Clustering of financial time series in risky scenarios View Full Text


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Article Info

DATE

2013-12-22

AUTHORS

Fabrizio Durante, Roberta Pappadà, Nicola Torelli

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. More... »

PAGES

359-376

References to SciGraph publications

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s11634-013-0160-4

    DOI

    http://dx.doi.org/10.1007/s11634-013-0160-4

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1040088698


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    165 rdf:type schema:Organization
    166 grid-institutes:grid.5608.b schema:alternateName Department of Statistical Sciences, University of Padua, Via Cesare Battisti 241, 35121, Padova, Italy
    167 schema:name Department of Statistical Sciences, University of Padua, Via Cesare Battisti 241, 35121, Padova, Italy
    168 rdf:type schema:Organization
     




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