Ethics, Cost-Benefit Analysis, and the HFT Debate

Last year’s best-seller by Michael Lewis, Flash Boys,[1] ignited a firestorm of debate on the subject of high-frequency trading, or HFT. Lewis’s central claim is that the stock markets are “rigged,” with HFT shops skimming sizable amounts off of trades by other, slower traders. The exchanges are allegedly in on the game, as they enable HFT through co-location, private data feeds, and the development of complex special order types, all in return for sizeable fees. Although SEC Chair Mary Jo White quickly rejected Lewis’s claim,[2] public debate continued and a number of lawsuits were filed against the exchanges and HFT firms.[3] While HFT presents complex legal and economic questions, what may be most important is the general mistrust of Wall Street on the part of investors that the debate reveals.

The confluence of a number of forces led to the current situation: the implementation of Regulation NMS in 2007, the application of information technology to the financial markets, and the introduction of maker/taker pricing systems at the exchanges, among others. In both its beneficial and not-so-beneficial effects, HFT primarily operates by exploiting informational advantages measured in milliseconds and even microseconds between the various exchanges that comprise the “national market system.” The goal of Reg. NMS was to foster price competition among the various exchanges, and it was to large extent successful in this. At the same time, however, the digital revolution came to the financial markets as the descendants of the “SOES bandits” at Datek Securities and elsewhere pioneered algorithmic trading programs that could act on information in fractions of a second. Also crucial was how the maker/taker pricing system revolutionized the business model of the exchanges. In a maker/taker system, an exchange charges traders a small fee for “taking” liquidity, i.e., hitting a posted quote. In turn, it pays some of this fee back to the trader whose quote is hit. The exchange typically pays out 2/3rds of the fee as a rebate, keeping 1/3rd for itself.

Algorithmic traders found a variety of ways to profit in this new trading environment. These techniques range from the relatively passive to the highly aggressive. Many are simply contemporary versions of traditional market-making strategies, while others appear to cross the line into high-tech versions of market manipulation.[4] Most HFT activity relies on co-locating a server in the building housing an exchange’s server to reduce transmission times to the lowest possible: 0.3 milliseconds or so for messages travelling from an exchange’s server to a co-located computer and back. Co-location thus allows for “latency arbitrage,” where traders exploit the timing differences between various market centers, which are now just the buildings housing each exchange’s servers. The exchanges charge tens of thousands of dollars a month for the privilege of co-locating in their facilities.[5] They also offered “flash orders,” which exploited Reg. NMS Rule 602(a)(i)(A)’s exception to the general rule that best bids and offers be sent to the securities information processor or “SIP.” While flash orders were ostensibly provided for the purpose of determining whether or not a trade can be found at a price superior to the national best bid/offer or “NBBO,” critics charge that HFT shops used them to gain a “sneak peek” at the direction of prices in the markets.

Also controversial are the exchanges’ direct and enriched data feeds, which provide a greater depth of data to traders than that provided to the SIP, including information on cancellations, modifications, and executions of orders. Finally, the exchanges developed special order types, including the notorious “Hide Not Slide,” which are far more complex than the traditional market and limit orders. Many of these new order types exploit market microstructure conditions such as maker/taker pricing and Reg. NMS’s prohibition against locked and crossed markets.

All of these techniques allow those who master them to extract small gains on millions of trades daily, resulting in unusually high profits at the top HFT shops.[6] Reports that Kansas City-based Tradebot had not lost money on a single day in four years, and that Virtu Financial had only one day of losses in five years, illustrate that for the leading HFT shops profits have been a sure thing. At its most basic, HFT confers advantages on a small subset of traders that can never be overcome by others, leading to the complaint that “it’s unfair.”

The exchanges and defenders of HFT have a simple response: their services are open to all who can pay for them, and those who profit have done so by making the requisite investments in IT infrastructure and personnel. While this is prima facie true, it masks the fact that HFT creates a two-tiered system in the financial markets, where a small subset of traders can profit at the expense of others in ways that are often hidden or deceptive. The story of how trader Haim Bodek learned about the special order types developed by an exchange is a case in point. Wall Street Journal reporter Scott Patterson recounts how Bodek only learned why he couldn’t access posted quotes using limit orders when an exchange representative told him at a cocktail reception that he wasn’t using the right type of order.[7] According to Bodek, he had complained to exchange employees numerous times before about his problems and no one informed him of the new order type. The SEC’s recent administrative proceeding against EDGX Exchange, Inc. substantiates the charge of selective disclosure for at least one exchange.[8]

How best to regulate the current computerized trading environment, then? The complexity of the system makes it hard to know exactly what is happening inside it. Add to that the fact that significant trading occurs in “dark” markets, although how much exactly is unknown. It is therefore difficult to discern the precise economic impact of HFT and what the effects of any regulatory changes would be. It is also difficult to disentangle HFT’s harmful effects from its role in the beneficial revolution associated with decimalization and Reg. NMS that has significantly lowered transaction costs for investors. These “knowledge problems” cast doubt on the usefulness of the cost-benefit analysis traditionally employed by regulators.[9]

In these circumstances, regulators ought to base any new regulatory strategy on general legal and moral principles instead of a cost-benefit approach. Three primary ones relevant to HFT are freedom from misrepresentation, a level playing field, and institutional integrity. These can all be grounded in a principle of reciprocity in exchange that traces back to Aristotle’s Nichomachean Ethics.[10] Aristotle believed that while one might legitimately trade on the basis of comparative advantage, differing needs, or differing beliefs about the future, an exchange is just when the two sides of the transaction are proportionately equal. Since money functions as the common measure of goods, a transaction where the amount paid for something is equal to that thing is just. This understanding of trade has ethical overtones, because it implies that for a transaction to be just, the price must be an accurate measure of an item’s worth. If one is deceived as to the true nature of the goods, or their price, the transaction is unjust. In a just transaction, on the other hand, one could envision taking the other side of the exchange if one had different needs or even different beliefs about the future. But one would not consent to a transaction where the nature of the goods was disguised or the price did not otherwise reflect an item’s true worth.

From this general principle of reciprocity come three more specific principles that are part of the legal and ethical basis of commercial law. First, since we wouldn’t agree to a transaction in which we were lied to or deceived, we rely on the legal system to protect us from fraud and misrepresentation. The mechanisms of disclosure and remedies in securities law implement the principle of freedom from misrepresentation. Second, the law should, to some degree at least, foster a level playing field for investors. This is expressed in the ideas that investors should have equal access to the same basic information about companies, and that the markets should treat similarly situated participants similarly. While the law of insider trading struggles mightily with the idea of a level playing field, and trading on the basis of inside information alone, without a violation of a fiduciary duty, is not illegal in the U.S., a level playing field does exist as a goal or ideal of the American financial system. Finally, the concept of institutional integrity means that institutions will treat various groups of stakeholders fairly, acting in accordance with both explicit and implicit commitments to stakeholders as well as holding a coherent, non-contradictory combination of commitments.

The HFT debate implicates all three principles. The practices of “spoofing,” “layering,” and “momentum ignition” all involve the manipulation of prices by means of algorithms in violation of the principle of freedom from misrepresentation. They are in fact just contemporary versions of market manipulation, and have been prosecuted as such.[11] A much more difficult challenge is the fact that HFT creates a two-tiered trading system in which many traders will inevitably lose, even if by small amounts. Just as the law of insider trading struggles with the tension between rewarding information gathering, analysis, and risk-taking on the one hand, and enforcing equal access to basic information on the other, regulators will struggle with creating a level playing field in the computerized stock markets. One radical but promising proposal is to move from continuous pricing to batch auctions, at say every second, for equities.[12] And the new alternative trading system IEX, founded by Flash Boys protagonist Brad Katsuyama, is a fascinating test of whether there is market demand for a trading venue that attempts to level the playing field between traders. IEX purposefully introduces a 350 microsecond delay in orders, refuses co-location and proprietary data feeds, and charges a flat fee for all trades instead of maker/taker pricing. Finally, HFT appears to incentivize the exchanges to cater to HFT clients at the expense of other traders, thereby compromising their institutional integrity. This will also present a regulatory challenge, because their new business model, where maker/taker pricing predominates, forces the exchanges to compete for order flow for their survival. At the very least, however, exchanges should be transparent concerning their commercial relationships with different categories of customers.

Application of these principles will involve boundary-drawing in highly complex terrain, but they are familiar principles for regulators. The history of American securities law follows the history of Wall Street scandals, and the political message from the Flash Boys furor seems to be that fairness concerns regarding the financial system are still important to Americans six years on from the financial crisis. Looking to these principles of fairness can guide regulators charged with policing the markets in a way that the standard cost-benefit analysis may not.

ENDNOTES

[1] Michael Lewis, Flash Boys: A Wall Street Revolt (W.W. Norton 2014).

[2] Mary Jo White, Enhancing Our Equity Market Structure, Speech before Sandler O’Neil & Partners, L.P. Global Exchange and Brokerage Conference, June 5, 2014.

[3] City of Providence, Rhode Island v. BATS Global Markets, Inc. et al., 14-CV-2811 (S.D.N.Y. April 18, 2014); Lanier v. BATS Exchange, Inc., et al., 14-CV-3745 (S.D.N.Y. May 23, 2014). Also noteworthy is N.Y. Attorney General Eric Schneiderman’s complaint against Barclays Capital, Inc. for misrepresentations concerning its dark pool Barclays LX. See New York v. Barclays Capital, Inc., Complaint No. 451391/2014 (Supreme Court of the State of New York, County of New York, June 25, 2014).

[4] See Gregory Scopino, The (Questionable) Legality of High-Speed “Pinging” and “Front Running” in the Futures Markets, 47 Conn. L. Rev. 607 (2015).

[5] See generally Donald MacKenzie, Be Grateful for Drizzle, London Rev. Books, Sept. 11, 2014.

[6] See Matthew Baron, Jonathan Brogaard & Andrei Kirilenko, Risk and Return in High Frequency Trading, April 2014, available at http://www.princeton.edu/~mdbaron/BBK_HFT_risk_return_2014_0504.pdf.

[7] See Scott Patterson, Dark Pools: The Rise of the Machine Traders and the Rigging of the U.S. Stock Market 47-51 (Random House 2013).

[8] In the Matter of EDGA EXCHANGE, INC. and EDGX EXCHANGE, INC., SEC Administrative Proceeding File No. 3-16332 (Jan. 12, 2015).

[9] While Cass Sunstein defends cost-benefit analysis as the best tool available for complex regulatory problems despite these “knowledge problems,” John Coates casts doubt on the efficacy of cost-benefit analysis for problems of financial regulation. See Cass R. Sunstein, Cost-Benefit Analysis and the Knowledge Problem, available at http://papers.ssrn. ssrn.com/sol3/papers.cfm?abstract_id=2508965; John C. Coates IV, Cost-Benefit Analysis of Financial Regulation: Case Studies and Implications, available at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2375396. See also Jeffrey N. Gordon, The Empty Call for Cost-Benefit Analysis for Financial Regulators, 43 J. Legal Stud. S351 (2014).

[10] See Aristotle, Nichomachean Ethics V.5.

[11] See Charles Korsmo, High Frequency Trading: A Regulatory Strategy, 48 U. Rich. L. Rev. 523, 551 (2014)

[12] See Eric Budish, Peter Cramton & John Shim, The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response, Feb. 2015, available at http://faculty.chicagobooth.edu/eric.budish/research/HFT-FrequentBatchAuctions.pdf.

The preceding post comes to us from Steven McNamara, Assistant Professor of Business Law at the Olayan School of Business, The American University of Beirut. The post is based on his current paper entitled “The Law and Ethics of High-Frequency Trading,” which is available here.