We propose a clustering method for large dimensional data to classify the 365 largest euro area financial institutions according to their business model. The proposed clustering approach is applied to granular supervisory data on banks’ activities and combines also dimensionality reduction and outlier detection. We identify four business models, namely wholesale funded, securities holding, traditional commercial and complex commercial banks while identifying as outliers the banks that follow idiosyncratic business models. Evidence is provided that the sets of banks following the distinct business models differ with respect to performance and risk indicators.

Farne', M., Vouldis, A.T. (2021). Banks’ business models in the euro area: a cluster analysis in high dimensions. ANNALS OF OPERATIONS RESEARCH, 305(1-2 (October)), 23-57 [10.1007/s10479-021-04045-9].

Banks’ business models in the euro area: a cluster analysis in high dimensions

Matteo Farnè.
;
2021

Abstract

We propose a clustering method for large dimensional data to classify the 365 largest euro area financial institutions according to their business model. The proposed clustering approach is applied to granular supervisory data on banks’ activities and combines also dimensionality reduction and outlier detection. We identify four business models, namely wholesale funded, securities holding, traditional commercial and complex commercial banks while identifying as outliers the banks that follow idiosyncratic business models. Evidence is provided that the sets of banks following the distinct business models differ with respect to performance and risk indicators.
2021
Farne', M., Vouldis, A.T. (2021). Banks’ business models in the euro area: a cluster analysis in high dimensions. ANNALS OF OPERATIONS RESEARCH, 305(1-2 (October)), 23-57 [10.1007/s10479-021-04045-9].
Farne', Matteo; Vouldis, A. T.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/848481
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