Case Study: Robeco accelerates quantitative stock selection and portfolio optimization with MathWorks (MATLAB)

Robeco Develops Quantitative Stock Selection and Portfolio Optimization Models

Robeco, one of Europe’s leading asset managers and a Rabobank subsidiary, needed a proven computational platform to develop, distribute, and maintain quantitative stock‑selection and portfolio‑optimization tools that spreadsheets and inflexible commercial packages couldn’t support. To address this challenge Robeco turned to MathWorks, using MATLAB together with MATLAB Compiler SDK and Optimization Toolbox to build and deploy its models.

Using MathWorks' MATLAB, MATLAB Compiler SDK and Optimization Toolbox, Robeco’s Quantitative Strategies group developed back‑testing and modeling environments, converted algorithms into DLLs for integration with Visual Basic applications, and automated portfolio optimization and Monte Carlo risk analyses. The MathWorks solution enabled faster, less error‑prone updates, eliminated black‑box vendor tools, increased scalability and flexibility, and supports roughly €12 billion managed quantitatively with these models.

Robeco

Willem Jellema

Research Analyst