Streetwise Professor

July 25, 2014

Benchmark Blues

Pricing benchmarks have been one of the casualties of the financial crisis. Not because the benchmarks-like Libor, Platts’ Brent window, ISDA Fix, the Reuters FX window or the gold fix-contributed in an material way to the crisis. Instead, the post-crisis scrutiny of the financial sector turned over a lot of rocks, and among the vermin crawling underneath were abuses of benchmarks.

Every major benchmark has fallen under deep suspicion, and has been the subject of regulatory action or class action lawsuits. Generalizations are difficult because every benchmark has its own problems. It is sort of like what Tolstoy said about unhappy families: every flawed benchmark is flawed in its own way. Some, like Libor, are vulnerable to abuse because they are constructed from the estimates/reports of interested parties. Others, like the precious metals fixes, are problematic due to a lack of transparency and limited participation. Declining production and large parcel sizes bedevil Brent.

But some basic conclusions can be drawn.

First-and this should have been apparent in the immediate aftermath of the natural gas price reporting scandals of the early-2000s-benchmarks based on the reports of self-interested parties, rather than actual transactions, are fundamentally flawed. In my energy derivatives class I tell the story of AEP, which the government discovered kept a file called “Bogus IFERC.xls” (IFERC being an abbreviation for Inside Ferc, the main price reporting publication for gas and electricity) that included thousands of fake transactions that the utility reported to Platts.

Second, and somewhat depressingly, although benchmarks based on actual transactions are preferable to those based on reports, in many markets the number of transactions is small. Even if transactors do not attempt to manipulate, the limited number of transactions tends to inject some noise into the benchmark value. What’s more, benchmarks based on a small number of transactions can be influenced by a single trade or a small number of trades, thereby creating the potential for manipulation.

I refer to this as the bricks without straw problem. Just like the Jews in Egypt were confounded by Pharoh’s command to make bricks without straw, modern market participants are stymied in their attempts to create benchmarks without trades. This is a major problem in some big markets, notably Libor (where there are few interbank unsecured loans) and Brent (where large parcel sizes and declining Brent production mean that there are relatively few trades: Platts has attempted to address this problem by expanding the eligible cargoes to include Ekofisk, Oseberg, and Forties, and some baroque adjustments based on CFD and spread trades and monthly forward trades). This problem is not amenable to an easy fix.

Third, and perhaps even more depressingly, even transaction-based benchmarks derived from markets with a decent amount of trading activity are vulnerable to manipulation, and the incentive to manipulate is strong. Some changes can be made to mitigate these problems, but they can’t be eliminated through benchmark design alone. Some deterrence mechanism is necessary.

The precious metals fixes provide a good example of this. The silver and gold fixes have historically been based on transactions prices from an auction that Walras would recognize. But participation was limited, and some participants had the market power and the incentive to use it, and have evidently pushed prices to benefit related positions. For instance, in the recent allegation against Barclays, the bank could trade in sufficient volume to move the fix price sufficiently to benefit related positions in digital options. When there is a large enough amount of derivatives positions with payoffs tied to a benchmark, someone has the incentive to manipulate that benchmark, and many have the market power to carry out those manipulations.

The problems with the precious metals fixes have led to their redesign: a new silver fix method has been established and will go into effect next month, and the gold fix will be modified, probably along similar lines. The silver fix will replace the old telephone auction that operated via a few members trading on their own account and representing customer orders with a more transparent electronic auction operated by CME and Reuters. This will address some of the problems with the old fix. In particular, it will reduce the information advantage that the fixing dealers had that allowed them to trade profitably on other markets (e.g.,. gold futures and OTC forwards and options) based on the order flow information they could observe during the auction. Now everyone will be able to observe the auction via a screen, and will be less vulnerable to being picked off in other markets. It is unlikely, however, that the new mechanism will mitigate the market power problem. Big trades will move markets in the new auction, and firms with positions that have payoffs that depend on the auction price may have an incentive to make those big trades to advantage those positions.

Along these lines, it is important to note that many liquid and deep futures markets have been plagued by “bang the close” problems. For instance, Amaranth traded large volumes in the settlement period of expiring natural gas futures during three months of 2006 in order to move prices in ways that benefited its OTC swaps positions. The CFTC recently settled with the trading firm Optiver that allegedly banged the close in crude, gasoline, and heating oil in March, 2007. These are all liquid and deep markets, but are still vulnerable to “bullying” (as one Optiver trader characterized it) by large traders.

The incentives to cause an artificial price for any major benchmark will always exist, because one of the main purposes of benchmarks is to provide a mechanisms for determining cash flows for derivatives. The benchmark-derivatives market situation resembles an inverted pyramid, with large amounts cash flows from derivatives trades resting on a relatively small number of spot transactions used to set the benchmark value.

One way to try to ameliorate this problem is to expand the number of transactions at the point of the pyramid by expanding the window of time over which transactions are collected for the purpose of calculating the benchmark value: this has been suggested for the Platts Brent market, and for the FX fix. A couple of remarks. First, although this would tend to mitigate market power, it may not be sufficient to eliminate the problem: Amaranth manipulated a price that was based on a VWAP over a relatively long 30 minute interval. In contrast, in the Moore case (a manipulation case involving platinum and palladium brought by the CFTC) and Optiver, the windows were only two minutes long. Second, there are some disadvantages of widening the window. Some market participants prefer a benchmark that reflects a snapshot of the market at a point in time, rather than an average over a period of time. This is why Platts vociferously resists calls to extend the duration of its pricing window. There is a tradeoff in sources of noise. A short window is more affected by the larger sampling error inherent in the smaller number of transactions that occurs in a shorter interval, and the noise resulting from greater susceptibility to manipulation when a benchmark is based on smaller number of trades. However, an average taken over a time interval is a noisy estimate of the price at any point of time during that interval due to the random fluctuations in the “true” price driven by information flow. I’ve done some numerical experiments, and either the sampling error/manipulation noise has to be pretty large, or the volatility of the “true” price must be pretty low for it to be desirable to move to a longer interval.

Other suggestions include encouraging diversity in benchmarks. The other FSB-the Financial Stability Board-recommends this. Darrel Duffie and Jeremy Stein lay out the case here (which is a lot easier read than the 750+ pages of the longer FSB report).

Color me skeptical. Duffie and Stein recognize that the market has a tendency to concentrate on a single benchmark. It is easier to get into and out of positions in a contract which is similar to what everyone else is trading. This leads to what Duffie and Stein call “the agglomeration effect,” which I would refer to as a “tipping” effect: the market tends to tip to a single benchmark. This is what happened in Libor. Diversity is therefore unlikely in equilibrium, and the benchmark that survives is likely to be susceptible to either manipulation, or the bricks without straw problem.

Of course not all potential benchmarks are equally susceptible. So it would be good if market participants coordinated on the best of the possible alternatives. As Duffie and Stein note, there is no guarantee that this will be the case. This brings to mind the as yet unresolved debate over standard setting generally, in which some argue that the market’s choice of VHS over the allegedly superior Betamax technology, or the dominance of QWERTY over the purportedly better Dvorak keyboard (or Word vs. Word Perfect) demonstrate that the selection of a standard by a market process routinely results in a suboptimal outcome, but where others (notably Stan Lebowitz and Stephen Margolis) argue that  these stories of market failure are fairy tales that do not comport with the actual histories. So the relevance of the “bad standard (benchmark) market failure” is very much an open question.

Darrel and Jeremy suggest that a wise government can make things better:

This is where national policy makers come in. By speaking publicly about the advantages of reform — or, if necessary, by using their power to regulate — they can guide markets in the desired direction. In financial benchmarks as in tap water, markets might not reach the best solution on their own.

Putting aside whether government regulators are indeed so wise in their judgments, there is  the issue of how “better” is measured. Put differently: governments may desire a different direction than market participants.

Take one of the suggestions that Duffie and Stein raise as an alternative to Libor: short term Treasuries. It is almost certainly true that there is more straw in the Treasury markets than in any other rates market. Thus, a Treasury bill-based benchmark is likely to be less susceptible to manipulation than any other market. (Though not immune altogether, as the Pimco episode in June ’05 10 Year T-notes, the squeezes in the long bond in the mid-to-late-80s, the Salomon 2 year squeeze in 92, and the chronic specialness in some Treasury issues prove.)

But that’s not of much help if the non-manipulated benchmark is not representative of the rates that market participants want to hedge. Indeed, when swap markets started in the mid-80s, many contracts used Treasury rates to set the floating leg. But the basis between Treasury rates, and the rates at which banks borrowed and lent, was fairly variable. So a Treasury-based swap contract had more basis risk than Libor-based contracts. This is precisely why the market moved to Libor, and when the tipping process was done, Libor was the dominant benchmark not just for derivatives but floating rate loans, mortgages, etc.

Thus, there may be a trade-off between basis risk and susceptibility to manipulation (or to noise arising from sampling error due to a small number of transactions or averaging over a wide time window). Manipulation can lead to basis risk, but it can be smaller than the basis risk arising from a quality mismatch (e.g., a credit risk mismatch between default risk-free Treasury rates and a defaultable rate that private borrowers pay). I would wager that regulators would prefer a standard that is less subject to manipulation, even if it has more basis risk, because they don’t internalize the costs associated with basis risk. Market participants may have a very different opinion. Therefore, the “desired direction” may depend very much on whom you ask.

Putting all this together, I conclude we live in a fallen world. There is no benchmark Eden. Benchmark problems are likely to be chronic for the foreseeable future. And beyond. Some improvements are definitely possible, but benchmarks will always be subject to abuse. Their very source of utility-that they are a visible price that can be used to determine payoffs on vast sums of other contracts-always provides a temptation to manipulate.

Moving to transactions-based mechanisms eliminates outright lying as a manipulation strategy, but it does not eliminate the the potential for market power abuses. The benchmarks that would be least vulnerable to market power abuses are not necessarily the ones that best reflect the exposures that market participants face.

Thus, we cannot depend on benchmark design alone to address manipulation problems. The means, motive, and opportunity to manipulate even transactions-based benchmarks will endure. This means that reducing the frequency of manipulation requires some sort of deterrence mechanism, either through government action (as in the Libor, Optiver, Moore, and Amaranth cases) or private litigation (examples of which include all the aforementioned cases, plus some more, like Brent).  It will not be possible to “solve” the benchmark problems by designing better mechanisms, then riding off into the sunset like the Lone Ranger. Our work here will never be done, Kimo Sabe.*

* Stream of consciousness/biographical detail of the day. The phrase “Kimo Sabe” was immortalized by Jay Silverheels-Tonto in the original Lone Ranger TV series. My GGGGF, Abel Sherman, was slain and scalped by an Indian warrior named Silverheels during the Indian War in Ohio in 1794. Silverheels made the mistake of bragging about his feat to a group of lumbermen, who just happened to include Abel’s son. Silverheels was found dead on a trail in the woods the next day, shot through the heart. Abel (a Revolutionary War vet) was reputedly the last white man slain by Indians in Washington County, OH. His tombstone is on display in the Campus Martius museum in Marietta. The carving on the headstone is very un-PC. It reads:

Here lyes the body of Abel Sherman who fell by the hand of the Savage on the 15th of August 1794, and in the 50th year of  his age.

Here’s a picture of it:

OLYMPUS DIGITAL CAMERA

The stream by which Abel was killed is still known as Dead Run, or Dead Man’s Run.

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July 21, 2014

Doing Due Diligence in the Dark

Filed under: Exchanges,HFT,Regulation — The Professor @ 8:39 pm

Scott Patterson, WSJ reporter and the author of Dark Pools, has a piece in today’s journal about the Barclays LX story. He finds, lo and behold, that several users of the pool had determined that they were getting poor executions:

Trading firms and employees raised concerns about high-speed traders at Barclays PLC’s dark pool months before the New York attorney general alleged in June that the firm lied to clients about the extent of predatory trading activity on the electronic trading venue, according to people familiar with the firms.

Some big trading outfits noticed their orders weren’t getting the best treatment on the dark pool, said people familiar with the trading. The firms began to grow concerned that the poor results resulted from high-frequency trading, the people said.

In response, at least two firms—RBC Capital Markets and T. Rowe Price Group Inc —boosted the minimum number of shares they would trade on the dark pool, letting them dodge high-speed traders, who often trade in small chunks of 100 or 200 shares, the people said.

This relates directly to a point that I made in my post on the Barclays story. Trading is an experience good. Dark pool customers can evaluate the quality of their executions. If a pool is not screening out opportunistic traders, execution costs will be high relative to other venues who do a better job of screening, and users who monitor their execution costs will detect this. Regardless of what a dark pool operator says about what it is doing, the proof of the pudding is in the trading, as it were.

The Patterson article shows that at least some buy side firms do the necessary analysis, and can detect a pool that does not exclude toxic flows.

This long FT piece relies extensively on quotes from Hisander Misra, one of the founders of Chi-X, to argue that many fund managers have been ignorant of the quality of executions they get on dark pools. The article talked to two anonymous fund managers who say they don’t know how dark pools work.

The stated implication here is that regulation is needed to protect the buy side from unscrupulous pool operators.

A couple of comments. First, not knowing how a pool works doesn’t really matter. Measures of execution quality are what matter, and these can be measured. I don’t know all of the technical details of the operation of my car or the computer I am using, but I can evaluate their performances, and that’s what matters.

Second, this is really a cost-benefit issue. Monitoring of performance is costly. But so is regulation and litigation. Given that market participants have the biggest stake in measuring pool performance properly, and can develop more sophisticated metrics, there are strong arguments in favor of relying on monitoring.  Regulators can, perhaps, see whether a dark pool does what it advertises it will do, but this is often irrelevant because it does not necessarily correspond closely to pool execution costs, which is what really matters.

Interestingly, one of the things that got a major dark pool (Liquidnet) in trouble was that it shared information about the identities of existing clients with prospective clients. This presents interesting issues. Sharing such information could economize on monitoring costs. If a a big firm (like a T. Rowe) trades in a pool, this can signal to other potential users that the pool does a good job of screening out the opportunistic. This allows them to free ride off the monitoring efforts of the big firm, which economizes on monitoring costs.

Another illustration of how things are never simple and straightforward when analyzing market structure.

One last point. Some of the commentary I’ve read recently uses the prevalence of HFT volume in a dark pool as a proxy for how much opportunistic trading goes on in the pool. This is a very dangerous shortcut, because as I (and others) have written repeatedly, there is all different kinds of HFT. Some adds to liquidity, some consumes it, and some may be outright toxic/predatory. Market-making HFT can enhance dark pool liquidity, which is probably why dark pools encourage HFT participation. Indeed, it is hard to understand how a pool could benefit from encouraging the participation of predatory HFT, especially if it lets such firms trade for free. This drives away the paying customers, particularly when the paying customers evaluate the quality of their executions.

Evaluating execution quality and cost could be considered a form of institutional trader due diligence. Firms that do so can protect themselves-and their investor-clients-from opportunistic counterparties. Even though the executions are done in the dark, it is possible to shine a light on the results. The WSJ piece shows that many firms do just that. The question of whether additional regulation is needed boils down to the question of whether the cost and efficacy of these self-help efforts is superior to that of regulation.

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July 15, 2014

Oil Futures Trading In Troubled Waters

Filed under: Commodities,Derivatives,Economics,Energy,Exchanges,HFT,Regulation — The Professor @ 7:16 pm

A recent working paper by Pradeep Yadav, Michel Robe and Vikas Raman tackles a very interesting issue: do electronic market makers (EMMs, typically HFT firms) supply liquidity differently than locals on the floor during its heyday? The paper has attracted a good deal of attention, including this article in Bloomberg.

The most important finding is that EMMs in crude oil futures do tend to reduce liquidity supply during high volatility/stressed periods, whereas crude futures floor locals did not. They explain this by invoking an argument I did 20 years ago in my research comparing the liquidity of floor-based LIFFE to the electronic DTB: the anonymity of electronic markets makes market makers there more vulnerable to adverse selection. From this, the authors conclude that an obligation to supply liquidity may be desirable.

These empirical conclusions seem supported by the data, although as I describe below the scant description of the methodology and some reservations based on my knowledge of the data make me somewhat circumspect in my evaluation.

But my biggest problem with the paper is that it seems to miss the forest for the trees. The really interesting question is whether electronic markets are more liquid than floor markets, and whether the relative liquidity in electronic and floor markets varies between stressed and non-stressed markets. The paper provides some intriguing results that speak to that question, but then the authors ignore it altogether.

Specifically, Table 1 has data on spreads in from the electronic NYMEX crude oil market in 2011, and from the floor NYMEX crude oil market in 2006. The mean and median spreads in the electronic market: .01 percent. Given a roughly $100 price, this corresponds to one tick ($.01) in the crude oil market. The mean and median spreads in the floor market: .35 percent and .25 percent, respectively.

Think about that for a minute. Conservatively, spreads were 25 times higher in the floor market. Even adjusting for the fact that prices in 2011 were almost double than in 2006, we’re talking a 12-fold difference in absolute (rather than percentage) spreads. That is just huge.

So even if EMMs are more likely to run away during stressed market conditions, the electronic market wins hands down in the liquidity race on average. Hell, it’s not even a race. Indeed, the difference is so large I have a hard time believing it, which raises questions about the data and methodologies.

This raises another issue with the paper. The paper compares at the liquidity supply mechanism in electronic and floor markets. Specifically, it examines the behavior of market makers in the two different types of markets. What we are really interested is the outcome of these mechanisms. Therefore, given the rich data set, the authors should compare measures of liquidity in stressed and non-stressed periods, and make comparisons between the electronic and floor markets. What’s more, they should examine a variety of different liquidity measures. There are multiple measures of spreads, some of which specifically measure adverse selection costs. It would be very illuminating to see those measures across trading mechanisms and market environments. Moreover, depth and price impact are also relevant. Let’s see those comparisons too.

It is quite possible that the ratio of liquidity measures in good and bad times is worse in electronic trading than on the floor, but in any given environment, the electronic market is more liquid. That’s what we really want to know about, but the paper is utterly silent on this. I find that puzzling and rather aggravating, actually.

Insofar as the policy recommendation is concerned, as I’ve been writing since at least 2010, the fact that market makers withdraw supply during periods of market stress does not necessarily imply that imposing obligations to make markets even during stressed periods is efficiency enhancing. Such obligations force market makers to incur losses when the constraints bind. Since entry into market making is relatively free, and the market is likely to be competitive (the paper states that there are 52 active EMMS in the sample), raising costs in some state of the world, and reducing returns to market making in these states, will lead to the exit of market making capacity. This will reduce liquidity during unstressed periods, and could even lead to less liquidity supply in stressed periods: fewer firms offering more liquidity than they would otherwise choose due to an obligation may supply less liquidity in aggregate than a larger number of firms that can each reduce liquidity supply during stressed periods (because they are not obligated to supply a minimum amount of liquidity).

In other words, there is no free lunch. Even assuming that EMMs are more likely to reduce supply during stressed periods than locals, it does not follow that a market making obligation is desirable in electronic environments. The putatively higher cost of supplying liquidity in an electronic environment is a feature of that environment. Requiring EMMs to bear that cost means that they have to recoup it at other times. Higher cost is higher cost, and the piper must be paid. The finding of the paper may be necessary to justify a market maker obligation, but it is clearly not sufficient.

There are some other issues that the authors really need to address. The descriptions of the methodologies in the paper are far too scanty. I don’t believe that I could replicate their analysis based on the description in the paper. As an example, they say “Bid-Ask Spreads are calculated as in the prior literature.” Well, there are many papers, and many ways of calculating spreads. Hell, there are multiple measures of spreads. A more detailed statement of the actual calculation is required in order to know exactly what was done, and to replicate it or to explore alternatives.

Comparisons between electronic and open outcry markets are challenging because the nature of the data are very different. We can observe the order book at every instant of time in an electronic market. We can also sequence everything-quotes, cancellations and trades-with exactitude. (In futures markets, anyways. Due to the lack of clock synchronization across trading venues, this is a problem in a fragmented market like US equities.) These factors mean that it is possible to see whether EMMs take liquidity or supply it: since we can observe the quote, we know that if an EMM sells (buys) at the offer (bid) it is supplying liquidity, but if it buys (sells) at the offer (bid) it is consuming liquidity.

Things are not nearly so neat in floor trading data. I have worked quite a bit with exchange Street Books. They convey much less information than the order book and the record of executed trades in electronic markets like Globex. Street Books do not report the prevailing bids and offers, so I don’t see how it is possible to determine definitively whether a local is supplying or consuming liquidity in a particular trade. The mere fact that a local (CTI1) is trading with a customer (CTI4) does not mean the local is supplying liquidity: he could be hitting the bid/lifting the offer of a customer limit order, but since we can’t see order type, we don’t know. Moreover, even to the extent that there are some bids and offers in the time and sales record, they tend to be incomplete (especially during fast markets) and time sequencing is highly problematic. I just don’t see how it is possible to do an apples-to-apples comparison of liquidity supply (and particularly the passivity/aggressiveness of market makers) between floor and electronic markets just due to the differences in data. Nonetheless, the paper purports to do that. Another reason to see more detailed descriptions of methodology and data.

One red flag that indicates that the floor data may have some problems. The reported maximum bid-ask spread in the floor sample is 26.48 percent!!! 26.48 percent? Really? The 75th percentile spread is .47 percent. Given a $60 price, that’s almost 30 ticks. Color me skeptical. Another reason why a much more detailed description of methodologies is essential.

Another technical issue is endogeneity. Liquidity affects volatility, but the paper uses volatility as one of its measures of stressed markets in its study of how stress affects liquidity. This creates an endogeneity (circularity, if you will) problem. It would be preferable to use some instrument for stressed market conditions. Instruments are always hard to come up with, and I don’t have one off the top of my head, but Yanev et al should give some serious thought to identifying/creating such an instrument.

Moreover, the main claim of the paper is that EMMs’ liquidity supply is more sensitive to the toxicity of order flow than locals’ liquidity supply. The authors use order imbalance (CTI4 buys minus CTI4 sells, or the absolute value thereof more precisely), which is one measure of toxicity, but there are others. I would prefer a measure of customer (CTI4) alpha. Toxic (i.e., informed) order flow predicts future price movements, and hence when customer orders realize high alphas, it is likely that customers are more informed than usual and earn positive alphas. It would therefore be interesting to see the sensitivities of liquidity supply in the different trading environments to order flow toxicity as measured by CTI4 alphas.

I will note yet again that market maker actions to cut liquidity supply when adverse selection problems are severe is not necessarily a bad thing. Informed trading can be a form of rent seeking, and if EMMs are better able to detect informed trading and withdraw liquidity when informed trading is rampant, this form of rent seeking may be mitigated. Thus, greater sensitivity to toxicity could be a feature, not a bug.

All that said, I consider this paper a laudable effort that asks serious questions, and attempts to answer them in a rigorous way. The results are interesting and plausible, but the sketchy descriptions of the methodologies gives me reservations about these results. But by far the biggest issue is that of the forest and trees. What is really interesting is whether electronic markets are more or less liquid in different market environments than floor markets. Even if liquidity supply is flightier in electronic markets, they can still outperform floor based markets in both unstressed and stressed environments. The huge disparity in spreads reported in the paper suggests a vast difference in liquidity on average, which suggests a vast difference in liquidity in all different market environments, stressed and unstressed. What we really care about is liquidity outcomes, as measured by spreads, depth, price impact, etc. This is the really interesting issue, but one that the paper does not explore.

But that’s the beauty of academic research, right? Milking the same data for multiple papers. So I suggest that Pradeep, Michel and Vikas keep sitting on that milking stool and keep squeezing that . . . data ;-) Or provide the data to the rest of us out their and let us give it a tug.

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July 11, 2014

25 Years Ago Today Ferruzzi Created the Streetwise Professor

Filed under: Clearing,Commodities,Derivatives,Economics,Exchanges,HFT,History,Regulation — The Professor @ 9:03 am

Today is the 25th anniversary of the most important event in my professional life. On 11 July, 1989, the Chicago Board of Trade issued an Emergency Order requiring all firms with positions in July 1989 soybean futures in excess of the speculative limit to reduce those positions to the limit over five business days in a pro rata fashion (i.e., 20 percent per day, or faster). Only one firm was impacted by the order, Italian conglomerate Ferruzzi, SA.

Ferruzzi was in the midst of an attempt to corner the market, as it had done in May, 1989. The EO resulted in a sharp drop in soybean futures prices and a jump in the basis: for instance, by the time the contract went off the board on 20 July, the basis at NOLA had gone from zero to about 50 cents, by far the largest jump in that relationship in the historical record.

The EO set off a flurry of legal action. Ferruzzi tried to obtain an injunction against the CBT. Subsequently, farmers (some of whom had dumped truckloads of beans at the door of the CBT) sued the exchange. Moreover, a class action against Ferruzzi was also filed. These cases took years to wend their ways through the legal system. The farmer litigation (in the form of Sanner v. CBT) wasn’t decided (in favor of the CBT) until the fall of 2002. The case against Ferruzzi lasted somewhat less time, but still didn’t settle until 2006.

I was involved as an expert in both cases. Why?

Well, pretty much everything in my professional career post-1990 is connected to the Ferruzzi corner and CBT EO, in a knee-bone-connected-to-the-thigh-bone kind of way.

The CBT took a lot of heat for the EO. My senior colleague, the late Roger Kormendi, convinced the exchange to fund an independent analysis of its grain and oilseed markets to attempt to identify changes that could prevent a recurrence of the episode. Roger came into my office at Michigan, and told me about the funding. Knowing that I had worked in the futures markets before, asked me to participate in the study. I said that I had only worked in financial futures, but I could learn about commodities, so I signed on: it sounded interesting, my current research was at something of a standstill, and I am always up for learning something new. I ended up doing about 90 percent of the work and getting 20 percent of the money :-P but it was well worth it, because of the dividends it paid in the subsequent quarter century. (Putting it that way makes me feel old. But this all happened when I was a small child. Really!)

The report I (mainly) wrote for the CBT turned into a book, Grain Futures Contracts: An Economic Appraisal. (Available on Amazon! Cheap! Buy two! I see exactly $0.00 of your generous purchases.) Moreover, I saw the connection between manipulation and industrial organization economics (which was my specialization in grad school): market power is a key concept in both. So I wrote several papers on market power manipulation, which turned into a book . (Also available on Amazon! And on Kindle: for some strange reason, it was one of the first books published on Kindle.)

The issue of manipulation led me to try to understand how it could best be prevented or deterred. This led me to research self-regulation, because self-regulation was often advanced as the best way to tackle manipulation. This research (and the anthropological field work I did working on the CBT study) made me aware that exchange governance played a crucial role, and that exchange  governance was intimately related to the fact that exchanges are non-profit firms. So of course I had to understand why exchanges were non-profits (which seemed weird given that those who trade on them are about as profit-driven as you can get), and why they were governed in the byzantine, committee-dominated way they were. Moreover, many advocates of self-regulation argued that competition forced exchanges to adopt efficient rules. Observing that exchanges in fact tended to be monopolies, I decided I needed to understand the economics of competition between execution venues in exchange markets. This caused me to write my papers on market macrostructure, which is still an active area of investigation: I am writing a book on that subject. This in turn produced many of the conclusions that I have drawn about HFT, RegNMS, etc.

Moreover, given that I concluded that self-regulation was in fact a poor way to address manipulation (because I found exchanges had poor incentives to do so), I examined whether government regulation or private legal action could do better. This resulted in my work on the efficiency of ex post deterrence of manipulation. My conclusions about the efficiency of ex post deterrence rested on my findings that manipulated prices could be distinguished reliably from competitive prices. This required me to understand the determinants of competitive prices, which led to my research on the dynamics of storable commodity prices that culminated in my 2011 book. (Now available in paperback on Amazon! Kindle too.)

In other words, pretty much everything in my CV traces back to Ferruzzi. Even the clearing-related research, which also has roots in the 1987 Crash, is due to Ferruzzi: I wouldn’t have been researching any derivatives-related topics otherwise.

My consulting work, and in particular my expert witness work, stems from Ferruzzi. The lead counsel in the class action against Ferruzzi came across Grain Futures Contracts in the CBT bookstore (yes, they had such a thing back in the day), and thought that I could help him as an expert. After some hesitation (attorneys being very risk averse, and hence reluctant to hire someone without testimonial experience) he hired me. The testimony went well, and that was the launching pad for my expert work.

I also did work helping to redesign the corn and soybean contracts at the CBT, and the canola contract in Winnipeg: these redesigned contracts (based on shipping receipts) are the ones traded today. Again, this work traces its lineage to Ferruzzi.

Hell, this was even my introduction to the conspiratorial craziness that often swirls around commodity markets. Check out this wild piece, which links Ferruzzi (“the Pope’s soybean company”) to Marc Rich, the Bushes, Hillary Clinton, Vince Foster, and several federal judges. You cannot make up this stuff. Well, you can, I guess, as a quick read will soon convince you.

I have other, even stranger connections to Hillary and Vince Foster which in a more indirect way also traces its way back to Ferruzzi. But that’s a story for another day.

There’s even a Russian connection. One of Ferruzzi’s BS cover stories for amassing a huge position was that it needed the beans to supply big export sales to the USSR. These sales were in fact fictitious.

Ferruzzi was a rather outlandish company that eventually collapsed in 1994. Like many Italian companies, it was leveraged out the wazoo. Moreover, it had become enmeshed in the Italian corruption/mob investigations of the early 1990s, and its chairman Raul Gardini, committed suicide in the midst of the scandal.

The traders who carried out the corners were located in stylish Paris, but they were real commodity cowboys of the old school. Learning about that was educational too.

To put things in a nutshell. Some crazy Italians, and English and American traders who worked for them, get the credit-or the blame-for creating the Streetwise Professor. Without them, God only knows what the hell I would have done for the last 25 years. But because of them, I raced down the rabbit hole of commodity markets. And man, have I seen some strange and interesting things on that trip. Hopefully I will see some more, and if I do, I’ll share them with you right here.

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July 8, 2014

The Securities Market Structure Regulation Book Club

Filed under: Derivatives,Economics,Exchanges,Politics,Regulation — The Professor @ 4:30 pm

There was another hearing on HFT on Capitol Hill today, in the Senate. The best way to summarize it was that it reminded me of an evening at the local bookstore, with authors reading selections from their books.

Two examples suffice. Citadel’s Ken Griffin (whom I called out for talking his book on Frankendodd years ago) heavily criticized dark pools, and called for much heavier regulation of them. But he sang the praises of purchased order flow, and warned against any regulation of it.

So, go out on a limb and bet that (a) Citadel does not operate a dark pool, and (b) Citadel is one of the biggest purchasers of order flow, and you’ll be a winner!

The intellectually respectable case against dark pools and payment for order flow is the same. Both “cream skim” uninformed orders from the exchanges, leaving the exchange order flow more informed (i.e., more toxic), thereby reducing exchange liquidity by increasing adverse selection costs. I’m not saying that I agree with this case, but I do recognize that it is at least grounded in economics, and that an intellectually consistent critic of dark pools would also criticize purchased order flow.

But some people have books to sell.

The other example is Jeffrey Sprecher of ICE, which owns and operates the NYSE. Sprecher lamented the fragmentation of the equity markets, and praised the lack of fragmentation of futures markets. But he went further. He said that futures markets were competitive and not fragmented.

Tell me another one.

Yes, there is limited head-to-head competition in some futures contracts, such as WTI and Brent. But these are the exceptions, not the rule. Futures exchanges do not compete head to head in any other major contract. Execution in the equity market is far more competitive than in the futures market. Multiple equities exchanges compete vigorously, and the socialization of order flow due to RegNMS makes that competition possible. This is why the equities exchange business is low margin, and not very profitable. Futures exchanges own their order flow, and since liquidity attracts liquidity, one exchange tends to dominate trading in a particular instrument. So yes, futures markets are not fragmented, but no, they are not competitive. These things go together, regardless of what Sprecher says.  He wants to go back to the day when the NYSE was the dominant exchange and its members earned huge rents. That requires undoing a lot of what is in RegNMS.

Those were some of the gems from the witness side of the table. From the questioner side, we were treated to another display of Elizabeth Warren’s arrogant ignorance and idiocy. The scary thought is that the left views her as the next Obama who will deny Hillary and vault to the presidency. God save us.

Overall the hearing demonstrated what I’ve been saying for years. Market structure, and the regulations that drive market structure, have huge distributive effects. Everybody says that they are in favor of efficient markets, but I’m sure you’ll be shocked to learn that their definition of what is efficient happens to correspond with what benefits their firms. The nature of securities/derivatives trading creates rents. The battle over market structure is a classic rent seeking struggle. In rent seeking struggles, everybody reads out of their books. Everybody.

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July 1, 2014

What Gary Gensler, the Igor of Frankendodd, Hath Wrought

I’ve spent quite a bit of time in Europe lately, and this gives a rather interesting perspective on US derivatives regulatory policy. (I’m in London now for Camp Alphaville.)

Specifically, on the efforts of Frankdodd’s Igor, Gary Gensler, to make US regulation extraterritorial (read: imperialist).

Things came to a head when the head of the CFTC’s Clearing and Risk  division, Ananda K. Radhakrishnan, said that ICE and LCH, both of which clear US-traded futures contracts out of the UK, could avoid cross-border issues arising from inconsistencies between EU and US regulation (relating mainly to collateral segregation rules) by moving to the US:

Striking a marked contrast with European regulators calling for a collaborative cross-border approach to regulation, a senior CFTC official said he was “tired” of providing exemptions, referring in particular to discrepancies between the US Dodd-Frank framework and the European Market Infrastructure Regulation on clearing futures and the protection of related client collateral.

“To me, the first response cannot be: ‘CFTC, you’ve got to provide an exemption’,” said Ananda Radhakrishnan, the director of the clearing and risk division at the CFTC.

Radhakrishnan singled out LCH.Clearnet and the InterContinental Exchange as two firms affected by the inconsistent regulatory frameworks on listed derivatives as a result of clearing US business through European-based derivatives clearing organisations (DCOs).

“ICE and LCH have a choice. They both have clearing organisations in the United States. If they move the clearing of these futures contracts… back to a US only DCO I believe this conflict doesn’t exist,” said Radhakrishnan.

“These two entities can engage in some self-help. If they do that, neither [regulator] will have to provide an exemption.”

It was not just what he said, but how he said it. The “I’m tired” rhetoric, and his general mien, was quite grating to Europeans.

The issue is whether the US will accept EU clearing rules as equivalent, and whether the EU will reciprocate. Things are pressing, because there is a December deadline for the EU to recognize US CCPs as equivalent. If this doesn’t happen, European banks that use a US CCP (e.g., Barclays holding a Eurodollar futures position cleared through the CME) will face a substantially increased capital charge on the cleared positions.

Right now there is a huge game of chicken going on between the EU and the US. In response to what Europe views as US obduracy, the Europeans approved five Asian/Australasian CCPs as operating under rules equivalent to Europe’s, allowing European banks to clear though them without incurring the punitive capital charges. To emphasize the point, the EU’s head of financial services, Michael Barnier, said the US could get the same treatment if it deferred to EU rules (something which Radhakrishnan basically said he was tired of talking about):

“If the CFTC also gives effective equivalence to third country CCPs, deferring to strong and rigorous rules in jurisdictions such as the EU, we will be able to adopt equivalence decisions very soon,” Barnier said.

Read this as a giant one finger salute from the EU to the CFTC.

So we have a Mexican standoff, and the clock is ticking. If the EU and the US don’t resolve matters, the world derivatives markets will become even more fragmented. This will make them less competitive, which is cruelly ironic given that one of Gensler’s claims was that his regulatory agenda would make the markets more competitive. This was predictably wrong-and some predicted this unintended perverse outcome.

Another part of Gensler’s agenda was to extend US regulatory reach to entities operating overseas whose failure could threaten US financial institutions. One of his major criteria for identifying such entities was whether they are guaranteed by a US institution. Those who are so guaranteed are considered “US persons,” and hence subject to the entire panoply of Frankendodd requirements, including notably the SEF mandate. The SEF mandate is loathed by European corporates, so this would further fragment the swaps market. (And as I have said often before, since end users are the alleged beneficiaries of the SEF mandate-Gary oft’ told us so!-it is passing strange that they are hell-bent on escaping it.)

European US bank affiliates with guarantees from US parents have responded by terminating the guarantees. Problem solved, right? The dreaded guarantees that could spread contagion from Europe to the US are gone, after all.

But US regulators and legislators view this as a means of evading Frankendodd. Which illustrates the insanity of it all. The SEF mandate has nothing to do with systemic risk or contagion. Since the ostensible purpose of the DFA was to reduce systemic risk, it was totally unnecessary to include the SEF mandate. But in its wisdom, the US Congress did, and Igor pursued this mandate with relish.

The attempts to dictate the mode of trade execution even by entities that cannot directly spread contagion to the US via guarantees epitomizes the overreach of the US. Any coherent systemic risk rationale is totally absent. The mode of execution is of no systemic importance. The elimination of guarantees eliminates the ability of failing foreign affiliates to impact directly US financial institutions. If anything, the US should be happy, because some of the dread interconnections that Igor Gensler inveighed against have been severed.

But the only logic that matters her is that of control. And the US and the Europeans are fighting over control. The ultimate outcome will be a more fragmented, less competitive, and likely less robust financial system.

This is just one of the things that Gensler hath wrought. I could go on. And in the future I will.

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June 25, 2014

The 40th Anniversary of Jaws, Barclays Edition: Did the LX Dark Pool Keep Out the Sharks or Invite Them In?

Filed under: Economics,Exchanges,HFT,Politics,Regulation — The Professor @ 8:33 pm

Today’s big news is the suit filed by NY Attorney General Eric Schneiderman alleging that Barclays defrauded the customers of its LX dark pool.

In the current hothouse environment of US equity market structure, this will inevitably unleash a torrent of criticism of dark pools. When evaluating the ensuing rhetoric, it is important to distinguish between criticism of dark pools generally, and this one dark pool in particular. That is, there are two distinct questions that are likely to be all tangled up. Are dark pools bad? Or, are dark pools good (or at least not bad), but did Barclays  not do what dark pools are supposed to do while claiming that it did?

What dark pools are supposed to do is protect traders (mainly institutional traders who can be considered uninformed) from predatory traders. Predatory traders can be those with better information, or those with a speed advantage (which often confers an information advantage, through arbitrage or order anticipation). Whether dark pools in general are good or bad depends on the effects of the segmentation of the market. By “cream skimming” the (relatively) uninformed order flow, dark pools make the exchanges less liquid. Order flow on the exchanges tends to be more “toxic” (i.e., informed), and these information asymmetries widen spreads and reduce depth, which raises trading costs for the uninformed traders who cannot avail themselves of the dark pool and who trade on the lit market instead. This means that the trading costs of some uninformed traders (those who can use the dark pools) goes down and the trading costs of some uninformed traders (those who can’t use dark pools) goes up. The distributive effect is one thing that makes dark pools controversial: the losers don’t like them. The net effect is impossible to determine in general, and depends on the competitiveness of the exchange market among other things: even if dark pools reduce liquidity on the exchange, they can provide a source of competition that generates benefits if the exchange markets are imperfectly competitive.

What’s more, dark pools reduce the returns to informed trading.  The efficiency effects of this are also ambiguous, because some informed trading enhances efficiency (by improving the informativeness of prices, and thereby leading to better investment decisions), but other informed trading is rent seeking.

In other words, it’s complicated. There is no “yes” or “no” answer to the first question. This is precisely why market structure debates are so intense and enduring.

The second question is what is at issue in the Barclays case. The NYAG alleges that Barclays promised to protect its customers from predatory HFT sharks, but failed to do so. Indeed, according to the complaint, Barclays actively tried to attract sharks to its pool. (This is one of the problematic aspects of the complaint, as I will show). So, the complaint really doesn’t take a view on whether dark pools that indeed protect customers from sharks are good or bad. It just claims that if dark pools claim to provide shark repellent, but don’t, they have defrauded their customers.

Barclays clearly did make bold claims that it was making strenuous efforts to protect its customers from predatory traders, including predatory HFT. This FAQ sets out its various anti-gaming procedures. In particular, LX performed “Liquidity Profiling” that evaluated the users of the dark pool on various dimensions. One dimension was aggressiveness: did they make quotes or execute against them? Another dimension was profitability. Traders that earn consistent profits over one second intervals are more likely to be informed, and costly for others without information to trade with. Based on this information, Barclays ranked traders on a 0 to 5 scale, with 0 being profitable, aggressive, predatory sharks, and 5 representing passive, gentle blue whales.

Furthermore, Barclays claimed that it allowed its customers to limit their trading to counterparties with certain liquidity profiles, and to certain types of counterparties. For instance, a user could choose not to be matched with a trader with an aggressive profile. Similarly, a customer could choose not to trade against an electronic liquidity provider. In addition, Barclays said that it would exclude traders who consistently brought toxic order flow to the market. That is, Barclays claimed that it was constantly on alert for sharks, and kept the sharks away from the minnows and dolphins and gentle whales.

The NYAG alleges this was a tissue of lies. There are several allegations.

The first is that in its marketing materials, Barclays misrepresented the composition of the order flow in the pool. Specifically,  a graph that  depicted Barclays’ “Liquidity Landscape” purported to show that very little of the trading in the pool was aggressive/predatory. The NYAG alleges that this chart is “false” because it did not include “one of the largest and most toxic participants  [Tradebot] in Barclays’ dark pool.” Further, the NYAG alleges that Barclays deceptively under-reported the amount of predatory HFT trading activity in the pool.

The second basic allegation is that Barclays did not exclude the sharks, and that by failing to update trader profiles, the ability to avoid trading with a firm with a 0 or 1 liquidity profile ranking was useless. Some firms that should have been labeled 0′s were labeled 4′s or 5′s, leaving those that tried to limit their counterparties to the 4′s or 5′s vulnerable to being preyed on by the 0′s. Further, the AG alleges that Barclays promised to exclude the 0′s, but didn’t.

(The complaint also makes allegations about Barclays order routing procedures for its customers, but that’s something of a separate issue, so I won’t discuss that here).

Fraud and misrepresentation are objectionable, and should be punished for purposes of deterrence. They are objectionable because they result in the production of goods and services that are worth less than the cost of producing them. Thus, if Barclays did engage in fraud and misrepresentation, punishment is in order.

One should always be cautious about making judgments on guilt based on a complaint, which by definition is a one-sided representation of the facts. This is particularly true where the complaint relies on selective quotes from emails, and the statements of ex-employees. This is why we have an adversarial process to determine guilt, to permit a thorough vetting of the evidence presented by the plaintiff, and to allow the defendant to present exculpatory evidence (including contextualizing the emails, presenting material that contradicts what is in the proffered emails, and evidence about the motives and reliability of the ex-employees).

Given all this, based on the complaint there is a colorable case, but not a slam dunk.

There is also the question of whether the alleged misrepresentations had a material impact on investors’ decisions regarding whether to trade on LX or not: any fraud would have led to a social harm only to the extent too many investors used LX, or traded too much on it. Here there is reason to doubt whether the misrepresentations mattered all that much.

Trading is an “experience good.” That is, one gets information about the quality of the good by consuming it. Someone may be induced to consume a shoddy good once by deceptive marketing, but if consuming it reveals that it is shoddy, the customer won’t be back. If the product is viable only if it gets repeat customers, deception and fraud are typically unviable strategies. You might convince me to try manure on a cone by telling me it’s ice cream, but once I’ve tried it, I won’t buy it again. If your business profits only if it gets repeat customers, this strategy won’t succeed.

Execution services provided by a dark pool are an experience good that relies on repeat purchases. The dark pool provides an experience good because it is intended to reduce execution costs, and market participants can evaluate/quantify these costs, either by themselves, or by employing consultants that specialize in estimating these costs. Moreover, most traders who trade on dark pools don’t trade on a single pool. They trade on several (and on lit venues too) and can compare execution costs on various venues. If Barclays had indeed failed to protect its customers against the sharks, those customers would have figured that out when they evaluated their executions on LX and found out that their execution costs were high compared to their expectations, and to other venues.  Moreover, dark pool customers trade day after day after day. A dark pool generates succeeds by reducing execution costs, and if it doesn’t it won’t generate persistently large and growing volumes.

Barclays LX generated large and growing volumes. It became the second largest dark pool. I am skeptical that it could have done so had it really been a sham that promised superior execution by protecting customers from sharks when in fact it was doing nothing to keep them out. This suggests that the material effect of the fraud might have been small even had it occurred. This is germane for determining the damages arising from the fraud.

It should also be noted that the complaint alleges that not only did Barclays not do what it promised to keep sharks out, it actively recruited sharks. This theory is highly problematic. According to the complaint, Barclays attracted predatory HFT firms by allowing them to trade essentially for free.

But how does that work, exactly? Yes, the HFT firms generate a lot of volume, but a price of zero times a volume of a zillion generates revenues of zero. You don’t make any money that way. What’s more, the presence of these sharks would have raised the trading costs of the fee-paying minnows, dolphins, and whales, who would have had every incentive to find safer waters, thereby depriving Barclays of any revenues from them. Thus, I am highly skeptical that the AG’s story regarding Barclays’ strategy makes any economic sense. It requires that the non-HFT paying customers must have been enormously stupid, and unaware that they were being served up as bait. Indeed, that they were so stupid that they paid for the privilege of being bait.

It would make sense for Barclays to offer inducements to HFT firms that supply liquidity, because that would reduce the trading costs of the other customers, attracting their volume and making them willing to pay higher fees to trade in the pool.

All we have to go on now is the complaint, and some basic economics. Based on this information, my initial conclusion is that it is plausible that Barclays did misrepresent/overstate the advantages of LX, but that this resulted in modest harm to investors, and that even if the customers of LX got less than they had expected, they did better than they would have trading on another venue.

But this is just an initial impression. The adversarial process generates information that (hopefully) allows more discriminating and precise judgments. I would focus on three types of evidence. First, a forensic evaluation of the LX trading system: did the Liquidity Profile mechanism really allow users to limit their exposure to toxic/predatory order flow? Second, an appraisal of the operation of the system: did it accurately categorize traders, or did Barclays, as alleged in the complaint, systematically mis-categorize predatory traders as benign, thereby exposing traders who wanted to avoid the sharks to their tender mercies? Third, a quantification of the performance of the system in delivering lower execution costs. If LX was indeed doing what a dark pool should do, users should have paid lower execution costs than they would have on other venues. If LX was in fact a massive fraud that attracted customers with promises of protection from predatory traders, but then set the sharks on them, these customers would have in fact incurred higher execution costs than they could have obtained on other venues. At root, the AG alleges that LX promised to lower execution costs, but failed to do so because it did not protect customers from predatory traders: the proof of that pudding is in the eating.

The adversarial judicial process makes it likely that such evidence will be produced, and evaluated by the trier of fact. The process is costly, and often messy, but given the stakes I am sure that these analyses will be performed and that justice will be done, if perhaps roughly.

My bigger concern is  in the adversarial political process. Particularly in the aftermath of Flash Boys, all equity market structure market issues are extremely contentious. Dark pools are a particularly fraught issue. The exchanges (NYSE/ICE and NASDAQ) resent the loss of order flow to dark pools, and want to kneecap them. Many in Congress are sympathetic to their pleas. As I noted at the outset, although the efficiency effects of dark pools are uncertain, their distributive effects are not: dark pools create winners (those who can trade on them, mainly) and losers (those who can’t trade on them, and rent seeking informed traders who lose the opportunity to exploit those who trade on dark pools). Distributive issues are inherently political, and given the sums at stake these political battles are well-funded.

There is thus the potential that the specifics of the Barclays case are interpreted to tar dark pools generally, resulting in a legislative and regulatory over-reaction that kills the good dark pools as well as the bad ones. The facts that AGs are by nature grand-standers generally, and that Schneiderman in particular is a crusader on the make, make such an outcome even more likely.

Given this, I will endeavor to provide an economics-based, balanced analysis of developments going forward. As I have written so often, equity market issues are seldom black and white. Given the nature of equity trading, specifically the central role played by information in it, it is hard to analyze the efficiency effects of various structures and policies. We are in a second best world, and comparisons are complex and messy in that world. In such a world, it is quite possible that both Barclays and the AG are wrong. We’ll see, and I’ll call it as I see it.

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June 18, 2014

The For-Profit Exchange Red Herring Are Running Again

Filed under: Derivatives,Economics,Exchanges,History,Politics,Regulation — The Professor @ 7:28 pm

One of the reddest of herrings is that the movement to for-profit exchanges is the source of our current woes in securities and derivatives markets. The herring were running today in DC, at a hearing on HFT held by  the Permanent Subcommittee on Investigations. One of the witnesses, Andrew Brooks of T. Rowe Price testified thus:

We question whether the functional roles of an exchange and a broker-dealer have become blurred over the years creating inherent conflicts of interest that may warrant regulatory action. It seems clear that since the exchanges have migrated to “for-profit” models, a conflict has arisen between the pursuit of volume (and the resulting revenue) and the obligation to assure an orderly marketplace for all investors. The fact that 11 exchanges and over 50 dark pools operate on a given day seems to create a model that is susceptible to manipulative behaviors. If a market participant’s sole function is to interposition themselves between buyers and sellers we question the value of such a role and believe that it puts an unneeded strain on the system. It begs the question as to whether investors were better served when exchanges functioned more akin to a public utility. Should exchanges with de minimus market share enjoy the regulatory protection that is offered by their status as exchanges, or should they be ignored?

This is tripe from beginning to end. The idea that exchanges ever “functioned as public utilities” is a joke. Non-profit, mutual exchanges were clubs that operated in the interest of the brokers and market makers that owned them. Period. The public be damned.

Not-for-profit is not a synonym for public-spirited. As I showed over 15 years ago, exchanges adopted the non-profit form as a way of reducing rent seeking battles between heterogeneous members. It had nothing to do with serving the public interest.

Jeff Carter has a great blog post about how not-for-profit exchanges really operated. He gives some very good examples of something I emphasized in my 2000 JLE piece: the primacy of committee governance as a way of refereeing rent-seeking squabbles between very, very profit oriented members:

Exchanges prior to demutualization were run by members.  As a board member, I chaired, co-chaired or served on several committees.  I was lobbied constantly by members.  I cannot remember the exact number, but I think we had some 200 committees, sub-committees and ad hoc committees.  We had 40 board members.  It was almost impossible to get anything meaningful done.

Here is an example.  We had a rule that if a contract reached an average daily volume of 10,000 or more, in financial futures it could no longer be dual traded.  The Nasdaq pit was taking off and somewhere in 1999, it went over 10k ADV.  Locals wanted dual trading to end.  Brokers didn’t want it to end.  As a board (and local), I thought we should end it because that was the hard and fast rule.

Nasdaq brokers threatened to quit if we banned dual trading.  The board agreed not to ban it.  That doesn’t happen in a for profit environment.

Another example.  We needed to adjust a pit configuration.  It is tough to put in a blogpost the level of argument that ensued, the amount of committee time and lobbying that took place, and the number of committees that had to check off a relatively minor adjustment.  But, that’s the way things worked because real estate was extremely valuable.  One foot higher, lower to the right or left could mean the difference between survival and life.

And if you think that there were no conflicts of interest in traditional not-for-profit exchanges, I have several bridges to sell you. And I’ll throw in some Arizona coastline, just to show what a swell guy I am.

With respect to self-regulation, my work from over 20 years ago demonstrated that traditional exchanges had little incentive to adopt and enforce rules that reduced certain forms of inefficient conduct (such as manipulation) because (a) they didn’t internalize the benefits of doing so, and (b) these rules could be exploited to redistribute rents among members, and a primary purpose of exchange organization and governance is to mitigate such distributive conflicts.

Unpublished work, which I might dust off, compared and contrasted the incentives of for-profit and not-for-profit exchanges to self-regulate efficiently. I showed that FP exchanges actually have superior incentives to prevent and deter some forms of inefficient conduct.

But the main point to keep in mind is that there was never, ever, ever, any Golden Age of public spirited exchanges acting in the public interest. Indeed, the entire reason that laws such as the Securities and Exchange Act, and the Commodity Exchange Act, were passed was that exchanges were widely-and correctly-perceived as being extremely flawed guardians of the public interest.

I say again. Not-for-profit exchanges shouldn’t be confused with charities, like the United Way. The non-profit form, and the committee-driven governance that Jeff describes, had one objective, and one objective only: to benefit (greedy) exchange members. Technological changes, specifically the move to electronic trading, eliminated the need for ownership and governance structures that protected specialized intermediaries like locals and floor brokers. Once that happened, exchanges demutualized. End of story.

There are serious issues about the incentives of exchanges, be they for-profit or non-profit, to adopt and enforce efficient rules. That’s where the focus should be. Superficial invocations of some non-existent Golden Age do not advance the debate. They put it in reverse. So let’s give that a rest and focus on the real issues, shall we?

 

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The Klearing Kool Aid Hangover

Back in Houston after a long trip to Turkey, France, Switzerland, and the Netherlands speaking about various commodity and clearing related issues, plus some R&R. Last stop on the tour was Chicago, where the Chicago Fed put on a great event on Law and Finance. Clearing was at the center of the discussion. Trying to be objective as possible, I think I can say that my critiques of clearing have had an influence on how scholars and practitioners (both groups being well-represented in Chicago) view clearing, and clearing mandates in particular. There is a deep  skepticism, and a growing awareness that CCPs are not the systemic risk safeguard that most had believed in the period surrounding the adoption of Frankendodd. Ruben Lee’s lunch talk summarized the skeptical view well, and recognized my role in making the skeptic’s case. His remarks were echoed by others at the workshop. If only this had penetrated the skulls of legislators and regulators when it could have made a major difference.

And the hits keep on coming. Since about April 2010 in particular, the focus of my criticism of clearing mandates has been on the destabilizing effects of rigid marking-to-market and variation margin by CCPs. I emphasized this in several SWP posts, and also my forthcoming article (in the Journal of Financial Market Infrastructure, a Risk publication) titled “A Bill of Goods.” So it was gratifying to read today that two scholars at the LSE, Ron Anderson and Karin Joeveer, used my analysis as the springboard for a more formal analysis of the issue.

The Anderson-Joeveer paper investigates collateral generally. It concludes that the liquidity implications of increased need for initial margin resulting from clearing mandates are not as concerning as the liquidity implications of greater variation margin flows that will result from a dramatic expansion of clearing.

Some of their conclusions are worth quoting in detail:

In addition, our analysis shows that moving toward central clearing with product specialized CCPs can greatly increase the numbers of margin movements which will place greater demands on a participant’s operational capacity and liquidity. This can be interpreted as tipping the balance of benefits and costs in favor of retaining bilateral OTC markets for a wider range of products and participants. Alternatively, assuming a full commitment to centralized clearing, it points out the importance of achieving consolidation and effective integration across infrastructures for a wider range of financial products. [Emphasis added.]

Furthermore:

A system relying principally on centralized clearing to mitigate counter-party risks creates increased demand for liquidity to service frequent margin calls. This can be met by opening up larger liquidity facilities, but indirectly this requires more collateral. To economize on the use of collateral, agents will try to limit liquidity usage, but this implies increased frequency of margin calls. This increases operational risks faced by CCPs which, given the concentration of risk in CCPs, raises the possibility that an idiosyncratic event could spill over into a system-wide event.

We have emphasized that collateral is only one of the tools used to control and manage credit risk. The notion that greater reliance on collateral will eliminate credit risk is illusory. Changing patterns in the use of collateral may not eliminate risk, but it will have implications for who will bear risks and on the costs of shifting risks. [Emphasis added.]

The G-20 stampede to impose clearing focused obsessively on counterparty credit risk, and ignored liquidity issues altogether. The effects of clearing on counterparty risk are vastly overstated (because the risk is mainly shifted, rather than reduced) and the liquidity effects have first-order systemic implications. Moving to a system which could increase margin flows by a factor of 10 (as estimated by Anderson-Joeveer), and which does so by increasing the tightness of the coupling of the system, is extremely worrisome. There will be large increases in the demand for liquidity in stressed market conditions that cause liquidity to dry up. Failures to get this liquidity in a timely fashion can cause the entire tightly-coupled system to break down.

As Ruben pointed out in his talk, the clearing stampede was based on superficial analysis and intended to achieve a political objective, namely, the desire to be seen as doing something. Pretty much everyone in DC and Brussels drank the Klearing Kool Aid, and now we are suffering the consequences.

Samuel Johnson said “Marry in haste, repent at leisure.” The same thing can be said of legislation and regulation.

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April 23, 2014

File Under “Dog Bites Man”: Exchange Monopolies and Dark Pools

Filed under: Commodities,Derivatives,Economics,Exchanges,Politics,Regulation — The Professor @ 2:13 pm

An exchange chairman believes that all trading should take place on exchanges. In commenting on securities market structure, CME Group Chairman Terry Duffy criticizes fragmentation-especially the existence of dark pools-and touts the lack of fragmentation in futures trading.

The concentration of trading activity on futures exchanges, as opposed to the fragmentation across different exchanges (as well as off-exchange venues) in equities is due to a major difference in the treatment of orders. In futures markets, exchanges own their order flow: hypothetically, if there was another exchange posting a better price in a particular product, CME would not be obligated to direct an order to that better-priced market. When exchanges own their order flow in this way, traders direct orders to the exchange where they expect to get the best price. This is typically the market where most traders are. This creates a centripetal force that causes all activity to tip to a single dominant exchange. That is why CME, Eurex, ICE, etc., have monopolies or near monopolies in the products they trade. (And yes, Terry, even though no one is stopping anyone from competing with you, this order flow effect means that no one can do so effectively, leaving you a de facto monopoly. Only LIFFE’s idiocy in its battle with Eurex in 1998 allowed the Germans to get trading in the Bund futures to tip their way.)

This is the way it used to be in equities too. Prior to the late-2000s, the NYSE effectively owned its order flow, and 80-85 percent of trading volume in NYSE listings took place on the NYSE. The remainder occurred on “third markets” that catered to the verifiably uninformed (more on this below).  But in 2005 the SEC changed the rules in a fundamental way. It passed RegNMS, which socialized order flow by requiring exchanges to route orders to others displaying better prices. Within a very short period, a handful of exchanges executing between 8-20 percent of volume competed fiercely with one another. The NYSE’s effective monopoly had been broken.  This is why Goldman paid $6.5 billion for a specialist unit in 2000, and sold it for $30 million this year. The 2000 price capitalized monopoly rents: there are none to capitalize in 2014.

Duffy says he’s fine with this kind of fragmentation  of trading across exchanges with the associated intense competition (though that’s very easy for him to say because he doesn’t have to worry about that outcome given the lack of a RegNMS-type rule in futures markets), but he thinks dark pools should be shut down.

To evaluate this position, you need to understand what role dark pools play. Just like third markets and block markets of the pre-RegNMS era, dark pools (and internalization of retail order flow) are a ways of screening out informed traders. This reduces the costs of the uninformed who can trade on dark pools be reducing their vulnerability to adverse selection. This is good for them, but the overall effects are much harder to understand. Order flow on exchanges becomes more toxic (i.e., a higher proportion of the order flow is informed) which raises adverse selection costs on exchanges, and thereby raises trading costs there.

The net effect of this is very difficult to determine. This is another application of the second best. Since exchanges may have market power, the additional competition from off-exchange venues can improve efficiency even if it raises adverse selection costs for some traders. Moreover, as I’ve argued in my HFT posts recently, since some informed trading is of the rent seeking variety, by reducing the returns to informed trading dark pools can reduce wasteful investments in information.

This means that Duffy’s criticism of dark pools might be right. But it might be wrong.

One thing is definitely true. Market structure has huge distributive effects. Although the rules on dark pools have very uncertain efficiency effects, there is no doubt that these rules affect the distribution of costs and benefits across different types of traders. It is precisely these distributive effects which make the battles over market structure so divisive and protracted.

I’d also note that Duffy ignoring some features of futures markets, and derivatives markets generally, that perform functions similar to dark pools. For instance, CME allows block trading. Indeed, it is engaged in a tussle with the CFTC, which wants to reduce the amount of block trading in order to force more volume into the order book.

But block trades are a way that less-informed large traders can reduce adverse selection costs. They have long performed this function in equity markets, and are now doing so in futures. And by stripping out that order flow from the order book, block trades have the same effects as dark pools.  Blocks are a form of fragmentation.

Block markets are non-anonymous: that’s how they screen out the informed. Block traders won’t deal with those they believe likely to be informed, and by trading face-to-face traders can develop reputations for not being informed and profiting systematically at the expense of their counterparties.

Well, wouldn’t you know it, but this is how OTC derivatives markets work too. The lack of price transparency in OTC markets is often bewailed, but OTC markets are transparent in another important way that exchanges are not: they offer counterparty transparency, whereas exchanges are counterparty opaque. This benefits, say, firms that are trading to hedge in large volume (who are likely to be uninformed). It’s not a surprise that trading activity migrated from OTC to blocks on CME and ICE after Frankendodd made swaps trading more expensive. Both futures blocks and swaps are ways of reducing the execution costs of large, likely uninformed traders.

Put differently: blocks (and swaps) are a form of fragmentation, in the sense that they divert trading activity away from the limit order book. So Duffy shouldn’t be quite so sure about the superiority of the futures market model. It is fragmented in its own way, and has a lot more market power. But of course Duffy likes the last part, though he would never admit it.

 

 

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