“It’s almost a central nervous system for dark pools,” says Lee Maclin, director of research at Pragma, a financial engineering firm that partnered with Weeden & Co., the agency broker, back in April to develop and distribution execution products.

Currently the system is in beta testing with buy-side clients and has access to 25 passive liquidity sources, but that number will grow to over 30 when the system officially launches on Jan. 1st, according to Doug Rivelli, managing director at Weeden Co., the institutional agency broker based in Greenwich, Conn.

Instead of needing direct connectivity to 30 separate dark pools, this allows a buy-side client “to send their order through a single point on their OMS and have their order managed in an intelligent manner within all the passive sources that we have available to us,” says Rivelli. On the operations side, it’s efficient in that the client will clear all the executions with those destinations through a single ticket with Weeden.

Orders will be allocated among the dark pools based on both historical analysis of each of the venues as well as real-time information on what’s transpiring in each venue, says Rivelli. “It’s important to understand that no venue gains preference over any other venue for another reason except for quality,” says Rivelli. For instance, OnePipe will not consider how much each venue is charging it to access their liquidity. “It’s a very pure methodology or algorithm that’s designed to maximize the liquidity experience of our customers,” adds Rivelli.

Weeden and Pragma say they are addressing a problem that has its historical roots in the shrinking order side of equity trades, which explains why the dark pools came about. In 1998, the average size of a trade in IBM was 1,400 shares; in 2006 it was 400 shares and this year it’s 250 shares. As these orders get smaller in the public markets, Maclin says, “The electronic open markets make it hard for people that have large orders to execute them without giving away a lot of information.” An explosion in the number of dark pools came about to help traders protect the information content in their large orders. “The problem is now that here are so many of them, we’re getting liquidity fragmentation,” says Maclin.

However, “what institutions should not do is simply choose the most liquid destination and send all of your orders there. When you actually look at the mathematics that is not optimal,” warns Maclin. “There is a complex analysis that should take place,” insists Maclin. This starts with analysis of all the historical liquidity in each dark pool but also encompasses knowing the rules that are particular to each liquidity pool, such as minimum times for staying in the pool and minimum order sizes. In addition to knowing the historical crossing rates of each network, the system takes in all the real-time information and is able to direct orders to where customers are getting executed.

Comparing the liquidity management system to an air traffic controller, that is aware of where all the planes are at any one point in time and knows how to optimize the runway space, Maclin says, OnePipe “has more information than any one customer and it’s taking in this information to direct the customer to the best liquidity.” For example, if there is a buy order that hasn’t been executed in a dark pool, it knows the order imbalance is a sell order.

OnePipe can also benefit the destination and the clients, notes Peter Fraenkel, Pragma’s director of quantitative services. If both orders come through OnePipe, it can direct the sell order to the destination where the buy-order is waiting, he says. One Pipe can connect to an unlimited number of destinations, including the smallest dark pools, notes Fraenkel. While buy-side firms may not bother connecting to small liquidity pools, Rivelli points that the information is valuable.

Since One Pipe has more information available to it than any one customer or individual crossing network, both firms expect that the overall combined crossing rates would be higher than any of the constituent networks. Weeden’s Rivelli says he’s targeting crossing rates in the mid 20 percent rage, where typically crossing rates are around 8-to-10 percent.

Although both firms declined to name which liquidity pools they’re accessing due to contractual agreements with each of the venues, they said they were connected to broker dealer liquidity pools, some traditional crossing networks and streaming liquidity networks. They’re also looking to create some unique liquidity pools that are only accessible to OnePipe clients. As an example, they're talking to some retail firms about creating a retail flow pool that might be able to wash up against OnePipe, says Rivelli.

Looking ahead, Pragma and Weeden say this is only the beginning. They plan to connect OnePipe to their suite of algorithmic trading strategies, so that if an order is not getting crossed, the buy-side can optimally trade-out using algorithms. “If it wasn’t finding liquidity in OnePipe, it could expose the order to the market algorithmically,” says Rivelli. This is possible because underneath the OnePipe infrastructure is TradeEngine, a real-time high frequency algorithmic trading platform that Weeden and Pragma have been deploying for several years. “In general we’re talking about not just the ability to use the OnePipe as a destination, but to layer algorithms on top of it and to make even more intelligent use of the liquidity sources,” says Fraenkel.