03.06.2015

Shining A Light on Orders

03.06.2015
Terry Flanagan

The prominence of dark pools and high-frequency trading has elevated the need for fine-grained analysis of order-routing strategies to offset the informational disadvantage the buy side sometimes faces vis-a-vis the sell side.

“In the typical principal-agent relationship, the agent always knows more than the principal,” said Matthew Celebuski, CEO of Trade Informatics, a provider of transaction cost analysis and execution services. “The broker knows where things trade. Maybe they did a cross on an order that might have gotten the mid-price somewhere else, but the client will never know that.”

Trade Informatics recently launched TI Fact, a routing analysis technology that it says eliminates the agency information advantage, thereby leveling the field for buy-side institutions and asset managers by assisting clients in spotting and reacting to predatory market practices.

“What Fact does is it goes in and rebuilds the market conditions on every single execution and every single route,” Celebuski said. “We’ve modeled all these dark pools, so we know what their latencies are and we’ll find that print on the tape, and then we’ll know what were the true market conditions at the time that the order took place.”

Trade Informatics has been using TI Fact internally for several years with its Strategic & Tactical Analytics Research and Trading, a broker-neutral set of trading engines that aims to ‘disintermediate’ buy-side trading desks from brokers.

“We look at our own models trading from the client site: which dark pools do well, which lit venues do well, which order types are good, what do broker smart order routers do to you, and it’s all millisecond-level analysis,” Celebuski said. “We have used it to improve our trading process.”

With the publication of Michael Lewis’ Flash Boys, Trade Informatics observed a spike in interest in routing analysis, and decided to commercialize the product. “Since the book, it’s gotten a lot of legs because people want that insurance,” said Celebuski.

Prior to forming Trade Informatics, Celebuski headed a quantitative trading group at Bear Stearns called Equity Analytics and Systematic Trading. “We ran the specialist book on the floor of the New York Stock Exchange in 385 names, anything to do with computers and trading,” he said. “We set everything up, starting in 2004, to be very quantitative, so everything had a formula next to it. We knew what the computers were actually doing, and we put in place a performance monitoring process where every decision of every model was saved. We’d analyze that decision overnight, was it a good decision or a bad decision, and try to get trading better for the next day.”

Toward the end of Celebuski’s tenure at Bear, “we started taking that light and shining it on customer orders,” he said. “We evaluated every trade of every month, every sales trader every month and every client of every month. We found stuff in the client data, just like when we were looking at our own data where we were trying to make money, where we could go to the client and say, “Hey, you know what? Your costs were 30 basis points last month. We think they could be 15.’”

That operation eventually became Trade Informatics.

“We monitor tick data on about 125,000 securities around the world,” Celebuski said. “We have terabytes and terabytes of data and high-end econometric models that we merge with the data to come up with some way to make trading cheaper. We can go back over years of data and say, ‘This is how you traded. However, had you traded these other ways, you could have saved X basis points.’”

Featured image by alswart/Dollar Photo Club

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