Clustering financial data using Copula-GARCH model in an application for main market stock returns

Beata Basiura; Anna Czapkiewicz

doi:https://doi.org/10.59170/stattrans-2010-002

Clustering financial data using Copula-GARCH model in an application for main market stock returns

Beata Basiura Faculty of Management, AGH University of Science and Technology, Krakow, Poland , Anna Czapkiewicz Faculty of Management, AGH University of Science and Technology, Krakow, Poland Statistics in Transition new series, vol. 11, 2010, 1, pages: 25-45 Published online: 1 July 2010 https://doi.org/10.59170/stattrans-2010-002

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ABSTRACT

There are many statistical techniques that allow us to find similarities among variables. Cluster analysis discovers structure within sets of data. The choice of a relevant metric is a fundamental problem in the case of clustering financial data. In this paper, the Copula–GARCH model is used to obtain the dependency parameter between time series. The dissimilarity measure based on the maximum likelihood parameter obtained from the Normal or t-Student copula is proposed and applied to classify forty two indices from American, European, and Asian stock markets.

KEYWORDS

Clustering stock indices, dependence parameter, Copula–GARCH model, Copula function, Skewed distribution

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