Case Study: Banque Cantonale Vaudoise achieves faster financial analysis and reduced development time with MathWorks (MATLAB)

Battelle Neural Banque Cantonale Vaudoise Speeds Financial Analysis TasksTechnology Restores Movement To A Paralyzed Man’s Arm And Hand

Banque Cantonale Vaudoise (BCV) needed a way to cluster equity industrial indices so analysts could group assets with similar yield fluctuations and manage a large investment universe more efficiently (for example, reducing review from 40+ indices to about nine clustered indices). The Top-Down Research team required software with flexible clustering parameters and integrated validation tools, and selected MathWorks’ MATLAB with Financial Toolbox, Optimization Toolbox, and Statistics and Machine Learning Toolbox to meet that need.

MathWorks’ MATLAB enabled BCV to import Excel data, run cluster analysis and dendrogram visualizations, validate clusters with mean‑variance criteria, and distribute results via Excel Link on a quarterly basis. The solution cut development time dramatically (development with MATLAB was roughly 10× faster than recreating the system in Fortran), supported fast large‑scale minimizations, increased project throughput, and produced actionable clustered indices for portfolio construction and investment policy.

Banque Cantonale Vaudoise

Pierre-Yves Boillat

Quantitative Analyst