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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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Institutions Are Already in Prediction Markets – As Data Consumers, Not Traders

The framing around institutional prediction markets assumes a gap that needs bridging: the markets exist, institutions are circling, and what stands between them is a stretch of missing infrastructure – clearing, margin, prime brokerage and surveillance. Build the scaffolding, the assumption runs, and the institutions follow. A panel at A-Team Group’s recent TradingTech Summit New...

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AI in Data Management Summit New York City

Following the success of the 15th Data Management Summit NYC, A-Team Group are excited to announce our new event: AI in Data Management Summit NYC!

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...