About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Portware AI System Growth Leading To ‘Bionic’ Trading

Subscribe to our newsletter

Building on the expansion of its Alpha Pro artificial intelligence agent for trading, begun in November, trade execution management system (EMS) provider Portware is moving toward what its CEO, Alfred Eskandar, calls a “bionic trading desk.”

From March 2009 to March 2017, Portware’s Alpha Pro technology has delivered 133 basis points in return on micro cap stocks, 63 basis points on small cap stocks and 17 basis points on large cap stocks that it has handled.

Over that eight-year period, Alpha Pro, as an AI-enabled algorithmic trading management solution, has handled $168 billion in notional value traded. The volume and returns have been achieved through a combination of AI and human action, Eskandar explains.

“Developments will ultimately lead us to a trading blotter partly managed by computer and partly by the human trader,” he says. “What’s most valuable is when machines inform traders ad traders use their experience to make an even more optimal decision. All-machine is not ready and all-human is not fast enough. But the combination of the two dissecting the blotter into the parts that are best fit to the various combinations of human and machine handing, is proven to give firms tremendous competitive advantage.”

The improvements to Alpha Pro and Portware’s Enterprise EMS which contains Alpha Pro help firms cope with accelerated market activity. “Traders need to consume, digest, analyse and spit out decisions at a much faster rate,” says Eskandar. “That can’t be done without machine-enabled workflows. … We want this to be very accessible to asset managers and all their brokers.”

Along with handling greater amounts of trading and trade-related activity, Portware’s improvements have also made it possible to automate trading of more assets under management, according to Eskandar. “You can double, triple or quadruple the size of assets and not need more technology or have to hire more people,” he says. “Users benefit from a scalable solution that gives more bandwidth to the people they have on the desk already.”

Subscribe to our newsletter

Related content

WEBINAR

Upcoming Webinar: Navigating the Build vs Buy Dilemma: Cloud Strategies for Accelerating Quantitative Research

Date: 20 May 2026 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes For many quantitative trading firms and asset managers, building a self-provisioned historical market data environment remains one of the most time-consuming and resource-intensive steps in establishing a new research capability. Sourcing data, normalising symbologies, handling corporate actions and maintaining...

BLOG

Exegy Acquires NovaSparks to Accelerate Convergence at the FPGA Layer

Exegy, the low-latency market data, trading, and execution technology provider, has agreed to acquire NovaSparks Inc., the specialist in Field Programmable Gate Array (FPGA) enabled market data and trading products. Exegy’s move to bring NovaSparks into the group signals a clear intent to exert deeper control over the FPGA-driven market data pipeline, from normalisation and...

EVENT

Buy AND Build: The Future of Capital Markets Technology

Buy AND Build: The Future of Capital Markets Technology London examines the latest changes and innovations in trading technology and explores how technology is being deployed to create an edge in sell side and buy side capital markets financial institutions.

GUIDE

Connecting to Today’s Fast Markets

At the same time, the growth of high frequency and event-driven trading techniques is spurring demand for direct feed services sourced from exchanges and other trading venues, including alternative trading systems and multilateral trading facilities. Handling these high-speed data feeds its presenting market data managers and their infrastructure teams with a challenge: how to manage...