division, is similarly unconvinced that HFTs are fundamentally different than human traders. He points to the controversy surrounding latency arbitrage and notes that it’s been done for more than a century. Prior to the use of telegraph machines, he says, “brokers literally competed to hire the fastest physical runners to run their quotes from the floor to the broker.”

Even so, getting a grip on high-frequency trading has been difficult for both regulators and the public at large. In part, that’s because many of the strategies employed by HFTs are deliberately designed to be stealthy, and because most exchanges don’t share trading information widely. Canada has a unique advantage in that all of the country’s exchanges feed their trade data in real time to the Investment Industry Regulatory Organization of Canada, the industry’s self-governing body. Using that data, IIROC studied a three-month period in 2011 and found that HFTs accounted for 22 per cent of trading volumes, 32 per cent of the dollar value of shares traded and 42 per cent of all trades executed. Victoria Pinnington, IIROC’s vice-president of trading review and analysis, said the next phase of the study will focus on the impact of HFTs on investors. “We feel that studying the issue in depth will help us to shape a regulatory response,” she says.

Many in the industry don’t want to wait. RBC has joined with Barclays, CI Investments, IGM Financial, ITG Canada and PSP Public Markets to create a new stock market venture called Aequitas Innovations that would take steps to limit the impact of HFTs. That includes employing a electronic countermeasure system designed by RBC to slow down certain data transmissions to markets so that orders all arrive simultaneously, giving HFTs no opportunity to capitalize on latency issues. “If we do this at the exchange level, then every broker dealer that uses Aequitas for their clients can benefit,” says Mills, Aequitas’s chairman.

Not surprisingly, TMX’s Cowan takes issue with the suggestion that investors are ill-served by the current market structure. He says electronic trading, and efforts to promote it, have largely been a positive development because they’ve increased market liquidity and narrowed bid-ask spreads (the cost of buying and selling stocks). As for selling HFTs and other electronic investors direct access to the TSX’s servers, he stresses that such services simply acknowledge the reality of today’s stock market, arguing that in the absence of co-location opportunities, savvy traders would simply try to “lease or buy the building next door.”

Instead of banning HFTs outright or making it more difficult for them to operate, Cowan says a better approach is to identify when HFTs are behaving in a manipulative fashion and clamp down on them just like any other investor. “If somebody is looking to purposely move a market, that’s illegal under current rules and should be enforced,” he says. As for the larger question of electronic trading and volatility, Cowan adds that, “what’s important is investing in the tools to make sure we have the appropriate protections in place.”

Even so, investors can be forgiven for thinking the stock market increasingly resembles a casino—a place that holds equal amounts promise and heartbreak, and where the real money is made behind the scenes.
I'm glad to see PSP Investments is among the backers of the new stock exchange. Unfortunately, this will not make a significant difference unless it catches on all over the world and other big investors demand changes to limit the impact of HFTs on all major exchanges, including futures exchanges.

I leave you with a fascinating thriller from VPRO about Haim Bodek, aka "The Algo Arms Dealer," a genius algorithm builder who dared to stand up against Wall Street (h/t, Ari Tagalakis). After watching this documentary, you will gain a better understanding of how "quants" have forever changed the financial landscape, for better or for worse, and how your pension contributions are their "dinner or low hanging fruit."

Kudos to Haim Bodek (@HaimBodek) for exposing the destructive effects of algorithmic trading and blowing the whistle on the Wall Street code. I suspect many "quantitative geniuses" making oodles of money on Wall Street will wake up one day and realize they've wasted their tremendous brain power on such trivial pursuits. By then it will be too late, they will be on antidepressants for the rest of their lives.