Streetwise Professor

A recent Wall Street Journal article (subscription required) discusses growing unease among brokerage firms over rising trading fees at NASDAQ and NYSE. European traders have expressed similar disquiet at rising fees on European bourses. The heady valuations of publicly traded exchanges, such as the CME and CBT, are predicated in part on the belief that they have pricing power that they will be able to raise fees in the future.

Is it plausible that exchanges have market power, and therefore can charge supercompetitive prices? In a nutshell: hell yes. There is little doubt that exchanges have considerable market power. Over the years I’ve written several articles on the subject setting out the arguments and evidence, but the essence of the story is rather straightforward. (This article sets out the argument in a non-mathematical way.) When some traders have better information than others, the relatively uninformed are better off when they concentrate their trading in a single marketplace. This creates a network effect. Traders like to trade where others trade. There are therefore natural monopoly elements to trading. (In the future I plan to blog about things that weaken the network effect and therefore facilitate competition between trading venues.) Moreover, it is hard to contest an incumbent monopolist’s position. (Cf., Eurex’s not-so-excellent US adventure, ditto EuroNextLIFFE.) Attracting liquidity to a new platform requires the simultaneous defection of numerous traders from the incumbent. This is a daunting coordination problem.

Hence, DTB/Eurex’s victory over LIFFE in Bund futures in 1998 is the exception rather than the rule. As I’ve shown in a working paper , moreover, that was something of a fluke for two reasons. First, DTB/Eurex had a less severe coordination problem because the German banks that were the source of large order flows also owned the exchange, so it was easier to build a base order flow to challenge LIFFE. Second, when DTB/Eurex had attracted enough volume to reduce the price impact disparity with LIFFE, it cut fees aggressively and LIFFE did not respond. If LIFFE had responded in kind rather than dilly-dallying for 3 crucial months, it might have hung on to a big chunk of the Bund business.

The CBT and CME learned from LIFFE’s errors and cut prices aggressively when faced with the prospect of entry; it’s always much more satisfying to learn from others’ screw ups than one’s own. Moreover, neither challenger could tap a block of affiliated order flow to build liquidity in contracts offered by the incumbent exchanges. As a result, the entrants weren’t able to repeat the Eurex coup on this side of the big pond.

When evaluating the prospect—or reality—of rising exchange fees, its important to remember that exchanges have always had market power, but they just exercised it in different ways. The traditional member-owned, not-for-profit exchanges did not exploit their market power by charging supercompetitive transaction fees. That would have cut into their members’ ability to make money by reducing the derived demand for brokerage and market making services. Instead, traditional exchanges exploited market power by limiting entry. With a few exceptions (primarily resulting from legislation and regulation rather than exchange choice) traditional member-owned exchanges limited the number of members. They also had rules that advantaged floor traders at the expense of others. These measures allowed the members to earn rents. As I’ve shown in a couple of articles, network effects make it possible for an exchange to choose a suboptimally small membership, raise trading costs, and yet face no credible competitive threat. Thus, exchange customers have historically paid supercompetitive prices for floor brokerage and floor market making services rather than supercompetitive exchange transaction fees.

Things are changing now that exchanges are moving away from the mutual non-profit (“MNP”) form. Investor-owned exchanges in particular have a new clientele to serve. Rather than catering to the interests of exchange members (typically floor traders or those who leased floor trading rights), some exchanges now respond to the interests of investors. For profit investor owned (“FPIO”) exchanges have no incentive to do things that inflate liquidity or brokerage costs. Indeed, they have the very opposite incentive. Higher profits to brokers and market makers reduce the derived demand for the services exchanges offer (namely, access to the trading engine.) As a result, they want to minimize barriers to entry by liquidity suppliers and suppliers of brokerage services. Exchanges will exploit the market power conferred by network effects by charging supercompetitive transaction fees.

High exchange fees are a more transparent way of exploiting market power. Market power wasn’t a secret to savvy folks in the old regime; I’ve talked to many upstairs traders, including some very successful ones, who routinely complained of being “robbed by the floor.” However, I imagine a lot of folks were unaware how limitations on entry and trading rules inflated trading costs. In-your-face increases in trading fees attract more attention, but the bottom line is that it’s just a different way of taking advantage of network effect-induced market power.

As an aside, I’ve been surprised for years at how little academic commentary and regulatory scrutiny has been directed at exchange membership limits. Economists since Friedman (in his dissertation on the medical profession) and Stigler (and probably before—I just learned it from Stigler and Sam Peltzman) have noted that entry restrictions are the most straightforward way for regulators or professional organizations (e.g,. the AMA) to cartelize an industry and create rents for producers. To most economists, the use of entry restrictions is prima facie evidence of the inefficiency of a regulatory policy. Yet although I’ve read pretty much all I can get my hands on about exchanges, I can’t recall seeing anyone level similar criticisms against exchanges despite the fact that they have almost universally imposed such limits. Indeed, it’s not uncommon to hear exchanges lauded as the exemplars of perfect competition. ‘Tis a puzzlement. (Hat tip to anybody who can provide a cite contradicting my assertion regarding the absence of academic criticism of entry limits at exchanges.)

Is there any way of comparing the relative efficiencies of the old and new monopolies? Looking at output—trading volume—may provide some evidence. IPE experienced an appreciable volume jump when it closed the floor, which would suggest that the new model is more efficient than the old. Other comparisons of this type could be illuminating.

The moral of the story is that exchange market power inheres in the fundamental nature of trading, but that the means by which an exchange reaps the rents of market power depend on its organizational and ownership form.

It may be the case that the transparency of exchange fees has regulatory and anti-trust consequences. As exchanges become more like traditional firms, they may draw more anti-trust scrutiny. That will be, as Arte Johnson used to say, verrry interesting.

Update. I followed up on the “note to self” on Internet pricing (see below). There were indeed several papers on Internet pricing schemes that were intended to address the congestion issue. Salient examples include Jeffrey MacKie-Mason & Hal Varian, “Some Economics of the Internet” and the same authors’ “Pricing the Internet.” Alan Wiseman’s “The Internet Economy” (2000) summarizes several pricing proposals. Perhaps not surprisingly, several Internet pricing proposals parallel the trading system capacity market schemes that I outline in this post. The tâtonnement process is similar to the MacKie-Mason & Varian auction approach. The capacity right system is analogous to David Clark’s (1997) expected capacity pricing mechanism. End Update.

After a series of embarrassing technology-related stumbles in 2005, the Tokyo Stock Exchange outdid itself with its early closing on Wednesday, 18 January 2006. The TSE’s electronic trading system has a built-in constraint that prevents it from handling more than 4 million transactions (regardless of their size) in a day. A flood of sell orders washed over the exchange when it was announced that Japanese authorities had raided the offices of internet highflier Livedoor during an investigation of securities fraud.

This TSE constraint is a new one on me. I was well aware of what one might term flow constraints—the number of messages (bids, offers, cancellations, transactions, confirmations) that a system can handle per second or per minute, but I was heretofore unaware of the possibility of an “integral constraint”—specifically, that the sum of trades over a day not exceed some preset limit. I’m not a hardware expert, but I would imagine that this constraint arises due to a limitation on system storage. Each trade requires storage of a record that details all relevant characteristics of each transaction—price, quantity, date, time, broker, buy/sell, party, counterparty, etc.—regardless of trade size. Thus, whereas flow constraints are attributable to limits on bandwidth or processing capacity, the TSE constraint is likely due to a limitation on the ability to store all of the transaction records.

Any electronic trading system is subject to capacity limits. Eurex had some capacity issues in the late-90s. NYMEX is considering an upgrade to its electronic trading systems and a possibility of using GLOBEX due to the capacity constraints inherent in its legacy ACCESS system (which experienced problems when volume surged after the London terror attacks in July, 2005).

Every open outcry system is also subject to capacity limits: recall the bottleneck created by slow printers at NYSE specialists’ posts during the October ’87 crash, or the “back office crisis” of the 1960s. Open outcry exchanges are constrained by their capacity to direct orders to the floor, and the capacities of floor brokers and market makers to process, execute, and financially carry trades. (OTC markets have capacity constraints too—cf. the CDO market.)

Capacity is limited because it is costly. It is uneconomic to have capacity to handle all possible contingencies. Therefore, exchanges must decide on how much capacity to install. This raises two issues.

First, how much capacity is optimal? Second, how does one allocate scarce capacity?

These questions are closely related. In particular, if there is a price mechanism that allocates capacity efficiently, and which discovers the shadow value of a unit of capacity, exchanges will be able to make good capacity choices. In the absence of a price-based allocation mechanism, it is much harder for exchanges to choose the right capacity.

The trading industry is not the only one that must answer these questions. These have been key questions in the electricity business since Edison first flipped the switch on the Pearl Street Station in New York in 1882. Since 124 years later the electricity industry is still experimenting with different institutional approaches to capacity allocation and planning, we shouldn’t be too sanguine about the prospects for a quickie solution in financial trading.

Interestingly, there are some similarities between the trading and power capacity conundrums. In particular, at least historically in the electricity business the ultimate consumers of electricity have not paid prices that fluctuate in real time to reflect fluctuations in the scarcity of generating and transmission capacity arising from demand changes, generation outages, etc. Steven Stoft calls this the “First Demand Side Flaw” in electricity markets. Although there are numerous proposals to improve metering and measurement technologies to permit this, widespread adoption of such measures is not likely any time soon.

Similarly, at present, securities and derivative trading systems do not have system usage fees that fluctuate with system usage. Indeed, most systems charge fees on the basis of completed transactions and charge zero prices for other actions that utilize system resources, such as the submission of bids and offers, changes in standing bids and offers, and cancellations. In essence, users pay a zero price at the margin for their consumption of system resources.

This is an issue that has been analyzed in the property rights economics literature that builds on Coase’s insight that it is costly to operate a price system. In the electricity context, real time pricing involves investment in metering equipment. This is a non-trivial cost. In the exchange context, it is costly to monitor, record, store, and bill every system user action. Indeed, creating such a capability would require additional investment in system capacity. Moreover, such a system imposes costs on users, such as, inter alia, the cost of monitoring the accuracy of billing. The question arises, then, as to whether the costs of implementing a capacity pricing system are smaller or larger than the benefit. The benefit arises from the fact that when a scarce resource is unpriced it is overutilized. (Cf. Barzel’s analysis of excessive search.)

Given that the marginal cost curve of using a system is likely close to zero when demands on it are below its capacity, a zero price is right most of the time. When demand bumps against the capacity constraint, however, the zero price is very costly. The exchange must find some non-price means to allocate capacity—such as a shutdown or a system slowdown. The hue and cry over the TSE’s action suggests that a shutdown is very costly (especially as it is likely to occur when information is flowing rapidly and therefore people desire to trade a lot.) Even a slowdown is costly, as traders who due to a slowdown have submitted orders only to find that they cannot cancel or revise them, or who do not know whether their orders have executed, will attest. Traders are typically control freaks who flip out when system problems reduce or eliminate their ability to control their trades and positions.

The problem with non-price rationing is that it impedes the efficient allocation of system resources among different customers with differing reservation prices: those with high willingness to pay may be cut off, but those with a low WTP may be able to trade. Moreover, absence of prices deprives exchanges of information about the value of capacity, which means that they are flying blind when deciding how big to make a trading system.

A price system could conceivably address these problems, and it is interesting to contemplate how such a system would work. It seems challenging—perhaps more challenging than in electricity markets. In electricity, except when generating capacity is completely committed, the value of an additional unit of generation is given by the marginal cost of production, which can be measured with some accuracy in real time (through generators’ bids, for instance). In the exchange context, however, the shadow price of capacity Q is given by the willingness to pay of the marginal consumer. How can this be determined in real time?

One can envision (theoretically) a tâtonnement process. Users submit messages (quotes, cancels, etc.) assuming that the system is unconstrained and the price of system resources is zero. The system evaluates whether these messages exceed system capacity. If so, the price of utilization of system resources is raised slightly, and users resubmit. The price is increased until the capacity constraint is just binding.

The operation of such a tâtonnement process in a continuous market seems impractical. Are there alternatives? One can also imagine the creation of capacity rights and a capacity market. For instance, market users could be required to have capacity rights (which in aggregate equal system capacity) in order to trade. These rights could be traded in a bilateral market—or perhaps the exchange could also provide a mechanism to trade these rights in a continuous market. During most periods the price of the capacity right would be zero. When capacity is constrained, or there is an appreciable probability that capacity will be constrained (one can think of the capacity right as being similar to an option because the value of the right to use capacity is a convex function of capacity utilization, so the capacity price will have some extrinsic value), those who have a high demand to trade can acquire it from those less interested in trading.

Given that settling transactions in anything—including rights to capacity—takes time, I am skeptical that this is a practical way to ensure that those with the highest willingness to pay are not rationed out during a capacity crunch, particularly one that is unexpected (as is likely to be the case in financial markets.) Certainly such a mechanism can ensure the allocation of trading rights to those who anticipate having a high demand to trade during a capacity shortage, so this is better than nothing. That is, those who anticipate having the high WTP can by the capacity option—the right to trade—ex ante. To the extent that ex ante evaluations of WTP track real time WTPs, this mechanism will allocate scarce system resources pretty efficiently and generate information on the value of capacity that exchanges can use to make investment choices.

Implementation of this approach also requires enforcement of the right: how do you know somebody has exceeded their limit, and how do you prevent them from doing so? This seems to me to be a non-trivial problem. Things are likely to be particularly complicated for integral constraints like the one that caused the TSE problems.

To my knowledge, neither the tâtonnement nor the capacity right approach have been even proposed in financial markets, let alone developed. (I do recall reading about pricing of the Internet, which raises similar issues. Note to self: check this out.) This suggests that for the foreseeable future that exchanges and market users will have to live with non-price capacity allocation during periods of market stress.

The absence of a price mechanism that discovers the value of capacity deprives exchanges of information needed to make efficient capacity investment decisions. So how much capacity should exchanges invest in and how do they figure this out? Here again the electricity experience is somewhat informative, and somewhat discouraging. Utility planners traditionally utilized the concept of “value of lost load” (“VOLL”) for system planning purposes. VOLL is an estimate of the cost of “shedding load,” i.e., of turning off customers’ lights in the event that electricity demand exceeds the physical capacity available to produce it. Due to the First Demand Side flaw, there is no equilibrium in prices when the (vertical) demand curve is to the right of system capacity, so it is necessary to shut people off. As Stoft shows, if you assume you can set VOLL correctly (insert economist joke here), market participants will make the efficient capacity choice. After all, VOLL is the opportunity cost of a unit of capacity.

The problem arises, of course, with determining the right VOLL. The VOLL in power markets is typically set arbitrarily. (Australia uses VOLL pricing and has taken a somewhat more systematic approach to estimating it.) Set VOLL too high, and you get too much capacity. Set VOLL to low, and you get too little.

So what is the VOLT—the “Value of Lost Trades”—in a financial market? Beats me, but it is worth some investigation by those who have skin in the game. I’m also curious as to the criteria that exchanges use when choosing system capacity. Do they have some measure of VOLT in mind? Where does this number come from?

In the meantime, it may be worthwhile to cut the TSE some slack. After all, all we know for certain is that an exchange that never hits its capacity limit has inefficiently invested in too much capacity. Without knowing the VOLT, it is much more difficult to evaluate whether the observed frequency of outages is too high or too low. Maybe TSE has the right capacity. Customer complaints about outages aren’t that informative about VOLT, because they don’t directly pay the price for capacity—it’s easy to bitch when somebody cuts off your freebies.

I also wonder how political and regulatory processes will impact exchange capacity planning and investment. The Japanese government has made its disappointment with TSE very clear. Japan’s Economy Minister, Kaoru Yosano has said “[a] Stock exchange that can’t carry on trading simply doesn’t deserve to exist.” There is reason to be concerned that governments will pressure exchanges to overinvest in capacity. Zero tolerance plays well in the press, but ignores the economic reality that trade-offs are part of life. It would be better to step back and apply good economics to evaluate these trade-offs.

Here begins yet another blog–which immediately raises the question: Why? A blog is a peculiarly 21st century vanity, and I set out with no expectations that I will amass a large readership. The field is so crowded, and many of the subjects that I will discuss are so arcane, that it would be foolish to expect otherwise. Indeed, I imagine that this blog is as likely to be read as the greeting plaque on the Viking space probe.

So why bother? In all modesty I think I can claim a decent reputation in a few specialized areas of economics and finance, notably the economics of exchanges and commodity markets. I have written about these subjects in academic publications for over two score years, and plan to continue to do so. However, traditional academic forms–journal articles, and to a lesser degree, books–are highly structured and highly limiting. There are many interesting subjects and ideas that do not fit comfortably in these traditional academic genres. Some ideas are too small in and of themselves to warrant publication in a journal–even a minor one–but too important to be ignored altogether. Some ideas are promising but insufficiently developed. Perhaps most important, traditional academic publication is inimical to discussion and analyis of current and topical subjects.

The blog is a more immediate, fluid, dynamic, and contemporaneously interactive medium. It is conducive to the communication of the small truth and the protean idea. It permits immediate analysis of the day’s topical issues. It is a way of reaching people outside the academic community–people who have valuable knowledge and insights, and who have vocational or avocational interests in a variety of subjects. So in a nutshell, this blog is the continuation of research by other means.

What about the name, you ask. The “Professor” part is pretty obvious–that’s what I am/do. The “Street” part echoes the colloquial use of the term “The Street” to refer to the financial markets. Around the world, “the Street” is synonymous with Wall Street. In Chicago, “the Street” refers to the LaSalle Street financial district dominated by the Board of Trade. (As a native Chicagoan, I am partial to the latter of course–hence the background graphic of a 1920s view down LaSalle Street to the famous CBOT building.) Since this blog will focus on financial issues, especially as they pertain to financial exchanges and markets around the world, the “Street” in “Streetwise” accurately describes the subject matter. As for the “Wise” part, well, that is a goal to strive for: I hope that I can express through this blog some wisdom accumulated through years of study and work. In the end, my readers will judge whether I achieve that goal.

The title is also somewhat ironic, and related to my (somewhat arrested) musical tastes. A complementary hat tip awaits the first person to make the connection. (A small reward, you might say, but in the world of Google the cost of obtaining such information is commensurately small.)

Although this blog will focus on financial and commodity markets, I will explore other interests as well. In particular, from time to time I will comment on military and political matters that engage my attention.

So for those of you that have somehow made it through the increasingly dense web to this site–Welcome. I hope you find it of interest. I encourage you to participate actively through comments, as I hope to learn from my readers too.