Separating Skill from Exposure

A Data-Driven Framework for Manager Evaluation

Active management continues to evolve, and performance evaluation is evolving with it. Allocators today are better equipped than ever to understand what truly drives returns and to assess the value of active versus passive strategies.

This paper introduces a data-driven framework that integrates data, clustering, and automated factor analysis, leveraging data from Morningstar, eVestment, and quantitative investment strategy (QIS) universes. By emphasizing the underlying sources of performance rather than headline results, the framework provides allocators with a consistent, objective foundation for evaluating managers, benchmarking peers, and identifying where lasting value is genuinely being created.

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