The ground on which market participants walk is shifting from a foundation of latency and performance concerns to a playing field where being proactive is their best asset, according to trading technology experts who spoke in a webinar hosted by Intelligent Trading Technology on June 1.
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 infrastructure can take months and absorb significant budget before a single model is tested. At the...
Trading infrastructure modernisation is no longer being driven solely by latency reduction or cost efficiency. The stronger message emerging across the industry is that firms are having to prepare for markets that are increasingly global, extended-hour, automated and operationally unforgiving. That was the central takeaway from a panel discussion at A-Team Group’s recent TradingTech Summit...
Now in its 16th year, the Data Management Summit (DMS) in London brings together the European capital markets enterprise data management community, to explore how data strategy is evolving to drive business outcomes and speed to market in changing times.
AI adoption in capital markets has moved into a more disciplined phase. The priority is now controlled deployment: where AI can be used safely, where it can deliver measurable value, and how outputs can be governed, monitored and evidenced. The 2026 edition of the AI in Capital Markets Handbook examines how AI is being applied...
