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...
The most consequential changes facing financial markets technology in 2026 will not be driven by new asset classes or incremental latency gains, but by a fundamental rethinking of how trading systems are architected at their core. For decades, market participants have organised technology around functional silos: execution, risk, middle office, post-trade. These boundaries were reinforced...
Now in its 15th year the Data Management Summit NYC brings together the North American 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...
