Streetwise Professor

July 21, 2015

The Fifth Year of the Frankendodd Life Sentence

Filed under: Clearing,Derivatives,Economics,Exchanges,Financial crisis,Politics,Regulation — The Professor @ 7:52 pm

Today is Frankendodd’s fifth birthday. Hardly time for celebration. It is probably more appropriate to say that this is the fifth year in the Frankendodd life sentence.

So where do we stand?

The clearing mandate is in force, and a large fraction of derivatives, especially interest rate and credit index derivatives are cleared. This was intended to reduce systemic risk, and as I’ve written since before the law was passed and signed, this was a chimerical goal. Indeed, in my view the systemic risk effects of the mandate are at best a push (merely shifting around the source of systemic risk), and at worse the net effects of the mandate are negative.

Belatedly regulators are coming around to the recognition of the risks posed by CCPs. They understand that CCPs have concentrated risk, and hence the failure of one of these entities would be catastrophic. So there is a frenzy of activity to try to make CCPs less likely to fail, and to ensure their rapid recovery in the event of problems. Janet Yellen has spoken on the subject, as has the head of the Office of Financial Research, Robert Dudley of the NY Fed, and numerous European regulators. Efforts are underway in the US, Europe, and Asia to increase CCP resources, and craft recovery and resolution procedures.

This is an improvement, I guess, over the KoolAid quaffing enthusiasm for the curative effects of CCPs that virtually all regulators indulged in post-crisis. But it distinctly reminds me of people madly sewing parachutes after the rather dodgy plane has taken off.

Further, these efforts miss a very major point. The main source of systemic risk from the clearing mandate derives from the huge liquidity strains that clearing (notably variation margin on a rigid time schedule) will create when the market is stressed. There has been some attention to ensuring CCPs have access to liquidity in the event of a default, but that’s not the real issue either. The real issue is funding large margin calls during a crisis.

Moreover, as I’ve also discussed, efforts to make CCPs more resilient can increase pressures elsewhere in the financial system (the “levee effect.”) Relatedly, regulators have not fully come to grips with the redistributive aspects of clearing–including in particular how netting, which they adore, can just relocate systemic risks.

I therefore stand by my prediction that a regulation-inflated clearing system will the source of the next systemic crisis.

Moving on, I called the SEF mandate the worst of Dodd-Frank. In the US, the majority of swap trades are done on SEFs, though mainly through RFQs rather than the central limit order books that Barney and Co. dreamed about in 2010.

There was never a remotely plausible systemic risk reducing rationale for the SEF mandate. Hence, if SEFs are inefficient ways to execute transactions, the mandate is all pain, no gain. As an indication of that this is indeed the case, note that virtually all European banks and end users stopped trading Euro-denominated swaps with US counterparties exactly when the mandate kicked in. The swaps mandate was too onerous, and anyone who could escape it did.

In a piece in Risk, I referred to the Made Available to Trade part of the SEF mandate the worst of the worst of Dodd-Frank. It made no sense to force all market participants to trade a particular kind of swap on SEFs just because one SEF decided to list it. Apparently that realization is slowly sinking in. The CFTC recently held a meeting on the MAT issue, and it seems as if there is a good chance that the CFTC will eventually determine what has to be traded on SEFs.

It is an indication of my loathing for MAT as it currently exists that I consider that an improvement.

Still moving on, Frankendodd was intended to reduce concentration and interconnectedness in the financial system. The actual result cannot really be called a mere unintended consequence: it was the exact opposite of the intended effect. Completely predictably (and predicted) the huge regulatory overhead increased concentration rather than reduced it. This is particularly true with respect to clearing. Gary Gensler’s dream of letting a thousand clearing firms bloom has turned into a nightmare, in which the clearing business is concentrated in a handful of big financial institutions, exacerbating too big to fail problems. And clearing has turned out to be the Mother of All Interconnections, because every big financial institution is connected to all big CCPs, and because pretty much everyone has to funnel the bulk of their derivatives trades through clearinghouses.

I could go on. Let me just re-iterate another risk of Frankendodd: standardization–the regulators’ fetish–is  a major source of systemic risk. Monocultures are particularly vulnerable to catastrophic failure, and the international regulatory standardization that was birthed in Pittsburg in 2009, and enacted in Frankendodd and MiFID and Emir, has created a regulatory monoculture. Some are grasping the implications of this. But too few, and not the right people.

I’ve focused here on the sins of commission. But there are also the sins of omission. Frankendodd did nothing about the Fannie and Freddie monster, which is coming back from the dead. F&F was a real systemic risk, but the same political dynamic that fed it in the 1990s and pre-2008 is at work again. Get ready for a repeat.

Frankendodd should have just focused on raising capital requirements for banks and other financial institutions with liquidity and maturity mismatches, and driven a stake through Fannie and Freddie. Instead, it sought to impose a detailed engineered solution on an emergent order. This inevitably ends badly.

So maybe it would be more accurate to say that we’re in our fifth year on death row. Someday the warden will come knocking.

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July 15, 2015

The Joint Report on the Treasury Spike: Unanswered Questions, and You Can’t Stand in the Same River Twice

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

The Treasury, Fed (Board of Governors and NYFed), SEC, and CFTC released a joint report on the short-lived spike in Treasury prices on 15 October, 2014. The report does a credible job laying out what happened, based on a deep dive into the high frequency data. But it does not answer the most interesting questions.

One thing of note, which shouldn’t really need mentioning, but does, is the report’s documentation of the diversity of algorithmic/high frequency trading carried out by what the report refers to as PTFs, or proprietary trading firms. This diversity is illustrated by the fact that these firms were both the largest passive suppliers of liquidity and the largest aggressive takers of liquidity during the October “event.” Indeed, the report documents the diversity within individual PTFs: there was considerable “self-trading,” whereby a particular PTF was on both sides of a trade. Meaning presumably that these PTFs had both aggressive and passive algos working simultaneously. So talking about “HFT” as some single, homogeneous thing is radically oversimplistic and misleading.

But let’s cut to the chase: Whodunnit? The report’s answer?: It’s complicated. The report says there was no single cause (e.g., a fat finger problem or whale trader).

This should not be surprising. In emergent orders, which financial markets are, large changes can occur in response to small (and indeed, very small) shocks: these systems can go non-linear. Complex feedbacks make attribution of cause impossible.  Although there is much chin-pulling (both in the report, and more generally) about the impact of technology and changes in market structure, the fundamental sources of feedback, and the types of participants in the ecosystem, are largely independent of technology.

Insofar as the events of 15 October are concerned, the report documents a substantial decline in market depth on both the futures market, and the main cash Treasury platforms (BrokerTec and eSpeed) in the hour following the release of the retail sales report. The decline in depth was due to PTFs reducing the size (but not the price) of their limit orders, and banks/dealers widening their quotes. Then, starting about 0930, there was a substantial order imbalance to the buy side on the futures: this initial order imbalance was driven primarily by banks/dealers. About 3 minutes later, aggressive PTFs kicked in on the buy side on both futures and the cash platforms.  Buying pressure peaked around 0939, and then both aggressive PTFs and the banks/dealers switched to the sell side. Prices rose when aggressors bought, and fell when they sold.

None of this is particularly surprising, but the report begs the most important questions. In particular, what caused the acute decline in depth in the hour leading up to the big price movement, and what triggered the surge in buy orders?

The first conjecture that comes to mind is related to informed trading and adverse selection. For some reason, PTFs (or more accurately, their algos) in particular apparently detected an increase in the toxicity of order flow, or observed some other information that implied that adverse selection risk was increasing, and they reduced their quote sizes to reduce the risk of being picked off.

Did order flow become more toxic in the roughly hour-long period following the release of the retail number? The report does not investigate that issue, which is unfortunate. Since liquidity declines were also marked in the minutes before the Flash Crash, it is imperative to have a better understanding of what drives these declines. There are metrics of toxicity (i.e., order flow informativeness). Liquidity suppliers (including HFT) monitor it in real time.  Understanding these events requires an analysis of whether variations in toxicity drive variations in liquidity, and in particular marked declines in depth.

Private information could also explain a surge in order imbalances. Those with private information would be the aggressors on the side of the net imbalance. In this case, the first indication of an imbalance is in the futures, and comes from the banks and asset managers. PTF net buying kicks in a few minutes later, suggesting they were extracting information from the banks’ and asset managers’ trading.

This raises the question: what was the private information, and what was the source of that information?

One problem with the asymmetric information story is the rapid reversal of the price movement. Informed trades have persistent effects. I’ve even seen in the data from some episodes that arguably manipulative (and hence uninformed) trades that could not be identified as such had persistent price impacts. So did new information arrive that led the buyers to start selling?

A potentially more problematic explanation of events (and I am just throwing out a hypothesis here) is that increased order flow toxicity due to informed trading eroded liquidity, and this created the conditions in which pernicious algorithms could thrive. For instance, momentum triggering (and momentum following) algorithms could have a bigger impact when the market lacks depth, as then smallish imbalances can move prices substantially, which then triggers trend following. When prices get sufficiently out of line, these algos might turn off or switch directions, or other contrarian algorithms might kick in.

These questions cannot be answered without knowing the algorithms, on both the passive and aggressive sides. What information did they have, and how did they react to it? Right now, we are just seeing their shadows. To understand the full chronology here–the decline in depth/liquidity, the surge in order imbalances from banks/dealers around 0930, the following surge in aggressive PTF buying, and the reversal in signed net order flow–it is necessary to understand in detail the entire algo ecosystem. We obviously don’t understand it, and likely never will.

Even if it was possible to go back and get a granular understanding of the algorithms and their interactions, this would be of limited utility going forward because the emergent ecosystem evolves continuously and rapidly. Indeed, no doubt the PTFs and banks carried out their own forensic analyses of the events of 15 October, and changed their algorithms accordingly. This means that even if we knew the  causal connections and feedbacks that produced the abrupt movement and reversal in Treasury prices, that knowledge will not really permit anticipation of future episodes, as the event itself will have changed the system, its connections, and its feedbacks. Further, independent of the effect of 15 October, the system will have evolved in the past 9 months. Given the dependence of the behavior of such systems on their very fine details, the system will behave differently today than it did then.

In sum, the joint report provides some useful information on what happened on 15 October, 2014, but it leaves the most important questions unanswered. What’s more, the answers regarding this one event would likely be only modestly informative going forward because that very event likely caused the system to change. Pace Heraclitus, when it comes to financial markets, “You cannot step twice into the same river; for other waters are continually flowing in.”

 

 

 

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July 2, 2015

See You In the Funny Papers

Filed under: Clearing,Commodities,Derivatives,Economics,Exchanges — The Professor @ 6:01 pm

Here’s a first. I appear in a comic strip history of the CME-ICE rivalry in Bloomberg Markets Magazine. Quite the likeness!

Other than the fact that I appeared at all, the most amusing part of the, er, article, is the panel depicting CME’s Terry Duffy getting the news that ICE was making a rival bid for CBOT via a note slipped under his hotel room door at the FIA at Boca at 0600. I had eaten dinner with Duffy and CME CEO Craig Donohue the night before. They were in a little better mood then than they were the next day.

Bloomberg’s Matt Leising called me at about 0630 to ask me about the development. That led to an appearance on Bloomberg TV, where I was interviewed right before Jeff Sprecher. He watched me give the interview, and was not pleased with my prediction that CME would eventually prevail, but have to pay a lot more: I saw him say to the woman next to him (who I later found out was his wife, Kelly Loeffler) “who is this guy?” That was exactly how it worked out though, and apparently there were no hard feelings because Sprecher spoke at a conference I organized at UH a couple of years later. Either that, or he didn’t connect me with “this guy.”

Evenhanded guy that I am, I invited Craig Donohue to speak at a conference a year or two after that. His speech was interrupted by some Occupy types (remember them?), whom my tiger of an assistant Avani and I bodily shoved out of the room while the rest of the audience sat in stunned silence (not knowing what was going on).

So yeah. My involvement with CME and ICE sometimes does sound like something out of the funny pages. Now it’s official.

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June 15, 2015

Always Follow the Price Signals. I Did on Brent-WTI.

Filed under: Commodities,Derivatives,Economics,Energy,Politics,Regulation — The Professor @ 8:18 pm

As a blogger, I am long the option to point out when I call one right. Of course, I am short the option for you all to point out when I call one wrong, but I can’t help it if that option is usually so far out of the money (or if you don’t exercise it when it is in) 😉

I will exercise my option today, after reading this article by Greg Meyer in the FT:

West Texas Intermediate crude, once derided as a broken oil benchmark, is enjoying a comeback.

Volumes of futures tracking the yardstick have averaged 1m contracts a day this year through May, up more than 45 per cent from the same period of 2014, exchange data show. WTI has also sped ahead of volumes in rival Brent crude, less than two years after Brent unseated WTI as the most heavily traded oil futures market.

. . . .

WTI has also regained a more stable connection with global oil prices after suffering glaring discounts because of transport constraints at its delivery point of Cushing, Oklahoma. The gap led some to question WTI as a useful gauge of oil prices.

“I guess the death of the WTI contract was greatly exaggerated,” said Andy Lipow of consultancy Lipow Oil Associates.

But in the past two years, new pipeline capacity of more than 1m barrels a day has relinked Cushing to the US Gulf of Mexico coast, narrowing the discount between Brent and WTI to less than $4 a barrel.

Mark Vonderheide, managing partner of Geneva Energy Markets, a New York trading firm, said: “With WTI once again well connected to the global market, there is renewed interest from hedgers outside the US to trade it. When the spread between WTI and Brent was more than $20 and moving fast, WTI was much more difficult to trade.”

Things have played out exactly as I forecast in August, 2011:

One of the leading crude oil futures contracts–CME Group’s WTI–has been the subject of a drumbeat of criticism for months due to the divergence of WTI prices in Cushing from prices at the Gulf, and from the price of the other main oil benchmark–Brent.  But whereas WTI’s problem is one of logistics that is in the process of being addressed, Brent’s issues are more fundamental ones related to adequate supply, and less amenable to correction.

Indeed, WTI’s “problem” is actually the kind an exchange would like to have.  The divergence between WTI prices in the Midcontinent and waterborne crude prices reflects a surge of production in Canada and North Dakota.  Pipelines are currently lacking to ship this crude to the Gulf of Mexico, and Midcon refineries are running close to full capacity, meaning that the additional supply is backing up in Cushing and depressing prices.

But the yawning gap between the Cushing price at prices at the Gulf is sending a signal that more transportation capacity is needed, and the market is responding with alacrity.  If only the regulators were similarly speedy.

. . . .

Which means that those who are crowing about Brent today, and heaping scorn on WTI, will be begging for WTI’s problems in a few years.  For by then, WTI’s issues will be fixed, and it will be sitting astride a robust flow of oil tightly interconnected with the nexus of world oil trading.  But the Brent contract will be an inverted paper pyramid, resting on a thinner and thinner point of crude production.  There will be gains from trade–large ones–from redesigning the contract, but the difficulties of negotiating an agreement among numerous big players will prove nigh on to impossible to surmount.  Moreover, there will be no single regulator in a single jurisdiction that can bang heads together (for yes, that is needed sometimes) and cajole the parties toward agreement.

So Brent boosters, enjoy your laugh while it lasts.  It won’t last long, and remember, he who laughs last laughs best.

This really wasn’t that hard a call to make. The price signals were obvious, and its always safe to bet on market participants responding to price signals. That’s exactly what happened. The only surprising thing is that so few publicly employed this logic to predict that the disconnection between WTI and ocean borne crude prices would be self-correcting.

Speaking of not enjoying the laugh, the exchange where Brent is traded-ICE-issued a rather churlish statement:

Atlanta-based ICE blamed the shift on “increased volatility in WTI crude oil prices relative to Brent crude oil prices, which drove more trading by non-commercial firms in WTI, as well as increased financial incentive schemes offered by competitors”.

The first part of this statement is rather incomprehensible. Re-linking WTI improved the contract’s effectiveness as a hedge for crude outside the Mid-continent (PADD 2), which allowed hedgers to take advantage of the WTI liquidity pool, which in turn attracted more speculative interest.

Right now the only potential source of disconnect is the export ban. That is, markets corrected the infrastructure bottleneck, but politics has failed to correct the regulatory bottleneck. When that will happen, I am not so foolish to predict.

 

 

 

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June 13, 2015

Definitive Proof That The New York Times’ David Kocieniewski Is A Total Moron*

Filed under: Commodities,Derivatives,Economics,Energy,Politics,Regulation — The Professor @ 6:06 pm

Not that further proof is needed, but still.

You may recall that NYT “reporter” (and by “reporter,” I mean “hack”) David Kocieniewski slimed me on the front page of the NYT on 31 December, 2013. In a nutshell, Kocieniewski accused me of being in the pocket of oil traders, and that this had led me to skew my research and policy positions. Specifically, he insinuated that I opposed position limits and defended speculation in energy markets because I had been suborned by oil traders who profited from high prices, like those that occurred in 2008 (before the crash). Kocieniewski’s main piece of “evidence” was that I had written a white paper sponsored by Trafigura. According to Kocieniewski, as an oil trader, Trafigura benefited from high prices.

At the time I pointed out that this demonstrates Kocieniewski’s appalling ignorance, as Trafigura is not a speculator, and is typically short futures (and other derivatives) to hedge its inventories of oil (and other commodities). Companies like Trafigura have no real interest in the direction of oil prices directly. They make money on margins and volumes. The relationship between these variables and the level of flat prices depends on what makes flat prices high or low.  I further said that if anything, commodity traders are likely to prefer a low price environment because (1) low prices reduce working capital needs, which can be punishing when prices are high, and (2) low price environments often create trading opportunities, in particular storage/contango plays that can be very profitable for those with access to storage assets.

Well, imagine my surprise (not!) when I saw this headline and article:

Crude slide bolsters Trafigura’s profits and trading margins

Trafigura has posted record half-year profits and a doubling of trading margins, illustrating how one of the world’s largest commodity trading houses has been a big beneficiary of the collapse in oil prices.

Profits at the group rose almost 40 per cent in the six months to 31 March, reaching $654m, while margins hit 3.1 per cent, as the Switzerland-based company used its global network of traders and storage facilities to buy cheap crude and take advantage of dislocations in the oil market.

. . . .
It was not the only company to benefit. Other trading groups including Vitol, the largest independent oil trader, and Gunvor have posted strong results for this period. Even ShellBP and Total managed better-than-expected first quarter results thanks to the performance of muscular trading operations.

Wow. In Kocieniewskiworld, “Crude slide bolsters Trafigura’s profits” would be a metaphysical impossibility. Here on earth, that’s an eminently predictable event. Which I predicted. Not that that makes me a genius, just more knowledgeable about commodity markets than David Kocieniewski (which is a very low bar).

Not that there was ever anything to it in the first place, but this pretty much blows to hell the entire premise of Dim Dave’s story. Proof yet again that if you read the NYT for economics stories, you’ll wind up dumber after reading than before.

* As well as an unethical slug who blatantly violated the NYT’s ethics guidelines. Not that his editor gave a damn, making him as much of an unethical slug as Kocieniewski.

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May 29, 2015

I Think I Read These Predictions About the Impending Revolution in LNG Trading Somewhere Before

Filed under: Commodities,Derivatives,Economics,Energy — The Professor @ 2:42 pm

The FT, Goldman, Jonathan Stern at the Oxford Institute of Energy Research, Vitol, and others are now predicting that the emergence of the US as an LNG exporter, and the looming surplus driven by that plus supplies from Australia, PNG, and elsewhere, are inexorably pushing this commodity away from traditional oil-based long term contracts towards spot trading.

Huh. I remember reading something along those lines last September. Oh, yeah. Here it is. (Also available in Spanish!) I guess it’s more accurate to say I remember writing something exactly along those lines in September.

The opening of the Cheniere* and later the Freeport and Cameron LNG trains in the Gulf will be particularly important. The US is likely to be at the margin in Asia, Latin America and perhaps Europe. Prices are set at the margin, meaning that the LNG pricing mechanism can be integrated into the already robust US/Henry Hub pricing mechanism. Giving the tipping effects discussed in my paper, the transition in the pricing mechanism and the development of a robust spot market is likely to take place relatively rapidly.

I know there is skepticism in the industry about this, but I am pretty confident in my prediction. Experiences in other markets, notably iron ore and to some degree coal, indicate how rapid these transitions can be.

Funny story (to me anyways). I gave the keynote speech at LNG World Asia in Singapore in September, and I laid out my views on this subject. I gave the talk in front of the giant shark tank at the Singapore Aquarium, and I could help but think of Team America, Kim Jung Il, and Hans Blix. I’m sure there were a few people in the audience who would have liked to feed me to the sharks for calling oil-linked pricing “a barbarous relic” and encouraging them to embrace the brave new world of LNG trading.

But whether they like it or not, it’s coming. The inflection point is nigh.

*Full disclosure. Number One Daughter works for Cheniere.

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May 5, 2015

Blaming SRO Lapses on For-Profit Status: A Straw Man Dining on Red Herring

Filed under: Commodities,Derivatives,Economics,Regulation — The Professor @ 8:28 pm

The frenzy over the Sarao spoofing indictment has led to the CME Group receiving considerable criticism about the adequacy of its oversight of its markets and trading system. One argument that has been advanced is that the CME’s for-profit status (and the for-profit status of other exchanges) is incompatible with its role as a self-regulatory organization. A piece by Brooke Masters titled “Exchanges Need to Balance Policing and Profitability” in the FT a few days ago puts it this way:

The Sarao case highlights the potential problems with the current US system of relying on “self-regulatory organisations”, including the exchanges, to do much of the frontline policing of markets. They are supposed to make sure traders abide by the rules and refer serious misbehaviour on to government regulators.

This system may have worked when exchanges were owned by their members, but now that they have to generate profits for shareholders, conflicts have emerged. A market that cracks down too hard or too quickly could drive away paying customers. The CME controls the futures market allegedly used by Mr Sarao, but the temptation to go soft could be far greater in areas where trading venues compete.

This is a straw man dining on red herring. The for-profit status of exchanges has little, if anything, to do with the incentives of an exchange to self-regulate. Indeed, for some types of conduct, investor ownership and for-profit status likely improves exchange policing efforts substantially.

I addressed these issues 21 years ago, and then again 15 years ago, in articles published in the Journal of Law and Economics, and 22 years ago in a piece in the Journal of Legal Studies. In the older JLE article, titled “The Self-Regulation of Commodity Exchanges: The Case of Market Manipulation,” I demonstrated incentives are crucial, and for some types of conduct the incentives to police were weak even for non-profit exchanges.

Exchanges (which were organized as non-profits) historically made little effort to combat corners, despite their manifest distorting effects, because the biggest costs of manipulation fell on inframarginal demanders of exchange services (namely, hedgers) or third parties (people who do not trade rely on exchange prices when making decisions), but exchange volume and member profitability depended on the marginal demanders (e.g., speculators) who were little affected. Therefore, exchanges didn’t internalize the cost of corners, so didn’t try very hard to stop them. For-profit exchanges would have faced the same problem.

In other cases, exchanges-be they for profit or non-profit-face strong incentives to police harmful conduct. For instance, securities exchanges have an incentive to reduce insider trading that reduces liquidity and hence raises trading costs leading to lower trading volume. Again, this incentive is largely independent of whether the exchange is for-profit or not-for-profit.

Exchange incentives to police a particular type of deleterious conduct depend crucially on how the costs of that conduct are distributed, and how it affects trading volume and trading costs. The effect on volume and trading costs determines whether and by how much the exchange’s owners (be they shareholders or members) internalize the cost of this conduct. This internalization depends primarily on the type of conduct, not on how the exchange is organized or who owns it or whether the exchange can pay its owners dividends.

In fact, for-profit exchanges have stronger incentives to adopt efficient rules relating to certain kinds of conduct than member-owned, not-for-profit ones. In particular, the members of mutual exchanges were intermediaries; brokers and market makers mainly. The intermediaries’  interests often conflicted with those of exchange users. In particular, self-regulation on member-owned exchanges often took the form of adopting rules and polices that were explicitly intended to benefit their members by restricting competition between them, thereby hurting exchange customers. For instance, member owned exchanges operated commissions cartels for decades: Only forty years ago last Friday (“May Day”) was the NYSE commission cartel that dated from its earliest days dismantled by the SEC. Even after the commission cartels were eliminated, member-owned exchanges adopted other anti-competitive rules that benefited members. Self-regulation was in large part an exercise in cartel management.

Further, powerful members, be they big individual traders or important firms, could often intimidate exchange managers and enforcement personnel. In addition, daily interaction between members contributed to a culture in which screwing a buddy was beyond the pale, but in which many a blind eye was turned when a customer got screwed. Not all the time, but enough, as the FBI sting in ’88-’89 and its aftermath made clear.

So no, there was no Eden of mutual, non-profit exchanges that rigorously enforced rules against abusive trading that was despoiled by the intrusion of the profit-seeking snake. The profit motive was there all along: exchange members were obviously highly profit-driven. It just was manifested in different ways, and not necessarily better ways, than in the current for-profit world.

This also raise the question: just who would own, control, and manage a neo-mutual, non-profit exchange? Big banks, either directly or through their brokerage units? Does anyone think that would solve more problems than it would create? Does anyone honestly believe that there would be fewer conflicts of interest and less potential for abuse in such a setup?

This all gets back to the issue of why exchanges demutualized in the first place. It had zero, zip, nada to do with self-regulation and rule enforcement. It was driven by a seismic technological change. I showed in my 2000 JLE article that non-profit form and mutual ownership economized on transactions costs on floor based exchanges, but were unnecessary in an electronic marketplace. I therefore predicted that exchanges would demutualize and become investor-owned as they shifted from open outcry to electronic trading. That’s exactly what happened over the next several years.

In sum, exchange ownership and organizational form are not the primary or even major determinants of the adequacy of exchange self-policing efforts. The incentives to self-regulate are driven more by economic factors common to both for-profit and not-for-profit exchanges, and the choice of organizational form is driven by transactions cost economizing (including the mitigation of rent seeking) rather than by self-regulatory considerations.  The tension between policing and profit existed even in non-profit exchanges. So those who fret about the adequacy of self-regulation need to get over the idea that going back to the future by re-mutualizing would make a damn bit of difference. If only it were that easy.

 

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April 24, 2015

A Matter of Magnitudes: Making Matterhorn Out of a Molehill

Filed under: Derivatives,Economics,HFT,Politics,Regulation — The Professor @ 10:47 am

The CFTC released its civil complaint in the Sarao case yesterday, along with the affidavit of Cal-Berkeley’s Terrence Hendershott. Hendershott’s report makes for startling reading. Rather than supporting the lurid claims that Sarao’s actions had a large impact on E Mini prices, and indeed contributed to the Flash Crash, the very small price impacts that Hendershott quantifies undermine these claims.

In one analysis, Hendershott calculates the average return in a five second interval following the observation of an order book imbalance. (I have problems with this analysis because it aggregates all orders up to 10 price levels on each side of the book, rather than focusing on away-from-the market orders, but leave that aside for a moment.) For the biggest order imbalances-over 3000 contracts on the sell side, over 5000 on the buy side-the return impact is on the order of .06 basis points. Point zero six basis points. A basis point is one-one-hundredth of a percent, so we are talking about 6 ten-thousandths of one percent. On the day of the Flash Crash, the E Mini was trading around 1165. A .06 basis point return impact therefore translates into a price impact of .007, which is one-thirty-fifth of a tick. And that’s the biggest impact, mind you.

To put the comparison another way, during the Flash Crash, prices plunged about 9 percent, that is, 900 basis points. Hendershott’s biggest measured impact is therefore 4 orders of magnitude smaller than the size of the Crash.

This analysis does not take into account the overall cumulative impact of the entry of an away-from-the market order, nor does it account for the fact that orders can affect prices, prices can affect orders, and orders can affect orders. To address these issues, Hendershott carried out a vector autoregression (VAR) analysis. He estimates the cumulative impact of an order at levels 4-7 of the book, accounting for direct and indirect impacts, through an examination of the impulse response function (IRF) generated by the estimated VAR.* He estimates that the entry of a limit order to sell 1000 contracts at levels 4-7 “has a price impact of roughly .3 basis points.”

Point 3 basis points. Three one-thousandths of one percent. Given a price of 1165, this is a price impact of .035, or about one-seventh of a tick.

Note further that the DOJ, the CFTC, and Hendershott all state that Sarao see-sawed back and forth, turning the algorithm on and off, and that turning off the algorithm caused prices to rebound by approximately the same amount as turning it on caused prices to fall. So, as I conjectured originally, his activity-even based on the government’s theory and evidence-did not bias prices upwards or downwards systematically.

This is directly contrary to the consistent insinuation throughout the criminal and civil complaints that Sarao was driving down prices. For example, the criminal complaint states that during the period of time that Sarao was using the algorithm “the E-Mini price fell by 361 [price] basis points” (which corresponds to a negative return of about 31 basis points). This is two orders of magnitude bigger than the impact calculated based on Hendershott’s .3 return basis point estimate even assuming that the algorithm was working only one way during this interval.

Further, Sarao was buying and selling in about equal quantities. So based on the theory and evidence advanced by the government, Sarao was causing oscillations in the price of a magnitude of a fraction of a tick, even though the complaints repeatedly suggest his algorithm depressed prices. To the extent he made money, he was making it by trading large volumes and earning a small profit on each trade that he might have enhanced slightly by layering, not by having a big unidirectional impact on prices as the government alleges.

The small magnitudes are a big deal, given the way the complaints are written, in particular the insinuations that Sarao helped cause the Flash Crash. The magnitudes of market price movements dwarf the impacts that the CFTC’s own outside expert calculates. And the small magnitudes raise serious questions about the propriety of bringing such serious charges.

Hendershott repeatedly says his results are “statistically significant.” Maybe he should read Deirdre McCloskey’s evisceration of the Cult of Statistical Significance. It’s economic significance that matters, and his results are economically miniscule, compared to the impact alleged. Hendershott has a huge sample size, which can make even trivial economic impacts statistically significant. But it is the economic significance that is relevant. On this, Hendershott is completely silent.

The CFTC complaint has a section labeled “Example of the Layering Algorithm Causing an Artificial Price.” I read with interest, looking for, you know, actual evidence and stuff. There was none. Zero. Zip. There is no analysis of the market price at all. None! This is a piece of the other assertions of price artificiality, including most notably the effect of the activity on the Flash Crash: a series of conclusory statements either backed by no evidence, or evidence (in the form of the Hendershott affidavit) that demonstrates how laughable the assertions are.

CFTC enforcement routinely whines at the burdens it faces proving artificiality, causation and intent in a manipulation case. Here they have taken on a huge burden and are running a serious risk of getting hammered in court. I’ve already addressed the artificiality issue, so consider causation for a moment. If CFTC dares to try to prove that Sarao caused-or even contributed to-the Crash, it will face huge obstacles. Yes, as Chris Clearfield and James Weatherall rightly point out, financial markets are emergent, highly interconnected and tightly coupled. This creates non-linearities: small changes in initial conditions can lead to huge changes in the state of the system. A butterfly flapping its wings in the Amazon can cause a hurricane in the Gulf of Mexico: but tell me, exactly, which of the billions of butterflies in the Amazon caused a particular storm? And note, that it is the nature of these systems that changing the butterfly’s position slightly (or changing the position of other butterflies) can result in a completely different outcome (because such systems are highly sensitive to initial conditions). There were many actors in the markets on 6 May, 2010. Attributing the huge change in the system to the behavior of any one individual is clearly impossible. As a matter of theory, yes, it is possible that given the state of the system on 6 May that activity that Sarao undertook with no adverse consequences on myriad other days caused the market to crash on that particular day when it didn’t on other days: it is metaphysically impossible to prove it. The very nature of emergent orders makes it impossible to reverse engineer the cause out of the effect.

A few additional points.

I continue to be deeply disturbed by the “sample days” concept employed in the complaints and in Hendershott’s analysis. This smacks of cherry picking. Even if one uses a sample, it should be a random one. And yeah, right, it just so happened that the Flash Crash day and the two preceding days turned up in a random sample. Pure chance! This further feeds suspicions of cherry picking, and opportunistic and sensationalist cherry picking at that.

Further, Hendershott (in paragraph 22 of his affidavit) asserts that there was a statistically significant price decline after Sarao turned on the algorithm, and a statistically significant price increase when he turned it off. But he presents no numbers, whereas he does report impacts of non-Sarao-specific activity elsewhere in the affidavit. This is highly suspicious. Is he too embarrassed to report the magnitude? This is a major omission, because it is the impact of Sarao’s activity, not offering away from the market generally, that is at issue here.

Relatedly, why not run a VAR (and the associated IRF) using Sarao’s orders as one of the variables? After all, this is the variable of interest: what we want to know is how Sarao’s orders affected prices. Hendershott is implicitly imposing a restriction, namely, that Sarao’s orders have the same impact as other orders at the same level of the book. But that is testable.

Moreover, Hendershott’s concluding paragraph (paragraph 23) is incredibly weak, and smacks of post hoc, ergo propter hoc reasoning. He insinuates that Sarao contributed to the Crash, but oddly distances himself from responsibility for the claim, throwing it on regulators instead: “The layering algorithm contributed to the overall Order Book imbalances and market conditions that the regulators say led to the liquidity deterioration prior to the Flash Crash.” Uhm, Terrence, you are the expert here: it is incumbent on you to demonstrate that connection, using rigorous empirical methods.

In sum, the criminal and civil complaints make a Matterhorn out of a molehill, and a small molehill at that. And don’t take my word for it: take the “[declaration] under penalty of perjury” of the CFTC’s expert. This is a matter of magnitudes, and magnitudes matter. The CFTC’s own expert estimates very small impacts, and impacts that oscillate up and down with the activation and de-activation of the algorithm.

Yes, Sarao’s conduct was dodgy, clearly, and there is a colorable case that he did engage in spoofing and layering. But the disparity between the impact of his conduct as estimated by the government’s own expert and the legal consequences that could arise from his prosecution is so huge as to be outrageous.

Particularly so since over the years CFTC has responded to acts that have caused huge price distortions, and inflicted losses in nine and ten figures, with all of the situational awareness of Helen Keller. It is as if the enforcers see the world through a fun house mirror that grotesquely magnifies some things, and microscopically shrinks others.

In proceeding as they have, DOJ and the CFTC have set off a feeding frenzy that could have huge regulatory and political impacts that affect the exchanges, the markets, and all market participants. CFTC’s new anti-manipulation authority permits it to sanction reckless conduct. If it was held to that standard, the Sarao prosecution would earn it a long stretch of hard time.

*Hendershott’s affidavit says that Exhibit 4 reports the IRF analysis, but it does not.

 

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April 22, 2015

Spoofing: Scalping Steroids?

Filed under: Derivatives,Economics,Exchanges,HFT,Regulation — The Professor @ 5:35 pm

The complaint against Sarao contains some interesting details. In particular, it reports his profits and quantities traded for nine days.

First, quantities bought and sold are almost always equal. That is characteristic of a scalper.

Second, for six of the days, he earned an average of .63 ticks per round turn. That is about profit that you’d expect a scalper to realize. Due to adverse selection, a market maker typically doesn’t earn the full quoted spread.  On only one of these days is the average profit per round turn more than a tick, and then just barely.

Third, there is one day (4 August, 2011) where he earned a whopping 19.6 ticks per round trip ($4 million profit on 16695 buy/sells). I find that hard to believe.

Fourth, there are two days that the government reports the profit but not the volume. One of these days is 6 May, 2010, the Flash Crash day. I find that omission highly suspicious, given that this is the most important day.

Fifth, I again find it odd, and potentially problematic for the government, that it charges him with fraud, manipulation, and spoofing on only 9 days when he allegedly used the layering strategy on about 250 days. How did the government establish that trading on some days was illegal, and on other days it wasn’t?

The most logical explanation of all this is that Sarao was basically scalping-market making-and if he spoofed, he did so to enhance the profitability of this activity, either by scaring off competition at the inside market, or inducing a greater flow of market orders, or both.

One implication of this is that scalping does not tend to cause prices to move one direction or the other. It is passive, and balances buys and sells. This will present great difficulties in pursuing the manipulation charges, though not the spoofing charges and perhaps not the fraud charges.

 

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Did Spoofing Cause the Flash Crash? Not So Fast!

Filed under: Derivatives,Economics,HFT,Regulation — The Professor @ 12:41 pm

The United States has filed criminal charges against on Navinder Sarao, of London, for manipulation via “spoofing” (in the form of “layering”) and “flashing.” The most attention-grabbing aspect of the complaint is that Sarao engaged in this activity on 6 May, 2010-the day of the Flash Crash. Journalists have run wild with this allegation, concluding that he caused the Crash.

Sarao’s layering strategy involved placement of sell orders at various levels more than two ticks away from the best offer. At his request, “Trading Software Company #1″ (I am dying to know who that would be) created an algorithm implemented in a spreadsheet that would cancel these orders if the inside market got close to these resting offers, and replace them with new orders multiple levels away from the new inside market. The algorithm would also cancel orders if the depth in the book at better prices fell below a certain level. Similarly, if the market moved away from his resting orders, those orders would be cancelled and reenetered at the designated distances from the new inside market level.

The complaint is mystifying on the issue of how Sarao made money (allegedly $40 million dollars between 2010 and 2014). To make money, you need to buy low, sell high (you read it here first!), which requires actual transactions. And although the complaint details how many contracts Sarao traded and how many trades (e.g., 10682 buys totaling 74380 lots and 8959 sells totaling 74380 lots on 5 May, 2010-big numbers), it doesn’t say how the trades were executed and what Sarao’s execution strategy was.

The complaint goes into great detail regarding the allegedly fraudulent orders that were never executed, it is maddeningly vague on the trades that were. It says only:

[W]hile the dynamic layering technique exerted downward pressure on the market SARAO typically executed a series of trades to exploit his own manipulative activity by repeatedly selling futures  only to buy them back at a slightly lower price. Conversely, when the market mved back upward as a result of SARAO’s ceasing the dynamic layering technique, SARAO typically did the opposite, that is he repeatedly bought contracts only to sell them at a slightly higher price.

But how were these buys and sells executed? Market orders? Limit orders? Since crossing the spread is expensive, I seriously doubt he used market orders: even if the strategy drove down both bids and offers, using aggressive orders would have forced Sarao to pay the spread, making it impossible to profit. What was the sequence? The complaint suggests that he sold (bought) after driving the price down (up). This seems weird: it would make more sense to do the reverse.

In previous cases, Moncada and Coscia (well-summarized here), the scheme allegedly worked by placing limit orders on both sides of the market in unbalanced quantities, and see-sawing back and forth. For instance, the schemers would allegedly place a small buy order at the prevailing bid, and then put big away from the market orders on the offer side. Once the schemer’s bid was hit, the contra side orders would be cancelled, and he would then switch sides: entering a sell order at the inside market and large away-from-market buys. This strategy is best seen as a way of earning the spread. Presumably its intent is to increase the likelihood of execution of the at-the-market order by using the big contra orders to induce others with orders at the inside market to cancel or reprice. This allowed the alleged manipulators to earn the spread more often than they would have without using this “artifice.”

But we don’t have that detail in Sarao. The complaint does describe the “flashing” strategy in similar terms as in Moncada and Coscia, (i.e., entering limit orders on both sides of the market) but it does not describe the execution strategy in the layering scheme, which the complaint calls “the most prominent manipulative technique he used.”

If, as I conjecture, he was using something like Moncada and Coscia were alleged to have employed, it is difficult to see how his activities would have caused prices to move systematically one direction or the other as the government alleges. Aggressive orders tend to move the market, and if my conjecture is correct, Sarao was using passive orders. Further, he was buying and selling in almost (and sometimes exactly) equal quantities. Trading involving lots of cancellations plus trades in equal quantities at the bid and offer shares similarities with classic market making strategies. This should not move price systematically one way or the other.

But both with regards to the Flash Crash, and 4 May, 2010, the complaint insinuates that Sarao moved the price down:

As the graph displays, SARAO successfully modified nearly all of his orders to stay between levels 4 and 7 of the sell side of the order book. What is more, Exhibit A shows the overall decline in the market price of the E-Minis during this period.

But on 4 May, Sarao bought and sold the exact same number of contracts (65,015). How did that cause price to decline?

Attributing the Flash Crash to his activity is also highly problematic. It smacks of post hoc, ergo propter hoc reasoning. Or look at it this way. The complaint alleges that Sarao employed the layering strategy about 250 days, meaning that he caused 250 out of the last one flash crashes. I can see the defense strategy. When the government expert is on the stand, the defense will go through every day. “You claim Sarao used layering on this day, correct?” “Yes.” “There was no Flash Crash on that day, was there?” “No.” Repeating this 250 times will make the causal connection between his trading and Flash Clash seem very problematic, at best. Yes, perhaps the market was unduly vulnerable to dislocation in response to layering on 6 May, 2010, and hence his strategy might have been the straw that broke the camels back, but that is a very, very, very hard case to make given the very complex conditions on that day.

There is also the issue of who this conduct harmed. Presumably HFTs were the target. But how did it harm them? If my conjecture about the strategy is correct, it increased the odds that Sarao earned the spread, and reduced the odds that HFTs earned the spread. Alternatively, it might have induced some people (HFTs, or others) to submit market orders that they wouldn’t have submitted otherwise. Further, HFT strategies are dynamic, and HFTs learn. One puzzle is why away from the market orders would be considered informative, particularly if they are used frequently in a fraudulent way (i.e., they do not communicate any information). HFTs mine huge amounts of data to detect patterns. The complaint alleges Sarao engaged in a pronounced pattern of trading that certainly HFTs would have picked up, especially since allegations of layering have been around ever since the markets went electronic. This makes it likely that there was a natural self-correcting mechanism that would tend to undermine the profitability of any manipulative strategy.

There are also some interesting legal issues. The government charges Sarao under the pre-Dodd-Frank Section 7 (anti-manipulation) of the Commodity Exchange Act. Proving this manipulation claim requires proof of price artificiality, causation, and intent. The customized software might make the intent easy to prove in this case. But price artificiality and causation will be real challenges, particularly if Sarao’s strategy was similar to Moncada’s and Coscia’s. Proving causation in the Flash Crash will be particularly challenging, given the complex circumstances of that day, and the fact that the government has already laid the blame elsewhere, namely on the Wardell-Reed trades. Causation and artificiality arguments will also be difficult to make given that the government is charging him only for a handful of days that he used the strategy. One suspects some cherry-picking. Then, of course, there is the issue of whether the statute is Constitutionally vague. Coscia recently lost on that issue, but Radley won on it in Houston. It’s an open question.

I am less familiar with Section 18 fraud claims, or the burden of proof regarding them. Even under my conjecture, it is plausible that HFTs were defrauded from earning the spread, or that some traders paid the spread on trades they wouldn’t have made. But if causation is an element here, there will be challenges. It will require showing how HFTs (or other limit order traders) responded to the spoofing. That won’t be easy, especially since HFTs are unlikely to want to reveal their algorithms.

The spoofing charge is based on the post-Frankendodd CEA, with its lower burden of proof (recklessness not intent, and no necessity of proving an artificial price). That will be easier for the government to make stick. That gives the government considerable leverage. But it is largely unexplored territory: this is almost a case of first impression, or at least it is proceeding in parallel with other cases based on this claim, and so there are no precedents.

There are other issues here, including most notably the role of CME and the CFTC. I will cover those in a future post. Suffice it to say that this will be a complex and challenging case going forward, and the government is going to have to do a lot more explaining before it is possible to understand exactly what Sarao did and the impact he had.

 

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