Algorithms For Everybody Else

June 2005

Pragma Financial Systems wants to bring algorithms to the common man.

Pragma Financial Systems wants to bring algorithms to the common man. A five-man vendor based in New York, Pragma is marketing algorithmic trading software to broker-dealers and money managers. Today control of most algorithms is in the hands of a select few bulge-bracket shops. "The smaller broker dealers don't have the algorithms that the banks have," says Lee Maclin, a Pragma partner, "and their clients are going to the banks which are delivering the service cheaply. So, they feel pressure to implement it."

Pragma is not the only organization marketing algorithms to brokers. However, it is possibly the only vendor with a purely algorithmic trading product. Two big banks Credit Suisse First Boston and Banc of America Securities offer their trading technology to other brokers. One vendor FlexTrade Systems is building algorithmic trading functionality into its portfolio trading system.

Brokers without proprietary algorithmic trading infrastructures are opting for third party offerings. Both CIBC World Markets and Knight Capital Group, for instance, offer third party algorithms to their clients under so-called "white-label" agreements.

CIBC and Knight affix their brands to the services. The source of the technology need not be disclosed. CIBC gets its algorithms from Banc of America. Knight would not disclose its supplier.

Pragmatic POV

Pragma is targeting the buyside as well as the sellside. For the buyside, its plan is to license the technology. For the sellside, it may price on a transaction basis, according to Maclin. To that end, Pragma is in the process of establishing a broker-dealer.

Pragma's technology has been in production for about a year. A Pragma customer is "one of the largest users of algorithms on the Street," Maclin says, although he won't disclose the name. The firm has integrated its system with those of direct access suppliers Neovest and Lime Brokerage.

'The whole concept excited me right away.'

Lee Maclin, Pragma Financial Systems

Pragma was established in 2002 by Maclin, who is also a professor of mathematics at New York University's Courant Institute, and David Mechner, a quant trader at a hedge fund called Pragma. The technology was spun out of the hedge fund, which has since been closed. Pragma, as does its competitors, claims its technology is better than the rest. Underlying the software is a more "rigorously intellectual" framework, according to Mechner. The two founders based their work on the seminal paper "Optimal Execution of Portfolio Transactions." It was published in the Journal of Risk in 2000 by mathematicians Neill Chriss and Robert Almgren. Their work aimed to determine the best way to liquidate a basket of securities. It set the stage for the development of the arrival price algorithm, now gaining favor on Wall Street. "The whole concept excited me right away," said Maclin, who once taught alongside Neil Chriss at NYU. "I saw this as a continuation of portfolio theory." The arrival price algorithm, one of a handful pushed by the Street's largest brokers, is relatively new. Not all brokers have it. Those that do include CSFB, Morgan Stanley, Deutsche Bank and Merrill Lynch. Arrival Price Best? Pragma's technology lets users choose any algorithm they want. However, Pragma execs maintain traders are best served using arrival price rather than a VWAP or TWAP, for instance. "Everyone is crawling towards this solution phase," says Maclin of arrival price, "but very slowly. The systems they must mutate over time are so complex that the operational risk of suddenly having clients trade in a very computing intensive environment is very great. So they are moving very slowly." At the heart of Almgren and Chriss' paper is a formula that encapsulates what most traders know through experience and intuition: If you trade quickly, you will likely incur market impact. If you trade more slowly, you will incur less market impact, but more risk and possibly opportunity cost. Therefore, the optimal trading strategy is one that minimizes the expected cost and risk of a trade. In mathematical terms, that's "min E (x) + V (x)". E (x) is expected cost. V (x) is risk. Lambda, or , represents the trader's tolerance for risk. The calculation determines a trading trajectory, or schedule, that specifies how many shares should be bought or sold over a pre-determined time period. The shape of the trajectory will vary depending on the trader's lambda, or tolerance for risk.