Streetwise Professor

June 25, 2014

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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June 18, 2014

The For-Profit Exchange Red Herring Are Running Again

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

 

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The Klearing Kool Aid Hangover

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

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

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

Some of their conclusions are worth quoting in detail:

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

Furthermore:

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

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

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

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

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

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April 23, 2014

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

 

 

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April 18, 2014

Stiglitz on HFT

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

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

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

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

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

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

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

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

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

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

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

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

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

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

HFT does not improve the important type of liquidity.

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

HFT also reduces natural liquidity.

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

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

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

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

 

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April 12, 2014

A Serious Question For Brad DeLong

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

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

So here it is:

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

The explanation is more important than the answer.

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Yes, Brad, It’s Just You (And Others Who Oversimplify and Ignore Salient Facts)

Filed under: Derivatives,Economics,Exchanges,HFT,Politics,Regulation,Uncategorized — The Professor @ 2:48 pm

Brad DeLong takes issue with my Predator/Prey HFT post. He criticizes me for not taking a stand on HFT, and for not concluding that HFT should be banned because it is a parasitic. Color me unpersuaded. De Long’s analysis is seriously incomplete, and some of his conclusions are incorrect.

At root, this is a dispute about the social benefits of informed trading. De Long takes the view that there is too little informed trading:

In a “rational” financial market without noise traders in which liquidity, rebalancing, and control/incentive traders can tag their trades, it is impossible to make money via (4). Counterparties to (4) will ask the American question: If this is a good trade for you, how can it be a good trade for me? The answer: it cannot be. And so the economy underestimates in fundamental information, and markets will be inefficient–prices will be away from fundamentals, and so bad real economic decisions will be made based on prices that are not in fact the appropriate Lagrangian-multiplier shadow values–because of free riding on the information contained in informed order flow and visible market prices. [Note to Brad: I quote completely, without extensive ellipses. Pixels are free.]

Free riding on the information in prices leading to underinvestment in information is indeed a potential problem. And I am quite familiar with this issue, thank you very much. I used similar logic in my ’94 JLE paper on self-regulation by exchanges to argue that exchanges may exert too little effort to deter manipulation because they didn’t internalize the benefits of reducing the price distortions caused by corners. My ’92 JLS paper applied this reasoning to an evaluation of exchange rules regarding the disclosure of information about the quantity and quality of grain in store. It’s a legitimate argument.

But it’s not the only argument relating to the incentives to collect information, and the social benefits and costs and private benefits and costs of trading on that information. My post focused on something that De Long ignores altogether, and certainly did not respond to: the possibility that privately informed trading can be rent seeking activity that dissipates resources.

This is not a new idea either. Jack Hirshleifer wrote a famous paper about it over 40 years ago. Hirsleifer emphasizes that trading on information has distributive effects, and that people have an incentive to invest real resources in order to distribute wealth in their direction. The term rent seeking wasn’t even coined then (Ann Kreuger first used it in 1974) but that is exactly what Hirshleifer described.

The example I have in my post is related to such rent seeking behavior. Collecting information that allows a superior forecast of corporate earnings shortly before an announcement can permit profitable trading, but (as in one of Hirshleifer’s examples) does not affect decisions on any margin. The cost of collecting this information is therefore a social waste.

De Long says that the idea that there is too little informed trading “does not seem to me to scan.” If it doesn’t it is because he has ignored important strands of the literature dating back to the early-1970s.

Both the free riding effects and the rent seeking effects of informed trading certainly exist in the real world. Too little of some information is collected, and too much of other types is collected. And that was basically my point: due to the nature of information, true costs and benefits aren’t internalized, and as a result, evaluating the welfare effects of informed trading and things that affect the amount of informed trading is impossible.

One of the things that affects the incentives to engage in informed trading is market microstructure, and in particular the strategies followed by market makers and how those strategies depend on technology, market rules, and regulation. Since many HFT are engaging in market making, HFT affects the incentives surrounding informed trading. My post focused on how HFT reduced adverse selection costs-losses to informed traders-by ferreting out informed order flow. This reduces the losses to informed traders, which is the same as saying it reduces the gains to informed traders. Thus there is less informed trading of all varieties: good, bad, and ugly.

Again the effects of this are equivocal, precisely because the effects of informed trading are equivocal. To the extent that rent seeking informed trading is reduced, any reduction in adverse selection cost is an unmitigated gain. However, even if collection of some decision improving information is eliminated, reducing adverse selection costs has some offsetting benefits. De Long even mentions the sources of the benefits, but doesn’t trace through the logic to the appropriate conclusion.

Specifically, De Long notes that by trading people can improve the allocation of risk and mitigate agency costs. These trades are not undertaken to profit on information, and they are generally welfare-enhancing. By creating adverse selection, informed trading-even trading that improves price informativeness in ways that leads to better real investment decisions-raises the cost of these welfare-improving risk shifting trades. Just as adverse selection in insurance markets leads to under provision of insurance (relative to the first best), adverse selection in equity or derivatives markets leads to a sub optimally small amount of hedging, diversification, etc.

So again, things are complicated. Reducing adverse selection costs through more efficient market making may involve a trade-off between improved risk sharing and better decisions involving investment, etc., because prices are more informative. Contrary to De Long, who denies the existence of such a trade off.

And this was the entire point of my post. That evaluating the welfare effects of market making innovations that mitigate adverse selection is extremely difficult. This shouldn’t be news to a good economist: it has long been known that asymmetric information bedevils welfare analysis in myriad ways.

De Long can reach his anti-HFT conclusion only by concluding that the net social benefits of privately informed trading are positive, and by ignoring the fact that any kind of privately informed trading serves as a tax on beneficial risk sharing transactions. To play turnabout (which is fair!): there is “insufficient proof” for the first proposition. And he is flatly wrong to ignore the second consideration. Indeed, it is rather shocking that he does so.*

Although De Long concludes an HFT ban would be welfare-improving, his arguments are not logically limited to HFT alone. They basically apply to any market making activity. Market makers employ real resources to do things to mitigate adverse selection costs. This reduces the amount of informed trading. In De Long’s world, this is an unmitigated bad.

So, if he is logical De Long should also want to ban all exchanges in which intermediaries make markets. He should also want to ban OTC market making. Locals were bad. Specialists were bad. Dealers were bad. Off with their heads!

Which raises the question: why has every set of institutions for trading financial instruments that has existed everywhere and always had specialized intermediaries who make markets? The burden of proof would seem to be on De Long to demonstrate that such a ubiquitous practice has been able to survive despite its allegedly obvious inefficiencies.

This relates to a point I’ve made time and again. HFT is NOT unique. It is just the manifestation, in a particular technological environment, of economic forces that have expressed/manifested themselves in different ways under different technologies. Everything that HFT firms do-market making, arbitrage activities, and even some predatory actions (e.g., momentum ignition)-have direct analogs in every financial trading system known to mankind. HFT market makers basically put into code what resides in the grey matter of locals on the floor. Arbitrage is arbitrage. Gunning the stops is gunning the stops, regardless of whether it is done on the floor or on a computer.

One implication of this is that even if HFT is banned, it is inevitable-inevitable-that some alternative way of performing the same functions would arise. And this alternative would pose all of the same conundrums and complexities and ambiguities as HFT.

In sum, Brad De Long reaches strong conclusions because he vastly oversimplifies. He ignores that some informed trading is rent seeking, and that there can be a trade-off between more informative prices (and higher adverse selection costs) and risk sharing.

The complexities and trade-offs are exactly why debates over speculation and market structure have been so fierce, and so protracted. There are no easy answers. This isn’t like a debate over tariffs, where answers are much more clean-cut. Welfare analyses are always devilish hard when there is asymmetric information.

Although a free-market guy, I acknowledge such difficulties, even though that means that implies that I know the outcome is not first best. Brad De Long, not a free market guy, well, not so much. So yes, Brad, it is just you-and other people who oversimplify and ignore salient considerations that are present in any set of mechanisms for trading financial instruments, regardless of the technology.

* De Long incorrectly asserts that informed trading cannot occur in the absence of “noise trading,” where from the context De Long defines noise traders as randomizing idiots: “In a ‘rational’ financial market without noise traders in which liquidity, rebalancing, and control/incentive traders can tag their trades, it is impossible to make money via [informed trading].” Noise trading (e.g., in a Kyle model) is a modeling artifice that treats “liquidity, rebalancing and control/incentive” trades-trades that are not information-driven-in a reduced form fashion.  Randomizing idiots don’t trade on information. But neither do rational portfolio diversifiers subject to endowment shocks.

It is possible-and has been done many, many times-to produce a structural model with, say, rebalancing traders subject to random endowment shocks who trade even though they lose systematically to informed traders. (De Long qualifies his statement by referring to traders who can “tag their trades.” No idea what this means. Regardless, completely rational individuals who benefit from trading because it improves their risk exposure (e.g., by permitting diversification) will trade even though they are subject to adverse selection.) They will trade less, however, which is the crucial point, and which is a cost of informed trading, regardless of whether that informed trading improves other decisions, or is purely rent-seeking.

 

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April 5, 2014

Pinging: Who is the Predator, and Who Is the Prey?

Filed under: Economics,Exchanges,HFT,Politics,Regulation — The Professor @ 11:59 am

The debate over Lewis’s Flash Boys is generating more informed commentary than the book itself. One thing that is emerging in the debate is the identity of the main contending parties: HFT vs. the Buy Side, mainly big institutional traders.

One of the criticisms of HFT is that it engages in various strategies to attempt to ferret out institutional order flows, which upsets the buy side. But the issue is not nearly so clearcut as the buy side would have you believe.

The main issue is that not all institutional orders are alike. In particular, there is considerable variation in the informativeness of institutional order flow. Some (e.g., index fund order flow) is unlikely to be informed. Other order flow is more informed: some may even be informed by inside information.

Informed order flow is toxic for market makers. They lose on average when trading against it. So they try to determine what order flow is informed, and what order flow isn’t.

Informed order flow must hide in order to profit on its information. Informed order flow uses various strategies based on order types, order submission strategies, choice of trading venues, etc., to attempt to become indistinguishable from uninformed order flow. Uninformed order flow tries to devise in strategies to signal that it is indeed uninformed, but that encourages the informed traders to alter their strategies to mimic the uninformed.

To the extent that market makers-be they humans or machines-can get signals about the informativeness of order flow, and  in particular about undisclosed flow that may be hitting the market soon, they can adjust their quotes accordingly and mitigate adverse selection problems. The ability to adjust quotes quickly in response to information about pending informed orders allows them to quote narrower markets. By pinging dark pools or engage in other strategies that allow them to make inferences about latent informed order flow, HFT can enhance liquidity.

Informed traders of course are furious at this. They hate being sniffed out and seeing prices change before their latent orders are executed. They excoriate “junk liquidity”-quotes that disappear before they can execute. Because the mitigation of adverse selection reduces the profits they generate from their information.

It can be frustrating for uninformed institutional investors too, because to the extent that HFT can’t distinguish perfectly between uninformed and informed order flow,  the uninformed will often see prices move against them before they trade too.  This creates a commercial opportunity for new trading venues, dark pools, mainly, to devise ways to do a better way of screening out informed order flow.

But even if uninformed order flow often finds quotes running away from them, their trading costs will be lower on average the better that market makers, including HFT, are able to detect more accurately impending informed orders. Pooling equilibria hurt the uninformed: separating equilibria help them. The opposite is true of informed traders. Market makers that can evaluate more accurately the informativeness of order flow induce more separation and less pooling.

Ultimately, then, the driver of this dynamic is the informed traders. They may well be the true predators, and the uninformed (or lesser informed) and the market makers are their prey. The prey attempt to take measures to protect themselves, and ironically are often condemned for it: informed traders’ anger at market makers that anticipate their orders is no different that the anger of a cat that sees the mouse flee before it can pounce. The criticisms of both dark pools and HFT (and particularly HFT strategies that attempt to uncover information about trading interest and impending order flow) are prominent examples.

The welfare impacts of all this are unknown, and likely unknowable. To the extent that HFT or dark pools reduce the returns to informed trading, there will be less investment in the collection of private information. Prices will be less informative, but trading will be less costly and risk allocation improved. The latter effects are beneficial, but hard to quantify. The benefits of more informative prices are impossible to quantify, and the social benefits of more informed prices may be larger, perhaps substantially so, than the private benefits, meaning that excessive resources are devoted to gathering private information.

More informative prices can improve the allocation of capital. But not all improvements in price efficiency improve the allocation of capital by anything near the cost of acquiring the information that results in these improvements, or the costs imposed on uninformed traders due to adverse selection. For instance, developing information that permits a better forecast of a company’s next earnings report may have very little effect on the investment decisions of that company, or any other company. The company has the information already, and other companies for which this information may be valuable (e.g., firms in the same industry, competitors) are going to get it well within their normal decision making cycle.  In this case, incurring costs to acquire the information is a pure waste. No decision is improved, risk allocation is impaired (because those trading for risk allocation reasons bear higher costs), and resources are consumed.

In other words, it is impossible to know how the social benefits of private information about securities values relate to the private benefits. It is quite possible (and in my view, likely) that the private benefits exceed the social benefits. If so, traders who are able to uncover and anticipate informed trading and take measures that reduce the private returns to informed trading are enhancing welfare, even if prices are less informative as a result.

I cannot see any way of evaluating the welfare effects of financial trading, and in particular informed trading. The social benefits (how do more informative prices improve the allocation of real resources) are impossible to quantify: they are often difficult even to identify, except in the most general way (“capital allocation is improved”). Unlike the trade for most goods and services, there is no reason to believe that social and private benefits align. My intuition-and it is no more than that-is that the bulk of informed trading is rent seeking, and a tax on the risk allocation functions of financial markets.

It is therefore at least strongly arguable that the development of trading technologies that reduce the returns to informed trading are a good thing. To the extent that one of the charges against HFT-that it is better able to detect and anticipate (I will not say front-run) informed order flow-is true, that is a feature, not a bug.

I don’t know and I am pretty sure nobody knows or even can know the answers to these questions. Which means that strongly moralistic treatments of HFT or any other financial market technology or structure that affects the returns to informed trading is theology, not economics/finance. Agnosticism is a defensible position. Certitude is not.

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April 2, 2014

Michael Lewis’s HFT Book: More of a Dark Market Than a Lit One

Filed under: Derivatives,Economics,Exchanges,HFT,Politics,Regulation,Uncategorized — The Professor @ 2:35 pm

Michael Lewis’s new book on HFT, Flash Boys, has been released, and has unleashed a huge controversy. Or put more accurately, it has added fuel to a controversy that has been burning for some time.

I have bought the book, but haven’t had time to read it. But I read a variety of accounts of what is in the book, so I can make a few comments based on that.

First, as many have pointed out, although this has been framed as evil computer geniuses taking money from small investors, this isn’t at all the case. If anyone benefits from the tightening of spreads, especially for small trade sizes, it is small investors. Many of them (most, in fact) trade at the bid-ask midpoint via internalization programs with their brokers or through payment-for-order-flow arrangements. (Those raise other issues for another day, but have been around for years and don’t relate directly to HFT.)

Instead, the battle is mainly part of the struggle between large institutional investors and HFT. Large traders want to conceal their trading intentions to avoid price impact. Other traders from time immemorial have attempted to determine those trading intentions, and profit by trading before and against the institutional traders.  Nowadays, some HFT traders attempt to sniff out institutional orders, and profit from that information.  Information about order flow is the lifeblood of those who make markets.

This relates to the second issue. This has been characterized as “front running.” This terminology is problematic in this context. Front running is usually used to describe a broker in an agency relationship with a customer trading in advance of the customer’s order, or disclosing the order to another trader who then trades on that information. This is a violation of the agency relationship between the client and the broker.

In contrast, HFT firms use a variety of means-pinging dark pools, accessing trading and quoting information that is more extensive and obtained more quickly than via the public data feeds-to detect the presence of institutional orders. They are not in an agency relationship with the institution, and have no legal obligation to it.

And this is nothing new. Traders on the floor were always trying to figure out when big orders were coming, and who was submitting them. Sometimes they obtained this information when they shouldn’t have, because a broker violated his obligation. But usually it was from watching what brokers were trading, knowing what brokers served what customers, looking at how anxious the broker appeared, etc.  To throw the floor of the track, big traders would use many brokers. Indeed, one argument for dual trading was that it made it harder for the floor to know the origin of an order if the executing broker dual traded, and might be active because he was trading on his own account rather than for a customer.

This relates too to the third issue: reports that the FBI is investigating for possible criminal violations. Seriously? I remember how the FBI covered itself in glory during the sting on the floors in Chicago in ’89. Not really. The press reports say that the the FBI is investigating whether HFT trades on “non-public information.”  Well, “non-public information” is not necessarily “inside information” which is illegal to trade on:  inside information typically relates to that obtained from someone with a fiduciary duty to shareholders. Indeed, ferreting out non-public information contributes to price discovery: raising the risk of prosecution for trading on information obtained through research or other means, but which is not obtained from someone with a fiduciary relationship to a company, is a dangerous slippery slope that could severely interfere with the operation of the market.

Moreover, it’s not so clear that order flow information is “non-public”.  No, not everyone has it: HFT has to expend resources to get it, but anybody could in theory do that. Anybody can make the investment necessary to ping a dark pool. Anybody can pay to get a faster data feed that allows them to get information that everyone has access to more quickly. Anybody can pay to get quicker access to the data, either through co-location, or the purchase of a private data feed. There is no theft or misappropriation involved. If firms trade on the basis of such information that can be obtained for a price that not everyone is willing to pay, and that is deemed illegal, how would trading on the basis of what’s on a Bloomberg terminal be any different?

Fourth, one reason for the development of dark pools, and the rules that dark pools establish, are to protect order flow information, or to make it less profitable to trade on that information. The heroes of Lewis’s book, the IEX team, specifically designed their system (which is now a dark pool, but which will transition to an ECN and then an exchange in the future) to protect institutional traders against opportunistic HFT. (Note: not all HFT is opportunistic, even if some is.)

That’s great. An example of how technological and institutional innovation can address an economic problem. I would emphasize again that this is not a new issue: just a new institutional response. Once upon a time institutional investors relied on block trading in the upstairs market to prevent information leakage and mitigate price impact. Now they use dark pools. And dark pools are competing to find technologies and rules and protocols that help institutional investors do the same thing.

I also find it very, very ironic that a dark pool is now the big hero in a trading morality tale. Just weeks ago, dark pools were criticized heavily in a Congressional hearing.  They are routinely demonized, especially by the exchanges. The Europeans have slapped very restrictive rules on them in an attempt to constrain the share of trading done in the dark. Which almost certainly will increase institutional trading costs: if institutions could trade more cheaply in the light, they would do so. It will also almost certainly make them more vulnerable to predatory HFT because they will be deprived of the (imperfect) protections that dark pools provide.

Fifth, and perhaps most importantly from a policy perspective, as I’ve written often, much of the problem with HFT in equities is directly the result of the fragmented market structure, which in turn is directly the result of RegNMS. For instance, latency arbitrage based on the slowness of the SIP results from the fact that there is a SIP, and there is a SIP because it is necessary to connect the multiple execution venues. The ability to use trades or quotes on one market to make inferences about institutional trades that might be directed to other markets is also a consequence of fragmentation. As I’ve discussed before, much of the proliferation of order types that Lewis (and others) argue advantage HFT is directly attributable to fragmentation, and rules relating to locked and crossed markets that are also a consequence of RegNMS-driven fragmentation.

Though HFT has spurred some controversy in futures markets, these controversies are quite different, and much less intense. This is due to the fact that many of the problematic features of HFT in equities are the direct consequence of RegNMS and the SEC’s decision (and Congress’s before that) to encourage competition between multiple execution venues.

And as I’ve also said repeatedly, these problems inhere in the nature of financial trading. You have to pick your poison. The old way of doing business, in which order flow was not socialized as in the aftermath of RegNMS, resulted in the domination of a single major execution venue (e.g., the NYSE). And for those with a limited historical memory, please know that these execution venues were owned by their members who adopted rules-rigged the game if you will-that benefited them. They profited accordingly.

Other news from today brings this point home. Goldman is about to sell its NYSE specialist unit, the former Spear, Leeds, which it bought for $6.5 billion (with a B) only 14 years ago.  It is selling it for $30 million (with an M).  That’s a 99.5 decline in market value, folks. Why was the price so high back in 2000? Because under the rules of the time, a monopoly specialist franchise on a near monopoly exchange generated substantial economic rents. Rents that came out of the pockets of investors, including small investors.  Electronic trading, and the socialization of order flow and the resultant competition between execution venues, ruthlessly destroyed those rents.

So it’s not like the markets have moved from a pre-electronic golden age into a technological dystopia where investors are the prey of computerized super-raptors. And although sorting out cause and effect is complicated, the decline in trading costs strongly suggests that the new system, for all its flaws, has been a boon for investors. Until regulators or legislators find the Goldilocks “just right” set of regulations that facilitates competition without the pernicious effects of fragmentation (and in many ways, “fragmentation” is just a synonym for “competition”), we have to choose one or the other. My view is that messy competition is usually preferable to tidy monopoly.

The catch phrase from Lewis’s book is that the markets are rigged. As I tweeted after the 60 Minutes segment on the book, by his definition of rigging, all markets have always been rigged. A group of specialized intermediaries has always exercised substantial influence over the rules and practices of the markets, and has earned rents at the expense of investors. And I daresay it would be foolish to believe this will ever change. My view is that the competition that prevails in current markets has dissipated a lot of those rents (although some of that dissipation has been inefficient, due to arms race effects).

In sum, there doesn’t appear to be a lot new in Lewis’s book. Moreover, the morality tale doesn’t capture the true complexity of the markets generally, or HFT specifically. It has certainly resulted in the release of a lot of heat, but I don’t see a lot of light. Which is kind of fitting for a book in which a dark pool is the hero.

 

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March 24, 2014

The Vertical (Silo) Bop: A Reprise

Filed under: Clearing,Commodities,Derivatives,Economics,Exchanges,Politics,Regulation — The Professor @ 7:26 pm

With all the Ukraine stuff, and Gunvor, and travel, some things got lost in my spindle.  Time to catch up.

One story is this article about a debate between NASDAQ OMX’s Robert Greifeld and CME Group’s Phupinder Gill.  The “vertical silo” in which an exchange owns both an execution venue and a clearinghouse was a matter of contention:

Nasdaq OMX Group Inc. CEO Robert Greifeld was asked yesterday about the vertical silo and whether it hurts investors.

“Monopolies are great if you own one,” he said during a panel discussion at the annual Futures Industry Association conference in Boca Raton, Florida, paraphrasing a quote he recalled hearing from an investor. His exchanges don’t use this system. “We have yet to find a customer who is in favor of the vertical model,” he said.

A very retro topic here on SWP.  I blogged about it quite a bit in 2006-2007.  Despite that, it’s still a misunderstood subject :-P

Presumably Greifeld believes that eliminating the vertical silo would open up competition in execution.  Yes, there would be competition, but the outcome would likely still be a monopoly in execution given the rules in futures markets.  Under current futures market regulations, there is nothing analogous to RegNMS which effectively socializes order flow by requiring each execution venue to direct orders to any other venue displaying a better price.  Under current futures market regulations, there is no linkage between different execution venues, and no obligation to direct orders to a better priced market.  This leads traders to submit orders to the venue that they expect will be offering the best price.   In this environment, liquidity attracts liquidity, and order flow tips exclusively to a single market.

So opening up clearing would still result in a monopoly execution venue.  There would be competition to be the monopoly, but at the end of the day only one market would remain standing.  Most likely the incumbent (CME in most cases, ICE in some others.)

It is precisely the fact that competition in clearing and execution would lead to bilateral monopolies that drives the formation of a vertical silo.  This eliminates double marginalization problems and reduces the transactions costs arising from opportunism and bargaining that are inherent to bilateral monopoly situations.

Breaking up the vertical silo primarily affects who earns the monopoly rent, and in what form. These outcomes depend on how the silo is broken up.

One alternative is to require the integrated exchange to offer access to its clearinghouse on non-discriminatory terms.  In this case, the one monopoly rent theorem implies that the clearing natural monopoly could extract the entire monopoly rent via its clearing fee.  Indeed, it would have an incentive to encourage competition in execution because this would maximize the derived demand for clearing, and hence maximize the monopoly price.  (This would also allow the integrated exchange to be compensated for its investment in the creation of new contracts, a point Gill emphasizes.  In my opinion, this is a minor consideration.)

Another alternative (which seems to be what Greifeld is advocating) would be to create a utility CCP (a la DTCC) that provides clearing services at cost.  In this case, the winning execution venue will capture the monopoly rent.

To a first approximation, market users would pay the same cost to trade under either alternative. And most likely, the dominant incumbent (CME) would capture the monopoly rent, either in execution fees, or clearing fees, or a combination of the two.  Crucially, however, total costs would arguably be higher with the utility clearer-monopoly execution venue setup, due to the transactions costs associated with coordination, bargaining, and opportunism between separate clearing and execution venues.  (Unfortunately, the phrase “transactions costs” does double duty in this context.  There are the costs that traders incur to transact, and the costs of operating and governing the trading and clearing venues.)

A third alternative would be to move to a structure like that in the US equity market, with a utility clearer and a RegNMS-type socialization of order flow.  Which would result in all the integration and fragmentation nightmares that are currently the subject of so much angst in the equity world.  Do we really want to inflict that on the futures markets?

As I’ve written ad nauseum over the years, there is no Nirvana in trading market structure.  You have a choice between inefficiencies arising from monopoly, or inefficiencies arising from fragmentation.   Not an easy choice, and I don’t know the right answer.

What I do know is that the vertical silo per se is not the problem.  The silo is an economizing response to the natural monopoly tendencies in clearing and execution (when there is no obligation to direct order flow to venues displaying better prices).  The sooner we get away from assuming differently (and the Boca debate is yet another example of our failure to do so) the sooner we will have realistic discussions of the real trade-offs in trading market structure.

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