Upcoming Webinar: Navigating the Build vs Buy Dilemma: Cloud Strategies for Accelerating Quantitative Research
Date: 20 May 2026
Time: 10:00am ET / 3:00pm London / 4:00pm CET
Duration: 50 minutes
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 same time, the expectations placed on quant teams are accelerating. Firms need faster time-to-market for new strategies, broader asset class coverage, and the ability to work with granular tick-level and depth-of-book data across hundreds of global venues, all without scaling headcount or infrastructure linearly.
This webinar examines how cloud-delivered, managed market data platforms are reshaping the build-versus-buy decision for quantitative research infrastructure. Our panellists will explore the practical trade-offs, architectural considerations and operational implications of moving from self-built data pipelines to on-demand, pre-normalised data environments.
Discussion topics will include:
- The build-versus-buy calculus for market data infrastructure: Why sourcing, cleaning and maintaining historical data in-house remains costly and slow, and where managed alternatives are gaining traction
- Accelerating quant research workflows: How pre-normalised, API-accessible data environments are enabling researchers to move from onboarding to back testing in days rather than months
- Cloud-native compute for intensive workloads: The operational case for elastic, vendor-managed infrastructure to support burst workloads such as multi-year back tests and stress testing
- Data depth and coverage: The growing demand for granular market data, including full depth of book, market-by-order and consolidated liquidity across global venues, and the infrastructure implications of sourcing and normalising it
- Integration and flexibility: Practical considerations around Python, SQL and REST API access, and how managed platforms fit alongside existing notebooks, pipelines and ML toolchains
This webinar is designed for senior professionals in quantitative research, data engineering, trading technology and infrastructure, including CTOs, heads of quant research, data scientists, portfolio managers, and technology leaders responsible for market data strategy and research platform architecture.
Speakers:
Moderator: Mike O’Hara
Editor, TradingTech Insight
A-Team Group
More about our speakers:
Mick Hittesdorf
OneTick Senior Cloud Architect
OneMarketData / KX
Mick Hittesdorf leads technical architecture product strategy at OneTick, focusing on market data platform modernization, Cloud migration, open standards, data integration and interoperability. Mick also works closely with OneTick’s flagship clients to help them plan, execute and operationalize market data platform Cloud migration and modernization initiatives.
Peter Simpson
OneTick Product Owner
OneMarketData / KX
Peter joined OneTick in 2019, and is responsible for the OneTick Product, ensuring that the platform continues to support customer needs. Prior to his work with OneMarketData, Peter held several senior roles including VP of Product at Datawatch Panopticon, Senior Manager of Analytics at Deloitte UK, and 10 years in various roles at HSBC Global Markets. Peter holds a Master of Science in Information Systems Engineering and a Bachelor of Science in Space Science & Technology, from Leicester University.
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