Traders have long associated adverse selection in dark pools with block executions. A trader typically considers himself âadversely selectedâ when the stock moves in his favor immediately after he executes a block in a dark pool. This historical incidence of adverse selection was easy to measure and detect; the trader simply compared his execution price to the closing price or the price a few hours later. Moreover, adverse selection in dark pools did not occur systematically in the past; over the long run, high-performing trades often washed away poorly-performing ones. Today, however, our research demonstrates that adverse selection occurs systematically in many dark pools and the nature of it is very different. It transpires over much shorter time periodsâ over seconds or minutes rather than hours. As such, it may not attract a traderâs attention, but the accumulating effect of small adverse fills over the longer-term performance of a large parent order can be considerable. Todayâs adverse selection is a result of the shift in dark pool composition. Pools that once excluded high-frequency trading participants have now opened their gates and as a result, experienced explosive volume growth. Although high-frequency trading firms play an important role in displayed markets by tightening the spreads, they are often the cause of short-term adverse selection in dark pools. And, due to the overwhelming participation level of high-frequency trading firms in dark pools, adverse selection is occurring much more frequently to the detriment of buyside participants. In this paper, our goal is to educate buyside dark pool participants on the negative effects adverse selection can have on performance and to provide an effective method for measuring it over the short-term and long-term. We begin by demonstrating the direct cause and effect relationship between adverse selection and Implementation Shortfall. We then present our own extended Implementation Shortfall measurement framework. This method is suitable for measuring the performance of dark pools as well as dark pool aggregators and it captures the effects of both short-term and long-term adverse selection. Most importantly, we end with a discussion of various liquidity filtration techniques that can help traders avoid adverse selection in dark pools. Understanding and Avoiding Adverse Selection in Dark Pools November 2009 © http://www.itg.com/news_events/papers/AdverseSelectionDarkPools_113009F.pdf
I hope those reading this understand that this "paper" is a marketing piece for ITG's own dark pools. Essentially, they are advocating "darker" dark pools that only the big buyside players can access. While there may or may not be some true merit to this for big buyside players, order flow routed to this venue can never be touched by non-institutional, small-time traders such as those who typically inhabit ET.
True! I am not opposed to darkness, per se; in fact, I think it would be more fair if institution-exclusive dark pools were forced to be completely dark; e.g., no IOI's, which I see as something like quotes available only to an exclusive group. But I see internalization as a far worse type of dark -- one in which the B/D, which is supposed to be representing the client, could potentially use the client's information to the B/D's own advantage, vis-a-vis their client and the market as a whole. As such, I think it's unfair and contributes significantly to pricing inefficiency.