capitalmarketsciooutlook

Pragma Securities: The Quantitative Trading Technology Experts

CIO VendorCurtis Pfeiffer, Chief Business Officer
It is yet another normal day at the headquarters of Pragma Securities. Curtis Pfeiffer, the Chief Business Officer of Pragma is expecting an executive visit from one of the largest global banks. “They have been receiving requests from their clients to deliver an algorithmic offering and after reviewing whether to build in-house or use another vendor, they have chosen Pragma,” exalts Pfeiffer. The bank has indeed considered various factors—other in-house projects, go-to-market timelines, the effort involved— before deciding to collaborate with Pragma. And after all these evaluations, it has been a no-brainer for them to choose Pragma. Not only will the company provide them with quality, control, and transparency through their solution, they would also deliver the solution in three months, which would be anywhere from 12-24 months if the decision had been to develop the solution internally. “We know how to support an institutional grade algorithmic trading service as well as how to provide a high performing execution experience which is difficult to replicate. We leverage this know-how to help clients establish and grow their algorithmic trading businesses,” says Pfeiffer. No wonder the firm handles billions of dollars a day for its clients across multiple asset classes—FX, equities and futures.

Founded in 2003, with an aim to be the algorithmic trading technology leader, Pragma provides highly customized algorithmic trading tools to its clients, which enables them to go to the market with an algorithmic trading solution in much less time, and with a high-grade, institutionally accepted service. The company’s primary offering, Pragma360 has several components associated with it. While it incorporates an execution algorithmic suite that offers different algorithms such as schedule-based along with liquidity sourcing strategies to the clients, it also provides various trade support tools. One of these tools is Panorama—a real-time algorithmic management system—which allows clients to view the algorithmic orders as they execute, including which venues the orders execute in.


We know how to support an institutional grade algorithmic trading service as well as how to provide a high performing execution experience which is difficult to replicate. We leverage this know-how to help clients establish and grow their algorithmic trading businesses


Panorama also provides real-time updates on trading performance vs. common TCA benchmarks. “Clients can also modify orders, which allows them a high degree of control in order to better serve their end clients,” mentions Pfeiffer.

One of the most important features of Pragma’s offering is the transaction cost analysis. “We store their trading data and provide them with a web portal called Trade Reports that enables clients to look historically at the performance of the trade versus the trading benchmark,” explains Pfeiffer. They can also conduct venue analysis to compare and observe the venues where their orders were executed and the variety of characteristics that were considered. Further, Pragma also offers services for Spot FX and Non-Deliverable Forwards (NDFs) and can support futures algorithms, which makes it a multi-asset class provider of algorithmic trading technology.

According to Pfeiffer, Pragma’s institutional knowledge along with the value proposition it creates by operating as a vendor steers them ahead of the competition. They don’t trade proprietarily and never internalized order flow, which keeps Pragma aligned with their clients as they don’t have a secondary revenue stream to protect. The company’s expertise in market microstructure, trading, and using algorithms allows them to deliver a high-performing product. Having carved a unique niche in the quantitative trading technology space, Pragma aims to continue providing intelligence that connects traders to the marketplace. “We are always looking for ways to further help our clients grow their businesses, whether that is leveraging new machine learning techniques for the algorithms, expanding across different asset classes, geographies, or improving the trade support tools,” concludes Pfeiffer.