The Data Foundation for Alpha - How fragmented data is eroding hedge fund performance

The hidden cost of fragmented data in hedge fund alpha generation

Alpha depends on more than models, talent and execution. It depends on the quality, consistency and timeliness of the data behind every investment decision.

Many hedge funds still operate with fragmented datasets, inconsistent identifiers and manual reconciliation processes that slow research, distort signals and increase operational risk. As firms scale across strategies, regions and asset classes, poor data is no longer just an operational challenge, it is a performance issue.

At the same time, AI-driven research workflows, systematic strategies and faster investment cycles all require clean, validated, point-in-time accurate data from the start. When data foundations are weak, the impact can be seen in unreliable signals, flawed backtests, duplicated effort and missed opportunities.

Join senior hedge fund practitioners, quantitative leaders and data experts as they discuss what a modern data foundation for alpha generation should look like, and what firms should expect from their data partners in 2026.

Expert speakers:

Matthew Bell - Senior Data Scientist - Man Group
Renato Guerrieri - Head of Quantitative Strategy - Liquid Alternatives - Downing
Kirsty Joss - Head of Distribution Support & Feeds - Product - FE fundinfo
Moderator: Mike O'Hara - Editor, TradingTech Insight - A-Team Group

What you'll learn:

- How fragmented data can reduce alpha potential and distort risk decisions
- Why point-in-time accuracy is critical for backtesting and model performance
- Best practices for data validation, governance and lineage at scale
- How leading hedge funds are modernising their data operating model
- Where firms are getting the build vs buy decision wrong
- What hedge funds should expect from data providers in 2026
- How AI is changing the future of data quality and investment research

Who should watch

Designed for senior professionals at hedge funds and quantitative investment firms, including Heads of Data, Data Engineers, Quantitative Researchers, Data Scientists, CTOs, Heads of Technology, Portfolio Managers, Heads of Trading, Operations Leaders and vendor management professionals responsible for data sourcing and validation.