Beyond the surface: The science and strategy of modern Risk Factor Modeling

Join Clearwater for an educational panel discussion into the “what, why, and how” of modern risk factor modeling with practitioners and executives in the world of investment management.

This event is hosted by PRMIA (Professional Risk Managers’​ International Association).

Key topics include:

• Why do we need factor models — How factor models provide estimation stability, reduce correlation errors through diversification, and deliver the economic intuition needed for effective risk management and portfolio construction.
• Types of risk factor models — The key distinctions among cross-sectional, time-series, statistical, and hybrid models, including when each approach is most appropriate for different investment strategies.
• Risk models vs. alpha models — The theoretical and practical boundaries between risk and alpha frameworks, where they overlap, and how leading practitioners integrate both into portfolio construction and stock selection.
• Data quality and model effectiveness — The critical relationship between data types, sources, and quality and how input integrity directly shapes the reliability of risk factor and stock selection models — especially in the AI era.
• The future of factor modeling — How emerging technologies including AI and machine learning are likely to reshape risk factor research, development, and application — from custom models built on the fly to non-linear factor approaches.