See the video below on how in-memory technology from ScaleOut Software can boost MapReduce 40x for financial applications, such as real-time risk analytics.
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See the video below on how in-memory technology from ScaleOut Software can boost MapReduce 40x for financial applications, such as real-time risk analytics.
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...
Institutional market data has long been associated with complex licensing, specialist infrastructure and lengthy procurement processes. Much of that complexity is unavoidable: exchange data can be technically demanding, commercially restricted and costly to distribute at scale. However, the expectation around how that data should be accessed is changing. As financial firms become more accustomed to...
A-Team Group’s Digital Assets & Tokenisation Briefing assembles an exclusive group of CxOs and senior technology innovators. These leading market practitioners and infrastructure providers are collectively building the digital rails and decentralised networks that will power Wall Street 2.0.
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...