Pragma Securities has attracted widespread attention over the years due to its flagship offering, Pragma 360, an algorithmic trading platform for foreign exchange (FX), North American equities and futures.
Through continuous innovation, the New York-based firm has consistently enhanced the platform’s capabilities based on the needs of its clients and the shifting market landscape. Those efforts have borne fruit this year as it takes home the award for the best smart-order routing product/tool at the SST Awards.
Much of the success of Pragma 360 over the past year is down to the evolution of its trading solutions in response to regulation in the shape of the revised Markets in Financial Instruments Directive (Mifid II), which came into force on January 3. As compliance dominated the industry’s objectives over the last year, the spotlight fell on banks and brokers to meet best-execution requirements. As pressure mounted on sell-side firms, Pragma 360 stood out among its competitors by offering intelligent and customizable algorithmic trading solutions with smart-order routing capabilities, enabling firms to make better informed trading decisions, achieve best execution, provide greater transparency to their clients, and track order data. “The drivers for the adoption of Pragma 360 are ultimately the need to achieve best execution and to be able to demonstrate best execution from quantitative analysis, where you can look at multiple orders and show that given the market conditions you’ve got, you know you’re getting a good sale on average and good execution results,” says David Mechner, CEO of Pragma Securities.
Pragma prides itself on its talented quantitative team of PhDs who specialize in algorithmic and analytical services and have a deep understanding of multi-asset market structures. This quant team is the brainwork behind Pragma 360’s ability to leverage machine learning to track orders and fit models using real-life historical events and market information. Machine learning is an emerging technology in trading, used to analyze and “learn” from historical events in an effort to better predict where orders should be made. “An important part of our offering is the tools that look historically at all of the trade data that’s generated off the Pragma 360 trading engine,” says Mechner. “That entails accumulating that into a database, lining it up with the historical market data, and presenting an analysis to our customers for them to provide to their customers and show that indeed we’re performing very well.”
Bloomberg’s Gerard Francis looks at the challenges that capital markets firms face when trying to incorporate alternative datasets.Subscribe to Weekly Wrap emails