Dark Pools and the Tactical Side of Trading
Momentum trading may become more art than science.
The term "dark pools" refers to pools of trade liquidity – usually bids and offers in considerable size – that are not posted on any publicly available market quote system. Private firms aggregated these questions outside of the exchanges with the hopes they can be crossed by private firms. An article in the January 29, 2007 issue of Advanced Trading provides as good an explanation of this growing phenomenon as I have seen.
Mutual funds and hedgies have long had a problem of having their orders jumped. Let's say a fund wants to buy 100,000 shares of XXYZ, which is currently trading $25 by $25.25. If they float the whole 100,000 into the visible market at $25.25, you can guarantee that ask will be yanked and run to $25.50. If there is demand in size, sellers will seek to run the ask up and make more money.
This "slippage" or "market impact" is a significant cost of doing business for large investors. The larger you are, the larger the impact. Large investors have turned to dark pools where they can display their desired transactions in a manner that reduces slippage. These trades are reported to the "public" markets as a done deal without the size bid/offer ever contributing to the publicly available price discovery process.
Price and Volume
If you have spent any time around technical analysis, you know most indicators are just fancy, visual ways of representing price and volume. Technical analysis is the art of determining where the "big money" is going in an attempt to get there ahead of it, reaping profits along the way.
More sophisticated technical analysis tools recognize not every trade is equal. In theory, a trade of 10,000 shares at $25 represents "smarter money" than a trade of 100 shares at $24.50. A sophisticated technical analysis tool would skew its visual representation (chart pattern) to reflect $25 was a "better" price than $24.50 in terms of predicting future price direction.
Other technical tools analyze where the trade happened in relation to the bid and ask. The idea is that any trade done at the bid represents selling pressure and a trade at the ask represents buying pressure. This type of technical analysis has increased as better data, faster computers, and faster telco lines have enabled the high volume of data throughput necessary to make the calculations in real time.
A few tools combine both approaches, assigning a 10,000-share trade at the ask more importance than a 100-share trade at the bid in terms of anticipating future price direction.
Absent the use of dark pools, big funds have to break their trades up into smaller pieces in an effort to mask their movements and reduce slippage costs. In 1999 and 2000 when everyone quit their jobs to become day traders, the problem of slippage became increasingly serious. I happened to be doing a great deal of technical analysis at the time, and can safely say shrinking average trade sizes affected the accuracy of my tools. There were simply fewer large trades of the kind necessary to detect where the big players were moving. The charts still flowed, but were no longer as reliably predictive.
However, everyone adapts. New tools were developed to deal with divining market direction from more uniform trade flows. The nice thing about Wall Street is there is always money to be found, as long as you are flexible in how you look for it.
Dark Pools and TA
I wonder how the increasing use of dark pools will affect technical analysis? On one hand, you could say restoration of large trades could revitalize some older technical tools and strategies. Instead of having to decipher the meaning of numerous tiny trades, one has more "meaningfully large" trades to generate directional predictions.
On the other hand, I'm guessing dark pools will harm some approaches. For example, a trade in a dark pool probably occurred in a bid/ask environment different from the publicly available bid and ask. What does a technical system based upon where trades occurred within the bid and ask spread do with a trade outside the public spread at the time? Similarly, if the algorithm weights trade as more significant, will that magnify an erroneous assumption that the trade went off at a bid/ask spread comparable to the public spread at the time?
For some of us, these are not idle questions. My firm is developing a product now that mixes volume and bid/ask analysis in order to divine the tactical environment around the 250+/- stocks in our development-stage biotech universe. Figuring out how to handle dark-pool trades within that technical system is a challenge.
Lately, my firm, Biotech Stock Research (BSR), has been writing to clients in some detail about the tactical side of investing. Fundamental analysis, as everyone knows, results in investment decisions based upon verifiable facts uncovered via hours of research and years of experience. While some days I have my doubts, I believe most people would agree fundamental analysis is generally what underlies most investment decisions.
In my view, "tactical trading" is about understanding how the market and its participants operate and what that means to the likely direction of the stock price. Let me illustrate with a few examples.
In 2004, my firm had a situation where we got everything right about a stock we covered, including predicting the outcome of the clinical trial data. But the day those data were reported, the stock was down over 40% because the data were "not positive enough."
The stock price had nothing to do with the data. They were clinically relevant for the stage of the study. It had everything to do with expectations of the holders of the stock. Knowing the fundamentals, therefore, was not enough to avoid the loss. Without knowing the tactical aspect of what everyone else was thinking, our fundamental analysis led us astray.
A second tactical example happened more recently. Repros Therapeutics (RPRX) reported fabulous preliminary data from its clinical trials. These data should have dramatically increased the stock price of this woefully undervalued company. Yes, we saw a pop in the price, but the stock stalled. When this sort of thing happens, people normally start questioning the quality of the data. Because my firm had done our tactical homework, however, we knew that wasn't the issue.
Repros, you see, generally trades by appointment (low daily volume). Management had said for some time they were going to raise money after the interim data were released. Instead of diving into an illiquid market in a manner suggested by the positive fundamental news, the major players were content to sit on the sidelines under the assumption they could get the size they needed from the financing deal.
I did some calling around and quickly figured out there was a bunch more demand than the 2-2.5 mln shares management was willing to float in the deal. People also told me they'd be buying in the open market what they couldn't get in the deal. With that information in hand, it was an easy decision to take the company to overweight in our model portfolio. Tactically, my firm anticipated a run in the stock price as people discovered they weren't going to get all the shares they wanted in the deal. If you pull up a chart of RPRX, you'll see my firm's tactically-driven decision to go overweight was a good one.
A third example is something that happens regularly in BSR's chosen segment of development-stage biotech companies. Out of the blue, short interest will spike and/or the price will move wildly. Because insider trading (the bad kind) is so common in this sector, you simply can't chalk it up to some aberration. Tactically, you're forced to hunt down the cause.
In 2002, my firm was very positive on Esperion, a company developing HDL-raising drugs. One Monday morning, the stock started falling off the face of the Earth. I couldn't figure out what was going on until I got a tip that some hedge funds received early copies of the New England Journal of Medicine. The issue contained a report of a key clinical trial for an Esperion drug. The hedge funds read the article as negative. We at BSR found out about the article on Tuesday and it took us until Wednesday at 3:00 pm to get a fax copy of the article. While the fax was barely readable, we could read enough to know the data were not negative and, in fact, were unprecedented. My firm was able to get the message out to clients to load up at $17.75 ahead of a company post-close conference call. The stock opened Thursday morning above $20. It was bought later that year by Pfizer (PFE) for $35/share.
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