Pragma, an independent, multi-asset class algorithmic trading technology provider, has enhanced its deep-learning enabled execution algorithms to intelligently trade Canadian and US interlisted equities.

Pragma launched Mercury, its deep neural network-based execution engine, in 2021 after a multi-year research and development effort, and a year of controlled production trading trials with its clients. Mercury’s deep neural network microtrading engine controls the routing, sizing, pricing and timing of orders, and has shown a robust improvement in execution quality, with an average shortfall improvement ranging from 33% to 50% across billions of traded shares.
 
Support for Canadian and interlisted equity trading is a natural extension of Pragma’s deep learning capabilities. Leveraging its high-quality simulator, a decade of experience in trading interlisted equities, and an additional year of research to extend the neural-network model to the problem of interlisted trading, Pragma clients can now access more intelligent execution algorithms for Canadian and interlisted equities. Through Panorama, Pragma’s algorithmic management system, clients can also view customised A/B experiments with the new Mercury algorithms on a real-time basis.