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May 16, 2007

Smart Gets Smarter

By Nina Mehta

For algorithmic providers developing advanced smart order routing, the current Reg NMS-inspired routing complexity in the displayed markets is only exacerbated by the growth of dark liquidity venues and crossing opportunities. To get best execution for clients, brokers must access that liquidity. Dark liquidity refers to orders that are not publicly displayed in trading venues and that cross within the national best bid and offer.

Some two dozen brokers already have algorithms that go to dark pools and use dark order types on public markets to stealthily execute orders. An increasing number of firms enable all or most of their algos to access dark liquidity, whether it's resting in dark pools and ATSs or in hidden orders on exchanges and ECNs.

Goldman says 20 percent of its electronic customer flow is now executed algorithmically through dark order types. Hale notes that almost every Goldman order launched by an algorithm attempts to execute within the NBBO on an exchange or ECN before taking displayed liquidity.

The recent growth of dark order types that cross orders within the inside market is a response to competition from dark pools and an effort to draw liquidity back to the public markets. However, identifying which markets are attracting undisplayed liquidity is hard. Smart order routers cannot simply look at a market's depth of book and analyze tick-level behavior, since those data feeds do not include reserve and hidden orders resting in order books.

To ascertain which markets have executable liquidity, algo providers must work backwards off trade and quote data and try to match it up to instant-by-instant snapshots of various markets' books. This must be done in real time, so that smart order routers can optimize their next-instant routing decisions across a large number of destinations.

Firms that gather and analyze these vast quantities of quote and trade information can search for signs that certain markets may have undisplayed liquidity. That enables them to route orders to those markets more effectively, yielding potentially better executions for customers.

What's unclear is whether the combination of dark liquidity and smart order-routing practices, which are altering the way algorithms route orders to dark and displayed markets, will affect trading behavior more broadly. It is possible, some say, that the presence of dark liquidity, coupled with changes in order placement, could provide new incentives for liquidity to enter the market.

"People use algorithmic spadework to try to take block trades and smooth them out over the course of the day to get into the slipstream of the daily retail flow," says UNX's Rosen. "If people move more into the dark, that will affect market behavior."

Dark liquidity has already changed certain fundamental aspects of algorithmic trading, according to many market participants. Credit Suisse's Mathisson points out that it has altered the fill rates traders can get without displaying orders and has created new ways to trade.

"You can do things you couldn't before, like break an order up and spray out 20 dark orders simultaneously on 20 different destinations," Mathisson says. "Instead of displaying orders, an algo can create a giant hidden net to catch the contra side no matter where it's been routed."