Copula-Based Clustering of Financial Time Series via Evidence Accumulation
Applications
2025-10-08 v1
Abstract
Understanding the dependence structure of asset returns is fundamental in risk assessment and is particularly relevant in a portfolio diversification strategy. We propose a clustering approach where evidence accumulated in a multiplicity of classifications is achieved using classical hierarchical procedures and multiple copula-based dissimilarity measures. Assets that are grouped in the same cluster are such that their stochastic behavior is similar during risky scenarios, and riskaverse investors could exploit this information to build a risk-diversified portfolio. An empirical demonstration of such a strategy is presented by using data from the EURO STOXX 50 index.
Keywords
Cite
@article{arxiv.2510.05960,
title = {Copula-Based Clustering of Financial Time Series via Evidence Accumulation},
author = {Andrea Mecchina and Roberta Pappadà and Nicola Torelli},
journal= {arXiv preprint arXiv:2510.05960},
year = {2025}
}