Streetwise Professor

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

Putin’s Tell on What He Really Fears: Let’s Take the Hint and Make His Nightmares Reality

Filed under: Economics,Military,Politics,Regulation — The Professor @ 2:58 pm

Vladimir Putin played his favorite game today: divide and conquer. He weighed in on the $9 billion US fine of French bank BNP Paribas for its flagrant and repeated violations of US sanctions on Sudan and Iran. He took a typically narcissistic view: according to Vova, the US offered to relent on its prosecution of BNPP if France terminated its sales of Mistral attack ships to Russia:

“We know about the pressure which our U.S. partners are applying on France not to supply the Mistrals to Russia,” Putin told Russian diplomats in Moscow today. “And we even know they hinted that if the French don’t deliver the Mistrals, they would quietly get rid of the sanctions against the bank, or at least minimize them,” he said without naming BNP Paribas.

He knows this how, exactly? Electronic surveillance? (Don’t tell Angela!) A leak from the French?

Certainly Putin is trying to stir trouble between the US and France, and exploiting the French anger at the US penalties. (To which I say: the anger should be directed at the mangers of BNP Paribas, especially the offenders in its Geneva commodity finance operation who violated sanctions against malign regimes with malice aforethought.)

But the chronology is way off. The US prosecution of BNP began long before Ukraine exploded. Years before. The USDOJ was particularly furious at the French bank’s flagrant attempts to conceal its sanctions busting: the bank eliminated identifying information from the transactions in order to evade detection, a sure sign of a specific intent to commit a violation. This fury was well-stoked long before Putin’s adventurism in Ukraine/Crimea. What’s more, US prosecutors operate very independently, and those involved in the BNP case would be outraged at attempts to interfere in their case against the French by a White House playing geopolitical games, especially given the years and blood, sweat, and tears involved in the prosecution. Prosecutors do not take orders from on high, especially in big cases like this.

This is likely another example of Putin projection. This is how Putin would have instructed his prosecutors to act, and they would have implemented his instructions without question: he just presumes that the same would happen in the US. But the US is very different in that regard. Indeed, I would wager that if the White House did attempt to interfere in this way, the prosecutors would have leaked.

Of course Putin has another agenda here. He realizes that the biggest threat he faces is US sanctions that would be enforced (via the financial provisions of the Patriot Act) by prosecuting any sanctions violator who deals in dollars just as the US has prosecuted BNP. By emphasizing the existential legal threat that European banks would face under a sanctions regime, Putin is attempting to fuel opposition to sanctions: since Obama has made it plain that he will not proceed with sanctions without European support, by fomenting European opposition he can counter the US. To the Europeans (and probably American banks too), the easiest way to avoid severe punishments for sanctions violations is to have no sanctions at all. Which is what Putin wants.

In other words, Putin’s mischievous comment on the BNP Paribas case is a tell. He is revealing what he really fears.  So let’s take the hint, and make his nightmares reality.

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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 26, 2014

There’s Gold in Them Thar Vaults, Boys! Um, Maybe Not

Filed under: China,Commodities,Economics,Politics,Regulation — The Professor @ 7:48 pm

If the vaults are in China, that is. Over the weekend I posted on the fraudulent commodity-based lending (collateralized by aluminum) in Qingdao. Now a Chinese government auditor claims that the gold used as collateral in $15 billion of loans does not exist.

To put this into context, Goldman (ha!) estimates that there are about $80 billion in loans in China collateralized by gold. Thus, the auditor’s report means that at least 20 percent of those loans are fraudulent. Given that it is likely easier to verify the existence of gold pledged as collateral than is the case for copper or soybeans, this suggests that even higher percentages of these other commodity-based loans (totaling another $80 billion) are backed by warehouse receipts that aren’t worth the paper they are printed on.

This situation creates the conditions for a horrific information contagion, which is the worst sort of systemic risk. Many analyses of systemic risk focus on counterparty credit risk, where the failure of one institution topples a set of interconnected dominoes. But historically, the domino problem has been less of a source of financial crises than information contagion. For instance, information contagion was arguably a far more important cause of the 2008 crisis than counterparty contagion.

Information contagion is a panic that results when the quality of assets in one part of the financial system leads people to question the value of other assets, usually similar but not always. For instance, in 2008,  the problems at Bear and Lehman were the result of bad mortgage investments by these firms. This raised questions about the solvency of other financial institutions that held, or were believed to hold, similar assets. Suddenly all banks became suspect, and had problems funding their assets. They started dumping assets to raise cash, which cratered prices and thereby created problems in institutions that had to mark their assets to a (now depressed) market. Banks that had extended liquidity support to SIVs had to bring them back on their balance sheets, threatening to make them undercapitalized.

Information contagion is most likely to occur, and is most severe when it does, when (a) asset values and balance sheets are opaque, and (b) financial institutions engage in a lot of maturity transformation (i.e., borrowing short to lend long). When asset values and balance sheets are opaque, market participants are more likely to draw inferences from revelations about the values of other firms/assets, because they can’t evaluate the firms/assets directly. In these circumstances, bad news about one firm or one type of asset can lead to a massive loss in confidence in other firms and assets. When these assets are funded with short term borrowings, firms can’t roll over their loans under these conditions, and are more likely to go bankrupt. Moreover, they are more likely to dump assets in fire sales that impose externalities on other firms holding similar assets.

China’s financial system is nothing if opaque. This is particularly true of the shadow banking system, but the banking system is also incredibly murky. For instance, the actual quality of loans on bank books is very difficult to assess. A lot of loans reported as performing are actually quite dodgy.

Information contagion is especially likely because the nature of the revelations about commodity loans raises serious questions about the monitoring of loans and the evaluation of the creditworthiness of borrowers and the quality (and existence!) of their collateral by financial institutions. If banks do a bad job at evaluating commodity loans and borrowers, and commodity collateral, it is reasonable to infer that they do a bad job at monitoring other loans and evaluating other borrowers. It is these sorts of inferences that lead to information contagion.

Moreover, maturity transformation is ubiquitous in China. This is especially true in the shadow banking system.

What this means is that although a few tens of billions of loans backed by non-existent collateral may not seem like a big deal in a financial system with about $17 trillion in credit outstanding (about 35 percent of which is in the shadow sector), the ramifications are far more serious than the value of these commodity loans suggest. There is a serious risk that doubts about the quality of the commodity loans will lead to growing doubts about the quality of other assets, especially in the shadow banking sector.  This creates the potential for panics and runs in that sector, and given the connections between shadow financial institutions and mainstream banks (connections which are themselves opaque) this could spillover into the conventional sector.

In other words, the potential for information contagion in a highly leveraged (with credit at about 250 percent of GDP), highly maturity transformed, and exceedingly opaque financial system is what makes the fraudulent commodity loans a big deal. Potentially a very big deal.

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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 21, 2014

Channeling Tino de Angelis in Qingdao

Filed under: China,Commodities,Economics,Regulation — The Professor @ 3:22 pm

Back in the early-60s, a guy named Tino de Angelis*, owner of the Allied Crude Vegetable Oil Refining Corporation, carried out a huge scam based on commodity finance. He bought soybean oil, against with American Express issued warehouse receipts. De Angelis took the warehouse receipts to banks, who took them as collateral against loans issued to Allied. And not just banks. Companies like Bunge and Proctor and Gamble also lent against the warehouse receipts.

So far, this is routine: commodity traders and processors routinely use their inventories as collateral against loans they use to finance them. The scam came in the fact that Allied obtained loans on non-existent bean oil. De Angelis had a variety of schemes to fool Amex into believing he owned more bean oil than he really did. Some of the tanks at Allied’s facilities did have oil in them, and those would be shown to Amex inspectors. The inspectors would then be led through the firm’s labyrinthine facility, allegedly to another tank to inspect. Except they’d been led back to the tank they had already inspected, but the number on the tank had been changed. Another con was to fill the tanks with water, with some oil sitting on top of the water. Allied also linked the tanks with pipes, and would shuttle the oil between tanks to keep ahead of the inspectors.

Through these means, de Angelis amassed warehouse receipts for quantities of oil that exceeded the entire amount in the US, and borrowed about $200 million against the phantom inventories (well over $1 billion in current dollars). Eventually, inspectors figured out the scheme, and the fraud was uncovered. The revelation caused Amex’s stock price to plummet (Warren Buffet scooped up some and made good money off the deal). Moreover, soybean oil futures also crashed.

De Angelis went to jail. Went released, he tried to run a Ponzi scheme.

This all happened more than 50 years ago: the scam was revealed a few days before JFK was assassinated. But a replay appears to be occurring in China, in the port of Qingdao specifically (though there are concerns that other ports may have similar problems). One trading firm has found to have borrowed large sums collateralized by non-existent aluminum allegedly stored in the port.

This is a major concern because commodity-based lending is a big deal in China, and if the practice is indeed widespread it could result in large losses. Commodity-based lending has been used in carry trades involving using letters of credit to borrow dollars buy commodities (initially mainly copper, but now other metals, iron ore, and ag products) that are imported into China and put in warehouses. The warehouse receipts are then used to collateralize loans in China, the proceeds of which are invested in high yielding, speculative endeavors.

This entire structure was already very fragile (because carry trades are inherently fragile), but if it turns out that even of a modest proportion of the collateral doesn’t exist it could collapse altogether. This could impose substantial losses on many banks. CITIC and Standard Charter are facing losses on the loans to the Qingdao trader. If there are many others, many more banks (and perhaps some western trading firms) could be hit hard.

One note of caution: some (notably Zero Hedge) are saying that collateral has been “rehypothecated.” This is not correct. Rehypothecation involves the lender pledging the collateral received from the original buyer as collateral to a loan. This process may occur several times. This results in the issuance of gross debt that is a multiple of the value of the collateral (the multiple could be as large as the inverse of the “haircut” on the collateral). But the net debt is approximately equal to the value of the collateral, and fraudulent receipts are not created. These collateral chains are potentially fragile, but the fragility does not result from the creation of fraudulent receipts.

In contrast, as described, the Qingdao scheme is like de Angelis’s, in that receipts are issued on non-existent goods. In this scheme, fraudulent receipts are created, and the net debt exceeds the value of the actual collateral. Of course, if the fraudulent receipts are rehypothecated, things will get uglier still.

Dealing with this mess would be hard enough in a jurisdiction with a solid and transparent legal system, reliable judges, and the rule of law. One can just imagine how this will play out in China, which has none of the above.

Then there are potentially broader implications. The commodity loans are one part of China’s vast shadow banking system. Concerns about the fragility of this system abound. If (a) the commodity loan problems are more pervasive, and (b) these problems are symptomatic of shoddy and fraudulent practices in the shadow banking system more generally, there is an appreciable risk of a financial crisis in China.

* Interestingly, de Angelis made money primarily on government programs, namely the National School Lunch Act and Food for Peace.

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June 18, 2014

SWP Itoldyasopalooza

Filed under: Clearing,Commodities,Derivatives,Economics,Energy,Politics,Regulation — The Professor @ 8:22 pm

While I’m doing the SWP Itoldyasopalooza, three more items.

First, the CFTC has reopened comments on the position limits proposed rule. The CFTC has taken intense incoming fire on the issue of hedge exemptions in particular, and with good reason. There are many problems, but the most egregious is the restriction on “cross hedges” (e.g., using gas futures as a hedge against electricity price risk).

I discussed this issue in my comment letter to the CFTC. Here’s the gist of the problem. The CFTC calculates the hedging effectiveness (measured by the R2 in a regression) of nearby NG futures for spot electricity prices. It finds the effectiveness is low (i.e., the R2 in the relevant regression is small). Looking past the issue of how some risk reduction is better than nothing, this analysis betrays a complete misunderstanding of electricity pricing and how NG futures are used as hedges.

Spot electricity prices are driven by fuel prices, but the main drivers are short term factors such as load shocks (which are driven by weather) and outages. However, these spot-price drivers mean revert rapidly. A weather or outage shock damps out very quickly.

This means that forward power prices are primarily driven by forward fuel prices, because fuel price shocks are persistent while weather and outage shocks are not. So it makes perfect sense to hedge forward power price exposure with gas futures/forwards. The CFTC analysis totally misses the point. Firms don’t use gas forwards/futures to hedge spot power prices. They are using the more liquid gas futures to hedge forward power prices. This is a classic example of hedgers choosing their hedging instrument to balance liquidity and hedging effectiveness. Gas forwards provide a pretty good hedge of power forward prices, and are are more liquid than power forwards. Yes, power forwards may provide a more effective hedge, but that’s little comfort if they turn out to be roach motels that a hedger can check into, but can’t leave if/when it doesn’t need the hedge any more.

The CFTC  ignores liquidity, by the way. How is that possible?

Market participants have strong incentives to make the liquidity-hedging effectiveness trade off efficiently. They do it all the time. Hedgers live with basis risk (e.g., hedging heavy crude with WTI futures) because of the liquidity benefits of more heavily traded contracts. The CFTC position limit rule substitutes the agency’s judgment for that of market participants who actually bear/internalize the costs and benefits of the trade-off. This is a recipe for inefficiency, made all the more severe by the CFTC’s utter failure to understand the economics of the hedge it uses to justify its rule.

As proposed, the rule suggests that the CFTC is so paranoid about market participants using the hedge exemption to circumvent the limit that it has chosen to sharply limit permissible hedges. This is beyond perverse, because it strikes at the most important function of the derivatives markets: risk transfer.

(This issue is discussed in detail in chapter 8 of my 2011 book. I show that the “load delta” for short term power prices is high, but it is low for forward prices. Conversely, the “fuel price delta” is high for power forward prices, precisely because load/weather/outage shocks damp out quickly. The immediate implication of this is that fuel forwards can provide an effective hedge of forward power prices.)

Second, Simon Johnson opines that “Clearing houses could be the next source of chaos.” Who knew? It would have been nice had Simon stepped out on this 5 years ago.

Third, the one arguably beneficial aspect of Frankendodd and Emir-the creation of swaps data repositories-has been totally-and I mean totally-f*cked up in its implementation. Not content with the creation of a single Tower of Babel, American and European regulators have presided over the creation of several! Well played!

Reportedly, less than 30 percent of OTC deals can be matched by the repositories.

This too was predictable-and predicted (modesty prevents me from mentioning by whom). Repositories are natural monopolies and should be set up as utilities. A single repository minimizes fixed costs, and facilitates coordination and the creation of a standard. I went through this in detail in 2003 when I advocated the creation of an Energy Data Hub. But our betters decided to encourage the creation of multiple repositories (suppositories?) with a hodge-podge of reporting obligations and inconsistent reporting formats.

This brings to mind three quotes. One by Ronald Reagan: “‘I’m from the government and here to help you’ are the 8 scariest words in the English language.” The other two by Casey  Stengel. “Can’t anybody play this game?” and “He has third base so screwed up, nobody can play it right.”

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