BearingPoint

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

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...

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Where Should Trading Firms Spend Their Latency Budget?

The pursuit of lower latency in electronic trading hasn’t disappeared, but the engineering decisions behind it are becoming more selective. Rather than trying to make every component of the trading stack as fast as possible, firms need to determine where microseconds genuinely affect trading outcomes, where predictable performance matters more than absolute speed, and where...

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TradingTech Summit London

Now in its 16th year, the TradingTech Summit London brings together senior leadership across capital markets trading technology and market data. Join us to deep dive into key opportunities and challenges driving technological transformation across sell-side and buy-side firms.

AI in Capital Markets Handbook 2026

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...