Clustering of financial time series in risky scenarios

Fabrizio Durante (), Roberta Pappadà () and Nicola Torelli ()

Advances in Data Analysis and Classification, 2014, vol. 8, issue 4, 359-376

Abstract: A methodology is presented for clustering financial time series according to the association in the tail of their distribution. The procedure is based on the calculation of suitable pairwise conditional Spearman’s correlation coefficients extracted from the series. The performance of the method has been tested via a simulation study. As an illustration, an analysis of the components of the Italian FTSE–MIB is presented. The results could be applied to construct financial portfolios that can manage to reduce the risk in case of simultaneous large losses in several markets. Copyright Springer-Verlag Berlin Heidelberg 2014

Keywords: Cluster analysis; Copula; Spearman’s correlation; Tail dependence; 62H30; 62H20; 62M10 (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (14)

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DOI: 10.1007/s11634-013-0160-4

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