Streetwise Professor

I may have to start calling Timmy! Rodney instead–as in “I don’t get no respect” Rodney Dangerfield.  The latest Timmy!/Rodney  smackdown came from German Member of European Parliament Werner Langen, a major player in European financial regulation: the FT calls it a stinging rebuke, and if you read the article, you’ll find that a fair characterization. Langen accuses Geithner of misstating the changes in derivatives regulation that the G20 agreed to, and attempting to force Europe to do things that it did not commit to do.

The undiplomatic rhetoric–disses, really–directed at Geithner is pretty astounding.  As I said earlier, I cannot recall anything like them directed with such regularity at any other US cabinet official.

Take it away, Rodney!:

Apparently not having enough on its plate, the CFTC has seen fit to vote out a NOPR on collateral segregation for cleared swaps.  The Commission decided to jettison the omnibus customer account model used successfully for donkey years in futures markets, and to require OTC CCPs to segregate collateral in their books and records, while permitting comingling of customer moneys in one account.  This legal segregation/operational comingling of customer collateral is intended to protect customers against “fellow-customer risk,” i.e., the risk that  the margins of non-defaulting customers of a futures commission merchant (FCM) that (a) has defaulted, and (b) has customers in default will be used to meet shortfalls in the defaulting customers’ accounts.

I wrote about this last year in a post titled “Alfred E. Newman Chooses an FCM: the Moral Hazard of Segregation.”  I argued that it is necessary to understand why futures exchanges would choose–and stick with–the omnibus model that exposes customers to the risk of each others’ default.  The most likely answer is that it provides customers with an incentive to monitor their FCMs.  FCMs that are undercapitalized, or which do not manage risk properly, pose a greater risk customers.  By giving customers skin in the game, they have an incentive to monitor the FCM’s capitalization and the adequacy of its risk management.  With segregation, customers can play Alfred E. Newman: “What?  Me worry?”  They have zero, zip, nada incentive to monitor their FCM.  Their money is safe even with an undercapitalized, or even crooked, broker.  This lack of customer monitoring leads to the survival of riskier FCMs, thereby increasing the risk in the system.

The CME and ICE Trust made a similar argument in letters to the CFTC.  Their letters apparently, uhm, cut no ice with a majority of the commissioners.  The CFTC evaluated the argument and rejected it.  In a nutshell, the Commission bought into the argument advanced by big money managers and pension funds that they don’t have the information to monitor FCMs.

This assertion has problems on many levels.  Yes, customer information about the safety and soundness of FCMs is imperfect.  They can’t evaluate that risk perfectly.  But they can see things like whether the FCM is overcapitalized, and by how much.  They can get some kind of idea as to what kind of customers the FCM serves.  They can observe first hand how the FCM manages the risk of that particular customer: does the FCM insist on prompt payment of margins?  Does it collect and evaluate information on the customer’s creditworthiness?  To the extent that a customer perceives that an FCM is slacking off with him, he can infer that’s a more general problem.  So they can–and do–observe signals on FCM safety and soundness.

And note that there is monitoring by multiple customers.  Each one might observe a noisy signal of FCM creditworthiness, but collectively they may get a relatively precise signal.  The literatures on global games and bank runs suggests that there are mechanisms whereby customers who decide whether to patronize an FCM based on a noisy signal of its riskiness can provide effective monitoring.

A sketch of a model would go something like this.  Customers observe a noisy signal on FCM riskiness.  They know other customers are observing noisy signals.  Each customer adopts a cut-off rule that says “I leave if I get a signal that the riskiness of the FCM rises above a certain level.”  In equilibrium, when enough customers get a bad signal, they run.  Sometimes that’s inefficient because they are fooled by bad draws of the signal.  But with enough customers, that’s relatively unlikely.  Instead, runs tend to occur when the FCM is in fact risky.  The prospect of being destroyed in a run gives an FCM an incentive to control its risk.

Things appear to work this way in practice.  Runs on FCMs often precede revelations that there is something seriously remiss.  There was a run on Refco before it imploded.  Ditto Lehman:

Some argue that the futility of relying on risk mutualisation in the default waterfall was illustrated by the fact that Lehman’s omnibus customer account dropped by roughly 75 percent during the week prior to its default. However, others say this proves the current system works.

“It shows market participants have the incentive to monitor the financial health of their FCM. Moving to an LSOC regime may well undermine this incentive,” said Taylor at the CME.

Exactly, Kim.

There is also empirical evidence that monitoring of relatively opaque financial institutions does occur when there is an incentive to do so.  In the 19th century, notes of different banks sold at varying discounts to reflect creditworthiness, and market participants would often run on banks that were perceived to be unduly risky.  Evidence presented by Calomiris and Gorton and others shows that these runs were not Diamond-Dybvig “sunspot” runs, but reflected bad fundamentals.  Rates in the Fed Fund market depend on the creditworthiness of the borrower.  Similarly, prices on CDS depend on creditworthiness of the counterparties.

As I noted earlier, big money managers and pension funds were pushing for segregation–indeed, greater segregation than the CFTC actually settled on.  Their protestations of their inability to monitor should be taken with a grain of salt–and would be quite alarming if true.  No, I think that the main motive is that they do in fact incur costs to monitor FCMs, but that other customers effectively free ride of their monitoring.  Segregation allows them to play Alfred E. Newman, and not worry about their FCMs risk–and thus not have to incur the costs of monitoring.

If the foregoing analysis is correct–and the CFTC’s arguments certainly don’t convince me otherwise–the proposal will increase total risk in the system, and shift costs from one kind of customer (the money managers and FCMs) to other customers.  This will come in the form of higher initial margins and higher default fund contributions because the inability to mutualize risk among customers requires shifting that risk elsewhere.  It will also come in the form of greater–and perhaps much greater–operational costs.  But note that these will all hit the big money managers and pension funds less than smaller entities.  They typically have lower funding costs (and hence are less impacted by the margin increases) and since many of the increased operational expenses are fixed costs, they have a bigger impact on the smaller firms.

Note too there are other possible regulatory responses that can reduce monitoring costs without interfering with incentives to monitor by fiddling with segregation.  In particular, improving FCM disclosures would help.  These could include providing customers with statistics on the fellow-customer risk they face, based, for instance, on stress tests.  CCPs perform such evaluations to estimate the risk they take on from FCMs and their customers, and properly protected and presented, such information would allow customers to make discriminating choices among FCMs based on risks and rewards.

There are other problems with the proposal.  In particular, given the concern about systemic risk in clearing, the proposal is particularly troubling.  CCPs mark-to-market on a daily or twice-daily or greater basis.  Thus, once or twice a day it is necessary for FCMs to meet variatio margin calls on both customer and house accounts.  Frequently the FCM needs to meet the call before the customer has provided the funds.  So in meeting the call, the FCM extends credit to the customer.  Moreover, settlement banks typically extend credit to the FCM to meet the variation margin payment.  In the omnibus system, banks view the credit as being collateralized by the omnibus account.  This is well diversified, usually, across customers and across products in the customer accounts.

Moving to segregation basically makes this credit mechanism unworkable, or at least far more costly than under the omnibus system.

This credit mechanism is extremely important.  Indeed, the possibility of its breakdown during times of market stress is one of the things that poses threat to the viability of a clearing system.  The near failure of this credit mechanism on 20 October, 1987 is what threatened the collapse of the major Chicago CCPs.

So what replaces it? It’s not immediately obvious how credit could be extended to meet variation margin payments in a segregated system in the way it is in an omnibus system.  With segregation, a bank extending credit to an FCM doesn’t have recourse to the entire portfolio of customer funds.  Individual accounts pose more risk, and are more difficult for the bank to evaluate.  It is also more operationally difficult to evaluate creditworthiness and to extend credit on hundreds of single accounts rather than a single omnibus account. So it will be much more costly to use credit to meet the metronomic variation margin calls.

But margin calls will still need to be met, and fast.  With credit being far more costly, FCMs will have to hold more liquid assets, and will likely require customers to post higher margins in order to have the cash necessary to meet the calls: in effect, segregation increases–perhaps dramatically–the precautionary demand for liquid assets. Moreover, during periods of market stress, even these additional holdings of liquid assets may not be enough to meet margin calls.  Riddle me this, Gary: What happens then, when they can’t be financed by credit?

This represents a major change in the operation of the market.  Given that it was possible for CCPs to operate in the past, but chose not to, it is reasonable to conclude they did not do so because it is more expensive than the omnibus system.

There’s also a monitoring angle here too.  Banks that extend credit to FCMs monitor them.  They are not going to extend credit to FCMs that are undercapitalized, or which do not manage properly the risk in the customer accounts.  So the omnibus system gives settlement banks an incentive to monitor FCMs.  Go to segregation, and that bank incentive to monitor vanishes.

There is a broader issue here.  Why does the CFTC perceive that it is necessary to impose a particular mechanism on market participants?  What is the market failure here?

The choice of segregation mechanism, and the specification of the default waterfall more generally, involves complicated trade-offs and incentive effects.  Yes, fellow-customer risk is a bummer, but we don’t live in Nirvana: we can’t make it disappear.  To reduce fellow-customer risk you either have to push the risk elsewhere or pay real costs to reduce it.

Exchanges and CCPs internalize many of the costs and benefits of those trade-offs and incentives.  If they choose an costlier mechanism, or one that allocates risk inefficiently, or one that provides bad incentives to control risk, the demand for their services declines.  They see lower volumes and lower prices as a result.

Now this may not work perfectly to achieve a first best outcome in the omniscient social planner sense.  But exchanges and CCPs (and integrated exchanges that operate CCPs) tend to have better information and stronger incentives than any regulator.  Absent some convincing demonstration that there is some major externality or other problem that leads them to choose badly, there is no basis to prescribe just how they should operate their businesses.

But no.  The CFTC just can’t seem to leave well enough alone.  It has again arrogated to itself the authority to impose a system on the marketplace, without making any showing whatsoever that competition and private contract lead to inefficient outcomes that can be improved by regulatory fiat.  This is especially perverse in this particular instance given that the likely outcome of the dictat is to increase risk–and indeed systemic risk.  All in the name of implementing an act ostensibly implemented to reduce risk.

How much irony can we take?

In 1974 or 1975, the Chicago Bears were unhappy with the condition of their home, Soldier Field.  They made noises about moving to Arlington Heights, a Chicago suburb.  Da Mare, Richard J. Daley, was having none of it.  I recall his angry statement at a press conference, delivered in his very imitable Bridgeport accent: “If da Bears wanna move to Arlington Heights, dey can call demselves de Arlington Heights Bears.”*   Daley laid it on the table for Bears owner George Halas:

“I think that’s fine, George. You’re a businessman. Do what you have to do. By the way, our lawyers say you can’t take the name Chicago with you out there. We’d have to take you to court. That could take years. I wonder how many people will come out to see The Arlington Heights Bears? I wonder how excited the network people will be about broadcasting The Arlington Heights Bears? You’re a fine businessman, George. You make the call.”

[And you wonder where Obama learned about Gangster Government?  He was raised in its American cradle.]

Fast forward nearly 40 years, and another Chicago icon–The Exchange Formerly Known as the Chicago Mercantile Exchange Now Called the CME Group–is making noises about leaving Chicago.  But not for Arlington Heights, because that would not solve its problem.  Its problem, you see, is that the corporate tax in Illinois is high and going higher–30 percent higher, in fact, due to a measure rammed through the state legislature by Governor Pat Quinn by means fair and foul, but mainly foul.  CME Group is thus facing the prospect of paying a far higher tax if it stays in Illinois than if it decamps for more favorable tax climes, like Indiana.

As the linked WSJ piece notes, the threat is likely a negotiating ploy by the CME.  (This is Illinois/Chicago, and the people at CME know how the game is played.)  The likely outcome is that they will get relief.  Rule by Waiver at the state level.

That would be a swell outcome for the CME Group, but would be symptomatic of far deeper problems.

The first is the desperate financial condition of the State of Illinois.

The second is that the attempts to escape this condition by raising taxes is doomed to failure.  Businesses and people can move.  Businesses can die.  Businesses can not be born.  Raising taxes at the state or local level often sets off a death spiral: the tax base contracts as businesses flee or are never born and people leave, so taxes are raised more, contracting the tax base further, and on and on.  Want to see the results?  You don’t have to go far from Illinois to do that.  Go to St. Louis, where it has happened at the city level.  Go to Michigan, where it is happening state wide.

The third is that this sort of tax bargaining favors the big and connected; is inimical to the rule of law; and feeds the Gangster Government phenomenon.  Yes, it’s nothing new.  But with the increasing fiscal desperation of many major states, it’s a growing problem.

So my guess is that the CME Group will continue to call Chicago home.  But the process by which that occurs will be a depressingly instructive example in the country’s slide towards the Natural State.

* This is one of Daley’s great quotes.  My favorite was uttered at the height of the chaos at the Democratic Party National Convention in Chicago in 1968: “Da police are not dere to create disorder, da police are dere to maintain disorder.”

Scott Irwin at UIUC brought to my attention this paper by Kenneth Singleton*: “Investor Flows and the 2008 Boom/Bust in Oil Prices.”  As one would expect from Singleton, it is carefully done and thoughtful.  It is appropriately cautious about what can be achieved, given the complexity of the problem and the available data.  He characterizes the empirical part of the paper as “guidance” to efforts to create “much richer structural models.”  Knowing intimately the challenges of this structural modeling, I can say that even given extensive guidance, the challenges to actually incorporating “price drift owing to learning and speculation based on differences of opinion” into models of intertemporal resource allocation (e.g., dynamic models of storage economies).

The headline result in Singleton’s paper is that he finds a statistically significant and positive association between excess returns on oil futures contracts of different maturities and (a) the lagged thirteen week change in imputed positions of index investors, and (b) the lagged thirteen week change in managed-money spread positions.  He also finds that the one-week change in repo positions on Treasury bonds by primary dealers predicts price moves  Unlike Hong and Yogo (a paper I discuss below), he finds that open interest has no predictive power over oil futures excess returns, once these (and some other) variables are controlled for.

Two issues arise here.  The first is the interpretation of the results.  The second is their policy implications.

Singleton appeals to two explanations: limits to arbitrage (LTA) and differences of opinion (DOE).

LTA explanations make sense.  Speculators are subject to various constraints: informational frictions, information costs, fixed costs, etc., limit the amount of capital speculators have.  Moreover, this capital is subject to economic shocks, and various institutional features (e.g., the use of Value at Risk or other similar mechanisms for constraining speculation by agents) can lead to self-reinforcement of these shocks.  Furthermore, hedger demands can vary randomly due to shocks to their balance sheets and to broader financial market conditions.  This can lead to changes in risk premia in equilibrium. (A paper by Acarya, Locstoer, and Rmadorai explores these issues.  This is really an extension of Hirschleifer the Younger’s work on segmentation of commodity markets and the broader financial markets due to fixed costs of market participation.) (My work with Martin Jermakyan on electricity derivatives pricing documents (a) large premia for risks that should be diversifiable, and (b) substantial declines in these risk premia as constraints on speculation declined.  We use LTA-type explanations to explain these results.)

I have worked through the numerical analysis of a structural storage model in which the market price of risk varies randomly as a way of incorporating LTA factors into a dynamic storage model.  Quite intuitively, shocks to the market price of risk affect prices.  When the market price of risk falls, the commodity price rises and interestingly, inventories rise too.  Indeed, the inventory effect is more noticeable in simulations than the price impacts.  The intuition is straightforward: when the market price of risk falls, due, for instance, to an easing of constraints on speculators, it is cheaper to hedge inventory risks, so it is cheaper to hold inventories, and inventories go up.  The only way for inventories to go up is for spot prices to rise to reduce consumption and increase output.

I view this work as complementary to Acharya et al.  They model the factors that affect risk aversion of hedgers and speculators, but have only a crude model of the storage economy.  I treat the risk aversion affects exogenously, but have a more rigorous model of the storage economy.  It would be nice to both in one model, but that’s not really tractable.

But my reduced form model is sufficient to demonstrate that LTA-type phenomenon which lead to fluctuations in the market price of risk in a particular commodity market can be associated with price and inventory movements and with changes in speculative trading.

The DOE explanation is more, well, speculative.  They can rationalize departures from rational expectations equilibrium pricing, and hence can explain some anomalies.  But testability is problematic.  Moreover, per Hong and Stein’s 2007 JEP survey article, the main thing that separates DOE from LTA is that the former predicts much higher trading volumes.  That doesn’t map in that clearly with Singleton’s findings.

Moreover, although Singleton does a good job at presenting the state of understanding in rational expectations-type models of storable commodities (including some nice cites to my work), and mentions evidence relating to quantities, I still don’t think he confronts fully the fact that commodities are different than speculative stocks–which are the main motivation for much of the DOE literature.  Commodities are consumed and produced in the here and now, meaning that distortions in prices affect consumption and production decisions.  That should show up in quantity data.  To figure out exactly how, you’d need to integrate a model with storage and differences of opinion among market participants.  That’s a very tall order.  Similarly, you’d like to have the model make predictions about the entire forward curve.  Another tall order.

If you think that due to DOE, speculators are causing prices to be high, it is pretty clear that this will reduce consumption.  For something like oil, the effects on output are complicated.  If producers have no ability to allocate output intertemporally, the effect of the price rise is straightforward: output should go up.  Thus, if prices are forced up by speculators, this should lead to a rise in inventories.  But for oil, producers may shift output over time.  Producers can store underground by deferring production (and perhaps exploration and development), and their decisions on intertemporal allocation depend on the price today relative to what is expected to be the price in the future.  Thus, you’d need to look at a DOE model of a forward curve that incorporates intertemporal resource allocation through mechanisms other than storage.  As noted before, a tall order.

These types of theories would be necessary to understand fully what is driving energy prices.  I don’t think such an understanding is necessary to evaluate the implications of Singleton’s analysis for specific policy proposals–notably, position limits.

I imagine that the usual suspects will seize on these results to say: “Aha!  The smoking gun showing that speculation impacts prices.  Proof that we need position limits.”

Uhm, not so fast.  To the extent that the results reflect limits-to-arbitrage type effects, where shocks to hedger and speculator balance sheets drive variations in the market price of risk, position limits would be counterproductive.  If the association between prices and speculative positions reflects variations in constraints on speculators’ ability to absorb risk, or on hedgers’ demands to shed risk, constraining risk transfer will not improve things.  Indeed, it will make them worse.

The implications of difference-of-opinion-type explanations are hardly supportive of commodity position limits either.  For one thing, if you really believe that DOE results in price distortions, and this phenomenon is ubiquitous, why focus obsessively on commodities?  Why not restrict speculation in the entire investment universe?  But just how would you do that, exactly?  How would you surmount the knowledge problem and get the amount of speculation right?

But even ignoring that issue, position limits are not a discriminating tool that would eliminate the source of DOE-based distortions, to the extent they exist in this commodity market or that.  They are not a magic wand that somehow homogenizes the opinions of market participants.  Presumably even differences of opinion among hedgers, and between hedgers and speculators not constrained by position limits, would result in price impacts.  In other words, this is a ubiquitous feature of all speculative markets, not just commodity markets in an era of index funds and big money managers.

There is some evidence that speaks to this.  A paper by Hong and Yogo finds that open interest in commodity markets has predictive power over futures excess returns.  They also present a model based on gradual information diffusion (a common feature in DOE models) that can explain this result. The empirical result is hard to explain in a rational expectations context.

But note that the data in Hong-Yogo goes back to the mid-1960s.  Well before commodity index funds.  Well before hedge funds became major players in commodities.  Well before the “financialization” of commodity markets.  Meaning that if you believe that DOE and departures from rational expectations, purely fundamental-based pricing explain the result, it cannot be attributed to relatively recent financial innovations.  The Hong-Yogo results say there was no Edenic past in which commodity pricing was rational, only to be destroyed by the snake of financialization that slithered into the garden in the 2000s.

Meaning further that measures targeted at selected types of traders will not restore the non-existent Eden.  Indeed, given that the implications of these behavioral models are quite sensitive to the composition of traders, the information that each type of trader relies on, etc., it is quite possible that restrictions can lead to even greater departures from “rational” pricing.   I would surmise that if you had good data on the trading of certain categories of entities, from these earlier eras you would be able to find that the trading of some type or types of traders would have predictive power, just as Singleton finds that the trading of index funds and spread traders has predictive power.  So if you constrain index funds and spread traders through position limits, it is quite likely that the old-school categories of traders would represent a greater proportion of trading activity, and recoup their predictive power.

In brief, if you believe the DOE-type stories, you believe that these effects are ubiquitous: they are in the water.  You can’t make them go away by targeting one class of trader.  If you have two traders–you’ll have a difference of opinion.

This relates to an earlier SWP theme.  It is really necessary to be careful in distinguishing between the documentation of speculative effects, and the appropriate policy response.  To justify any policy aimed at curbing speculation, it is necessary, but not sufficient to demonstrate that speculators have somehow affected prices.  You also have to show that they have distorted them; with LTA, for instance, changes in speculation may affect prices, but not distort them in any reasonable sense of the word.  Moreover, you have to show how the specific policy will reduce that distortion.  That depends crucially on the source of the speculative distortion.

DOE-based stories are at least on far firmer ground than the typical hydraulic explanations of how speculation distorts prices.  But as I argue above, they provide weak support for position limits.  LTA-based stories provide even weaker support: indeed, plausible versions of LTA suggest that position limits will make problems worse, not better.  (For instance, if you believe that small noise traders distort prices, constraining big smart money will tend to exacerbate the effects of small noise traders.  Although this kind of story could provide a rationale for constraining ETFs that reduce the costs of noise trading–but can you design position limits that constrain noise-trader dominated ETFs but not big smart money traders?)

So my final take on Singleton’s paper is that the result is interesting, not necessarily that surprising, consistent with some non-behavioral explanations of price movements in which financial constraints and fundamentals affect prices–and a very weak basis for policy recommendations, and a particularly weak basis for justifying position limits.

Not that the usual suspects won’t try.

*That would be Kenneth Singleton the Stanford economist, not Kenneth Singleton, former MLB player.

I’m in London for a conference at the LSE. Here with the family, and we’ve seen most of the typical sites (it’s my family’s first time in the city).

The highlight for me, however, was watching the ring trading at the London Metal Exchange. (Yes.  You don’t need to tell me.  I know I’m weird.)  Very interesting.  Each metal trades for five minutes–in theory.  In reality, there is desultory bidding and offering until the last 30-45 seconds of the 5 minute period, at which time trading really picks up.  A visual illustration of volume clustering.  Although it is face-to-face open outcry trading, it is very different than Chicago.  It is more like a sequence of call auctions, rather than a true continuous auction.  Moreover, the trading crowd is small–there were 15 people in the ring, and about twice that many clustering around it.  I’m glad I could see it, after having worked with LME data and studied metals rather extensively for about 18 years (yikes!)

Thanks to Allan Schoenberg for helping to set things up, and special thanks to Miriam Heywood at the LME for giving us the tour.

Bart Chilton, apparently all knowing, has decided that the priority rules that exchanges have chosen are all wrong, and need to be changed.  In his continuing war on high frequency trading (not to be confused with his war on commodity speculation), he has condemned size priority rules.  He claims that these give “cheetah” (stop it Bart!  You’re killing me with your clever repartee) traders that can move faster than others an unfair advantage that they use to game the markets.

Any centralized trading mechanism has to have priority rules—rules that determine the sequence in which orders are filled.  Price priority—the highest bid and higher offer get executed first—is universal, but secondary priority rules are needed to break ties between bids and offers at the same price.  Different secondary priority rules are possible.  A common one is first-come-first-served.  This is called time priority, giving the earlier orders at a given price priority in execution over ones entered later.  Another secondary rule may give some priority to designated market makers.  Still another is size priority, which gives bigger orders preference over smaller ones.  There can also be hybrid rules which use time, market maker status, and size to allocate trades between quotes entered at a given price.

Each priority rule provides different incentives.  There is no obvious “best” rule: every alternative involves trade-offs.  Chilton apparently believes that time priority is best, and that size priority is unfair.  But he provides zero, zip, nada in terms of an analysis of the trade-offs involved.

Size priority, no surprise, gives an incentive to quote in size.  This can be very beneficial, as it means that big market orders can be accommodated more readily without large price movements.  This can be important in markets in which liquditiy demanders desire to trade in size—which is the case, and increasingly so.  For somebody worried about flash crashes, you’d think this would be a virtue.

Exchanges internalize many—perhaps not necessarily all, but many—of the costs and benefits of alternative secondary priority rules.  Whether they are competing, or monopolists, exchanges that choose priority rules that result in the creation of the amount and type of liquidity that is preferred by most traders in the marketplace generate more volume and can charge higher fees and can make more money.

A coherent objection to exchange choices would require some sort of demonstration that there is an externality resulting from these choices.  Chilton, to belabor the obvious, does no such thing.

Chilton says that high frequency traders program their algorithms to optimize results given the secondary priority rule.  Really?  Wow.  Who knew?  But that would be true regardless of the rule.  If exchanges went with strict time priority, the HFTs would adjust their algos accordingly—and those with the fastest connections and best programmers would win.  The algorithms would be different, but odds are that the winners and losers would be the same.

It is particularly strange that Chilton simultaneously objects to size priority rules and HFT in which the fastest algos win.  Under time priority, speed (and hence things like collocation, computing power, etc.) would be even more important.  If he has a problem with the race going to the swiftest, protesting against size priority rules is a strange way to go about it.

Unless and until there is a convincing demonstration of that exchanges face systematically distorted incentives in their choice of priority rules, regulators should butt out.  Objections to priority rule choices should be based on a clear and concise identification of some sort of externality.  For absent such an externality, exchanges have every incentive to make the trade-off that maximizes value.  Not everybody will be happy with the choice because traders are diverse.  But that’s the nature of the real world in which trade-offs are pervasive, as opposed to the Never Never land where too many regulators and legislators seem to dwell.

The deputy governor, financial services of the Bank of England, Paul Taylor, gave a speech warning of the dangers inherent in clearinghouses. All of his major points were raised in my ISDA discussion paper (and which I’ve been flogging in my research and here on SWP for going on 3 years now).  Most notably, he highlighted the dangers of procyclical margins, and the very real possibility of a CCP failure and the devastating consequences such a failure would have. Been there, said that.

Such realism is good to hear, but as I said when Bernanke echoed similar concerns, it would have been a damn sight better had people like Mr. Tucker piped up before the clearing mandate train left the station with Congressional and Parliamentary Casey Joneses at the throttle.

But here’s the truly ironic part.  As I did in my ISDA piece, Tucker grapples with how to resolve a failed CCP:

Two strategies come to mind, which I am airing for debate. The first would be ‘recapitalising’ the CCP so that it can carry on.  The second would be to aim to bring off a more or less smooth unwinding of the CCP’s book of transactions.

On the former route, in the banking sphere the basic strategy is to develop regimes for bondholders to share in the losses after the equity is wiped out; a distressed bank gets ‘recapitalised’ in some way through a reconstruction of its liabilities.  But CCPs do not issue debt, so there is not obviously an economic equivalent of recapitalisation by way of haircutting the debt claims of bondholders.  Recapitalisation would seem to entail an injection of new outside capital.   That should not come from the public sector.  So the only options are the surviving clearing members themselves or a new ‘owner’.  On the face of it, the clearing members would have to be involved, as surely the stricken CCP’s default fund would also need replenishing in order for it to continue.

If the default fund were to be replenished by its surviving clearing members, that could in principle be sorted outat the time or it could be pre programmed.  In practice, making it up at the time must be dangerous.  A pre-programmed allocation of losses would be akin to the old “Down To The Last Drop” rule that used to be employed by a Chicago clearing house [the CME], under which surviving clearing members ultimately had collectively to absorb all losses: mutualisation.  (It was dropped because, as banks became futures-exchange clearing members, bank supervisors didn’t like the unlimited exposure of CMs who were banks.  An example of unjoined-up thinking.) [That’s not the way I heard it explained by those involved in the decisions.] [Emphasis added.]

Breathe deep the irony.  Remember that the primary justification advanced for mandating CCPs was to create a firewall that would limit the exposure of major financial institutions to counterparty losses arising from derivative defaults.  That is, the concern was that the failure of one large financial institution would cause it to default on derivatives trades, imposing losses on other large financial institutions, potentially resulting in their failure.  CCPs were supposed to contain default risks and prevent the from spreading, contagion-like, through the financial system.  But Mr. Tucker argues that for clearing mandates to work, it is necessary to breach the firewall and make big financial institutions the residual claimants of counterparty risk.

Mr. Tucker has just revealed the dirty little secret.  Well not a secret exactly; I’ve been pointing this out for years, notably in my posts on AIG.  Specifically, clearing does not make risks go away.  (No, Gary, there is no magic box.)  It just shifts risk around.  It has to go somewhere.*  Collateralization, by moving derivatives counterparties to the front of the creditor line, shifts risks to other creditors (who may well be large financial institutions, in part).  If collateralization is insufficient, the risks go to the other members of the clearinghouse–which means, it goes to other financial institutions.  Put differently, it vectors the risk right back to the same financial institutions that clearing was intended to protect.

Following the inexorable logic of the situation, namely, that the risk has to go somewhere, Tucker looks for where the risk can go.  Can’t go to bondholders, because a CCP doesn’t have any.  So it must go to clearing members–large financial institutions.**  Which means we’re right back where we started.

Which is another echo.  Several times I’ve predicted that clearing mandates would likely spur a process similar to that in the apocryphal story of the Indian village infested by mice, that brought in cats to eliminate the mice, that brought in dogs to deal with the proliferation of cats, that brought in elephants to drive out the hordes of dogs . . . and then brought back the mice to rid themselves of the rampaging elephants.  Clearing mandates were predicated on the chimerical belief that it was possible to make risk go away, when in fact, its primary effect is to shift risk around.  Which raises the question of where it has to go.  The BOE’s Mr. Tucker has apparently concluded, quite logically, that ultimately it has to rest with large financial institutions where it was in the first place.

In other words, bring back the mice.

* As I’ve noted repeatedly, clearing also affects incentives and therefore can affect the level of risk in the system.  There are a variety of reasons why CCPs may lead to an increase in total risk exposure, mainly by creating moral hazard, and increasing capital efficiency through netting.

** An important caveat here.  The nature of clearing members is not exogenous, and independent of the sharing rule.  Imposing good to the last drop is likely to make big banks reluctant to be clearing members with effectively unlimited exposure to other members.  Instead, GTTLD would likely lead to the creation of affiliates with limited capitalization.  By not recognizing this likelihood, Mr. Tucker is guilty of some “unjoined-up thinking” of his own.

Update.  Whoops.  In my hurry, wrote “Taylor” instead of Tucker.  Thanks MDC.

LCH.Clearnet has announced that three exchanges have expressed an interest in buying the heretofore independent CCP.  Why does stuff like this happen on my vacation?  I’ll just make a brief comment, and leave more for later.

Jeremy Grant posits that LCH is in play because of cross margining efficiencies.  This conjecture is understandable, but fundamentally flawed.  Yes, there are definitely cross margining efficiencies.  More generally, there are economies of scope due to diversification effects that make it less costly to consolidate clearing for multiple asset classes in a single CCP.  But this does not explain why exchanges would want to vertically integrate clearing and execution.  Ownership is not necessary to exploit scope economies.  Indeed, the two things are often in tension–and are in this instance.

Scope economies do not explain integration.  Indeed, things cut the other way.  To the extent that there are more scope economies in clearing than execution (which is quite plausible), in the absence of transactions costs the most efficient way to organize the business would be to form a single clearinghouse, with which multiple execution exchanges would contract to obtain clearing services.  In fact, one of the costs of integration is that it often entails the sacrifice of scope economies in clearing.

Put differently, scope economies do not explain the pattern of ownership: the relevant question is why do exchanges find it optimal to own their own clearing facilities, rather than obtaining clearing services by contract.  That would be the way to optimize cross margining, netting, and diversification economies.   Such economies would be exploited maximally by having, say, LCH, clear just about everything, and sell its clearing services to myriad exchanges that offer execution services in different product classes.  But that’s not the way the market is moving.

Thus, the fact that many exchanges are already integrated, and why more exchanges are seeking to integrate, must arise from some other economic force than scope economies.  The most plausible explanation–and one that I advanced more than 5 years ago–is transactions costs.  Due to double marginalization problems and the transactions costs that arise when complementary activities are supplied by single firms (or by a small number of firms that do not compete vigorously), it is often efficient to integrate these complementary activities.  That is a basic lesson of Williamsonian Transactions Cost Economics (TCE).

In my view, that’s why exchanges like CME and DB have integrated, and why other exchanges have or are in the process of doing the same thing.  This drives regulators and legislators nuts: they see such integration as a nefarious scheme to leverage monopoly.  That’s bad economics–and it’s been known to be bad economics for going on 50 years.  Instead, it is all about transactions cost economization.  Regulators can try and fight it, and they will.  If they succeed in their quest, however, they will only succeed at raising costs and reducing efficiency.

Insofar as the potential LCH deals with exchanges are concerned, SwapClear is presumably a major target in any deal, but also a major obstacle.  I can’t see the banks that dominate SwapClear going along with a merger of LCH into NYSE-EuroNext or NASDAQ or LSE.  Or if that happens, I would expect them to leave SwapClear and set up their own CCP, perhaps through ICE Trust or through a new, freestanding interest rate swap and repo CCP.  (Going through ICETrust would exploit scale economies, so that would be a likely approach.)

I have more to say on this, and probably will.  But it’s been a long day in the sun, so it will just have to wait.

FT Alphaville has an interesting post on metals warehousing that resonates with my earlier post on the subject.   They call attention to a BBC report on commodities.

Recall that I dismissed the concerns about leveraging market power, and said that the crucial issue was information.  Given the availability of statistics on metals inventories, I downplayed the information advantage that warehouse owners have, but the Alphaville post suggests I was hasty in that judgment:

MR [BBC reporter Michael Robinson]: Steinweg is the last independent warehouse. Does it give them [the banks which own warehouses] an unfair advantage?

MR: John van der Lek told me he’s relieved that the Steinweg group is still independent, he says he’d like to avoid any suspicion of conflict of interest.

MR: “But what’s wrong with a bank owning a warehouse?”

ST [Warehouse operator Steinweg’s head of metals John van der Lek]: “I don’t know why they want to own warehouses. There must be a reason for that. But I don’t know why they do.”

MR: “Is it good business for a bank?”

ST: “Could be, but I don’t know, I don’t think so. I don’t have an idea what their feeling for taking over a warehouse.”

MR: “The danger is pretty obvious. That the bank has more information than other traders because it owns a warehouse?”

ST: “Yeah. That is to a danger for the traders. Maybe so we’re in a situation where people get more information out of the warehouses, but we are here independent and we would like to keep it that way. And we hope our customers appreciate that.”

All that said, trading is about information flows, and integration of traders into physical assets is ubiquitous–and has been for a long time–for exactly that reason.  Again, recall that major grain merchants did–and still do–operate the main delivery warehouses for CBOT/CME Group contracts.  Banks have been going into physical asset ownership in energy in recent years.  BP always viewed its asset ownership as a key to its trading operations.  That’s the way the game is played.

Anybody who owns the physical assets like storage facilities will have an information advantage when it comes to trading.  The relatively recent move of financial institutions into this area reflects a complementarity between access to this information flow and the ability to operate and finance trading operations.

In other words, it’s not about leveraging market power.  It’s about putting information and capital together.  That’s the essence of trading.  It’s the financial equivalent of a Reese’s Peanut Butter Cup.

The CFTC made all the front pages by filing manipulation charges against Parnon Energy, Arcadia Petroleum LTD and Arcadia Energy (Suisse), all affiliates of the trading firm Arcadia.

Let me say at the outset that I am in favor of addressing manipulation by ex post actions like those filed by the CFTC, and have long made that argument.  Let me also say that in 2002, Arcadia was accused of manipulation of Brent crude, and price patterns at the time were symptomatic of a corner, and per public reports, Arcadia’s trading was consistent with an attempt to corner.  Thus, I have no objection to the type of action the CFTC has brought, and don’t put it beyond Arcadia or a company like Arcadia to engage in manipulative conduct.  Indeed, I wish that the CFTC would rely more on ex post actions and less on things like position limits or ex ante jawboning to reduce the frequency and severity of market manipulation.

That said, based on the complaint, I conclude that the CFTC case is a tenuous one.  It is tenuous because of the novel nature of the claim, and the weak support for that claim provided by the price and trading data cited in the complaint.

The CFTC does not allege a corner.  Instead, it claims that Arcadia engaged in deceptive conduct.  It bought cash WTI forward contracts it did not need, then sold those contracts in the last three trading days of the WTI “cash window.”  The CFTC alleges that the buying deceived the market by suggesting buying interest that was not there, creating a false perception of market tightness.  This perception of increased tightness caused backwardation to increase.

Arcadia’s subsequent sales allegedly disabused the market of its (allegedly false) belief, causing backwardation to fall.  Arcadia allegedly lost money on these cash WTI purchases and sales, but made up for it through first buying and selling nearby spreads, and once the front month contract stopped trading on NYMEX, shorting the (new) nearby spread.  The creation of the perception and subsequent destruction of the perception of tightness, the CFTC alleges, generated profits for those spread positions.

Thus, the CFTC alleges a trade impact manipulation, rather than a corner.  These are always a greater challenge to prove, and the proof the CFTC adduces is hardly convincing.

In particular, the price data do not provide strong support for the allegation.  Consider the first alleged episode, in January, 2008.  Per the complaint, Arcadia bought 4.1 million barrels of February WTI cash crude.  During this period, it was also buying the February-March spread.  But in the 3 January-8 January period, when this trading–notably the cash trading, per the complaint–was allegedly creating an artificial perception of tightness in the market, (a) front month cash WTI fell by about $3.30/bbl, (b) the February-March (GH8) backwardation actually fell by 4 cents, and (c) front month WTI fell relative to front month WTS and LLS.  The spread did jump up 25 cents between the 8th and the 10th, and the WTI-LLS front month spread jumped by over a dollar, but this is after Arcadia’s purchase of the cash WTI contracts, and the purchase of the bulk of the GH8 spreads.  So to believe the CFTC, one has to believe that the market only became aware of the impending tightness with a lag–which is hard to reconcile with its assertion that it became aware that the demand was chimerical immediately on the sale of Arcadia’s cash position.

Moreover, by 15 January the GH8 spread had fallen to a level below its value prior to the commencement of Arcadia’s buying.  Then, when Arcadia began to sell the GH8 spread, the spread actually began to widen, going from 17 cents to 64 cents during the period that Arcadia was selling it. February WTI actually rose relative to February WTS during these days of selling February WTI as well.

This is all very hard to square with any assertion that the market was responding to Arcadia’s trading activity.  After all, NYMEX February futures and WTI cash forwards are effectively perfect substitutes, both allowing the buyer to take delivery of 1000 barrels of WTI in Cushing during February, 2008.  The market was showing greater signs of tightness at the very time Arcadia was reducing its demand for February WTI.  It will be devilish hard for CFTC to argue that purchases of near perfect substitutes have different price impacts, and for it to argue that the market was very sensitive to Arcadia’s trading of February WTI when its sales are associated with rising backwardation and its purchases are associated with falling backwardation.

The GH8 cash WTI spread did indeed go from backwardation to contango during the cash window of 25-28 January, when Arcadia was doing its selling of Feb cash WTI.  But February WTI actually rose during this period, and indeed rose on 28 January when Arcadia did most of its selling.  Again, this is not symptomatic of a market that was suddenly convinced that demand tightness had declined.

It must also be noted that the collapse in the February-March cash spread was equally large for LLS ($.985), and more than twice as large for WTS ($2.335).  Thus, the spread collapse was not limited to the product that Arcadia was trading.

Perhaps CFTC will argue that Arcadia’s deceptive buying had lifted and then crushed LLS and WTS spreads as well, but any manipulative buying should have a larger impact on the commodity actually bought, and the 25 January-28 January spread moves are not consistent with that.

What’s more, making this argument would present the CFTC with an acute problem.  It defines “market dominance” based on the size of Arcadia’s position relative to the WTI market.  If LLS and WTS are such close substitutes for WTI that buying one impacts the prices of the others because they are effectively one market, then for the purpose of determining market dominance Arcadia’s position must be measured relative to that market–WTI, WTS, and LLS, plus any other close substitutes.  It would be much harder to prove market dominance under such an expanded market definition.

In brief, the price and trading patterns for the January episode are not consistent with the CFTC allegations.  Prices fell throughout, even after Arcadia allegedly fooled the market into believing that conditions were tight.  Prices and backwardation did not rise when Arcadia was buying.  Backwardation was rising when Arcadia was actually selling the spread.  The spread collapse during the cash window that the CFTC apparently believes is its “Gotcha” piece of evidence was mirrored by collapses as large or larger in other types of oil.

I also note that the CFTC has provide no evidence that any of the price and spread moves were statistically significant.

The spread and trading co-movements are more equivocal during the March, 2008 episode.  The April-May (JK8) spread did rise when Arcadia bought it, and during the period it commenced buying April cash WTI.  But the biggest move in the spread, from $1.16 to $1.94 occurred when Arcadia sold its JK8 NYMEX spreads.  It was buying 3.5 mm bbl of April cash during this 14-19 March period,  but it was selling 14.4 mm bbl of JK8 spreads–meaning that it sold 10.9 million more barrels of April WTI than it bought during this period–so how could this contribute to an explosion in the perceived tightness of WTI–as indicated by the 78 cent increase in the backwardation? Note too that the WTI April cash flat price was falling $5.73 during the period it was buying the 3.5 mm bbl of April cash crude–another thing that is hard to square with a perception of increased tightness.

Furthermore, the April-May LLS spread fell by more during the cash window ($2.29) than did the WTI spread ($2.015).  This is very hard to square with any coherent manipulative theory, and as noted before, any story in which sales of WTI cause declines in the price of LLS would require a market definition under which it would likely be very hard for CFTC to prove market dominance.

I should also mention that even ignoring this problem, the CFTC’s market definition is suspect.  It compares Arcadia’s position to the company’s estimate of flows of WTI in Cushing during the delivery month.  But this ignores stocks of oil in Cushing, which were about 17 mm bbl during this period.  Now some of these barrels were not WTI, but some if not most of these barrels should be included in any calculation of the size of Arcadia’s purchases relative to the size of the market.

Corner manipulation cases are hard: the CFTC has never won one.  Trade impact manipulation cases in which it is alleged that buying or selling created false perceptions of demand are even harder to analyze and prove.  Thus, just based on the nature of the allegation alone, the CFTC has filed a very challenging case.  When one looks at the evidence the CFTC presents in its complaint, the odds become even higher.  For the January episode in particular, the most straightforward interpretation of the evidence cuts squarely against the allegations.  This will be a very difficult case for the agency to win.

There’s another lesson here that has been lost in all of the hue and cry over the filing of the complaint.  CFTC has been examining the oil market with a fine tooth comb going back to 2005 if memory serves.  If this is the best case they can find after all that, the oil market must be pretty damn clean.