Streetwise Professor

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 😛 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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April 18, 2014

Stiglitz on HFT

Filed under: Derivatives,Economics,Exchanges,HFT,Regulation — The Professor @ 11:39 am

Joe Stiglitz presented a paper on HFT at the Atlanta Fed conference earlier this week that has received a lot of attention. The paper is worth reading, but I actually recommend Felix Salmon’s synopsis, which breaks out the issues nicely.

I agree with Stiglitz in part, and disagree in part. The agreement is that Stiglitz hits many of the themes of my recent posts on HFT, notably that when there is private information, financial markets are unlikely to reach first best outcomes, and that making welfare comparisons is very difficult: I would say nigh-on to impossible, actually. Stiglitz also recognizes that HFT affects the incentives to collect information, which is another theme that I’ve emphasized.

Where I disagree is that Stiglitz (like DeLong) concludes from these insights that HFT is wasteful and should be restricted. This conclusion does not follow at all, and can be traced to some implicit assumptions about the nature of informed trading by non-HFT traders.

Stiglitz says “HFT discourages the acquisition of information which would make the market more informative in a relevant sense.” And by “relevant sense” he means fundamental information about the real economy. He laments that HFT “can be thought of as stealing the information rents that otherwise would have gone to those who had invested in information.” Further, he criticizes that much of what HFT does is merely accelerate the revelation of this information, and this acceleration is so small that it cannot improve any decision on any margin, and hence the resources used by HFT are wasted.

But this implicitly assumes that the information produced by non-HFT traders, the collection of which is reduced by the “stealing of information rents”, is in fact fundamental information that would improve decisions. But as I’ve noted repeatedly, many of the informed traders who HFT firms sniff out are producing information that does not improve any economic decision on any margin. Getting better information about an impending earnings report can be very profitable, but revelation of this information doesn’t improve decision making.

By assuming that non-HFT informed traders are producing information that invariably improves decisions, Stiglitz misunderstands what a great deal of informed trading is about, and thereby ignores a benefit of HFT order anticipation-based trading, and crucially, of HFT quote adjustments that cause markets to run away from big traders and thereby limits their ability to profit on their information.

One way to think about it is that there is cash flow relevant information, and decision relevant information. Pretty much all decision relevant information is cash flow relevant, but not all cash flow information is decision relevant. One major example is what Stiglitz emphasizes: the slight acceleration of revelation of information. But I claim that a lot of the information produced by institutional traders is of exactly this type. Stiglitz (and DeLong) ignore this, which leads them to biased appraisals of the efficiency of HFT.

That is, once one recognizes that some informed trading is rent seeking, and socially wasteful, “stealing of information rents” by HFT can be a feature, not a bug.

Stiglitz also ignores that even if HFT reduces the amount of decision relevant information produced and incorporated into prices, reducing this source of private information still reduces the adverse selection costs incurred by uninformed investors trading for portfolio rebalancing or hedging reasons. This reduction in adverse selection costs tends to improve the allocation of risk. This benefit must be weighed against any cost arising from the reduction in the production of decision relevant information.

In brief, Stiglitz and I agree that HFT reduces the incentive to collect information. Where we differ is that Stiglitz believes this is an unmitigated bad, whereas I strongly believe that this is totally wrong, because Stiglitz’s characterization of informed trading is very unrealistic. My point is that non-HFT informed trading can be parasitic, but Stiglitz does not recognize this or account for it in his analysis.

Stiglitz also complains that HFT liquidity is junk liquidity. In particular, prices move before large orders can be executed.

This is a variant on the criticism that HFT reduces information rents. Moreover, Stiglitz fails to make comparisons between realistic alternatives. The ability to adjust quotes faster reduces adverse selection costs, and allows HFT to quote tighter markets. Restricting HFT in some way will lead to wider spreads and lower quoted depth. Either way, big orders will have a price impact.

Stiglitz also claims that HFT reduces other, better forms of liquidity. Salmon actually explains this point more clearly:

HFT does not improve the important type of liquidity.

If you’re a small retail investor, you have access to more stock market liquidity than ever. Whatever stock you want to buy or sell, you can do so immediately, at the best market price. But that’s not the kind of liquidity which is most valuable, societally speaking. That kind of liquidity is what you see when market makers step in with relatively patient balance sheets, willing to take a position off somebody else’s book and wait until they can find a counterparty to whom they can willingly offset it. Those market makers may or may not have been important in the past, but they’re certainly few and far between today.

HFT also reduces natural liquidity.

Let’s say I do a lot of homework on a stock, and I determine that it’s a good buy at $35 per share. So I put in a large order at $35 per share. If the stock ever drops to that price, I’ll be willing to buy there. I’m providing natural liquidity to the market at the $35 level. In the age of HFT, however, it’s silly to just post a big order and keep it there, since it’s likely that your entire order will be filled — within a blink of an eye, much faster than you can react — if and only if some information comes out which would be likely to change your fair-value calculation. As a result, you only place your order for a tiny fraction of a second yourself. And in turn, the market becomes less liquid.

These points are pretty dubious. The kinds of market makers that HFT displaces (locals on futures exchanges, specialists, day traders) were hardly characterized by “relatively patient balance sheets.” Their holding periods were also quite short. Indeed, one of the filters academics use to identify HFT traders is firms that end the day flat: this exactly what most locals and specialists strove to do. And most traders that “do a lot of homework on a stock” were not doing so to supply liquidity through limit orders that they did not adjust frequently. Those who do a lot of homework are usually liquidity takers, not liquidity suppliers.

In sum, although Stiglitz’s analytical framework and broad conclusions are correct, his specific conclusions about HFT are not. They are not correct primarily because he has a very unrealistic view of the nature of informed trading. Once one recognizes that much informed trading is a form of rent seeking-the point that Hirshleifer made over 40 years ago-most of Stiglitz’s objections to HFT dissolve. Put differently, Stiglitz is right to believe that the financial sector may be too big, in part because there can be excessively strong incentives to collect information and trade on it, but he fails to take this point to its logical conclusion when evaluating HFT.

I do find it rather odd that strongly left-leaning economists like Stiglitz and DeLong who are broadly skeptical of financial markets focus their criticism on one new feature of those markets-HFT-without considering the implications of their broader critiques of the financial sector. At root, their criticism is that much financial market activity is rent seeking. If you believe that, you have to consider how HFT affects these rent seeking activities. Once you do that, it is impossible to sustain the critiques of HFT, because even if there are rent seeking aspects to HFT, it also can reduce other forms of rent seeking.

 

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April 12, 2014

A Serious Question For Brad DeLong

Filed under: Economics,Exchanges,HFT,Politics,Regulation — The Professor @ 4:39 pm

This is totally serious. 100 percent snark free. The answer (and more importantly, the explanation) will help make explicit assumptions and logic, and thereby advance the discussion.

So here it is:

Do you oppose or support laws prohibiting trading by corporate insiders on material, non-public information? (Alternative formulation: Do you support the expenditure of resources to enforce laws prohibiting trading by corporate insiders on material, non-public information?) Explain your reasoning.

The explanation is more important than the answer.

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