Building More Resilient Portfolios Through Model Diversity

In this interview, Alejandro Rodriguez Dominguez discusses how traditional approaches to portfolio construction can be reimagined by treating assets as hypotheses within a structured predictive framework. By establishing a formal connection between diversity in predictive models and portfolio-level risk diversification, he highlights how institutions can better control risk outcomes before optimisation even begins.

He also explores the practical implications of this approach for both quantitative teams and risk practitioners, including improved robustness, stronger performance under stress, and greater alignment between modelling techniques and real-world risk management objectives. The discussion offers a forward-looking perspective on how model-driven portfolio design can evolve in increasingly complex market environments.