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.