Using ESG scores in equity issuer clustering
C. Geissler. CES Sorbonne Seminar on Financial Modelling, Maison des Sciences Economiques, 24 May 2022.
Abstract: The Centre d’Economie de la Sorbonne is organizing monthly research seminars around financial modelling. Today, Christophe Geissler will present an original application of the non-negative matrix factorization (NMF) method, for the case of extra-financial ESG data. These data are subject to high correlations between co-variables, as well as between observations. NMF provides a more easily interpretable clustering of co-variables and observations than a simple principal component analysis (PCA). It gives rise to a natural issuer clustering based on the ESG scores.