In this paper, we propose a new fuzzy clustering of time series with entropy regularization. Following a model-based approach, the dissimilarity measure is based on the bivariate lower tail dependence coefficients estimated for each pair of assets using a copula function. We apply the clustering procedure to the time series of price returns of the assets composing the Dow Jones Sustainability Europe Index and to the time series of 23 Morgan Stanley Capital International (MSCI) Developed Markets indices. We identify the classification structures according to the value selected for the exponent which enters the Fuzzy Silhouette index formula.

Tail dependence-based fuzzy clustering of financial time series

Zuccolotto, Paola
2023-01-01

Abstract

In this paper, we propose a new fuzzy clustering of time series with entropy regularization. Following a model-based approach, the dissimilarity measure is based on the bivariate lower tail dependence coefficients estimated for each pair of assets using a copula function. We apply the clustering procedure to the time series of price returns of the assets composing the Dow Jones Sustainability Europe Index and to the time series of 23 Morgan Stanley Capital International (MSCI) Developed Markets indices. We identify the classification structures according to the value selected for the exponent which enters the Fuzzy Silhouette index formula.
2023
Ateneo di appartenenza
PE1_14 Statistics
PE1_13 Probability
Esperti anonimi
Inglese
Internazionale
Fuzzy clustering, Partitioning around medoids, Copula functions, Tail dependence, Time series, Financial returns, Dow Jones Sustainability Europe Index, Entropy regularization
no
Not applicable
4
info:eu-repo/semantics/article
262
D'Urso, Pierpaolo; De Luca, Giovanni; Vitale, Vincenzina; Zuccolotto, Paola
1 Contributo su Rivista::1.1 Articolo in rivista
none
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/615086
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