Description
Financial institutions submit data on their credit portfolios to regulators. An individual institution can be identified with a distribution that is representative of its respective credit portfolio. We are interested in finding representative clusters of financial institutions based on the notion of Wasserstein barycenter. A particular challenge arises from missing data since financial institutions are subject to different regulatory requirements. This leads us to establish a form of the k-means clustering algorithm in Wasserstein space which can deal with missing coordinates.
This is based on joint work with Julio Backhoff and Mathias Beiglböck.
Primary authors
Julio Backhoff
(University of Vienna)
Mathias Beiglböck
(University of Vienna)
Lorenz Riess
(University of Vienna)