Abstract
Multidimensional scaling is an exploratory statistical technique which is widely used for detecting structures in multivariate data. Unfortunately, it relies on a single distance matrix. We propose an extension of multidimensional scaling to several distance matrices which is particularly useful when the latter are roughly proportional to each other. We apply the proposed method to several balance sheet ratios collected from Italian banks. The main empirical finding is that the two major banks are very different from each other and from smaller banks, which are clustered together. It contributes to the current debate on dimension as stabililizer of the banking system.
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Berti, A., Loperfido, N. (2018). An Extension of Multidimensional Scaling to Several Distance Matrices, and Its Application to the Italian Banking Sector. In: Corazza, M., Durbán, M., Grané, A., Perna, C., Sibillo, M. (eds) Mathematical and Statistical Methods for Actuarial Sciences and Finance. Springer, Cham. https://doi.org/10.1007/978-3-319-89824-7_25
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DOI: https://doi.org/10.1007/978-3-319-89824-7_25
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