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:

• Chris Kelliher, Portfolio Manager, Multi-Asset Systematic Strategies at Fidelity Investments

• Renato Guerrieri, Head of Quantitative Strategy - Liquid Alternatives at Downing

• Mick Hittesdorf, OneTick Senior Cloud Architect at OneTick / KX

• Peter Simpson, OneTick Product Owner at OneTick / KX

• Moderator: Mike O’Hara, Editor at TradingTech Insight

Watch the Recording:

More About OneTick Cloud:

OneTick Cloud provides real-time, intra-day and historic data and analytics on trading activity leading to actionable insights for sales, trading, and surveillance. With hundreds of customers, you know that OneTick is a recognized platform you can trust. We will cover these many powerful advantages to OneTick, and show you how, together, we can meet your business needs.