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Nonparametric estimation of general multivariate tail dependence and applications to financial time series

Salazar, Yuri and Ng, Wing Lon (2015) 'Nonparametric estimation of general multivariate tail dependence and applications to financial time series.' Statistical Methods & Applications, 24 (1). pp. 121-158. ISSN 1618-2510

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Abstract

In order to analyse the entire tail dependence structure among random variables in a multidimensional setting, we present and study several nonparametric estimators of general tail dependence functions. These estimators measure tail dependence in different orthants, complementing the commonly studied positive (lower and upper) tail dependence. This approach is in line with the parametric analysis of general tail dependence. Under this unifying approach the different dependencies are analysed using the associated copulas. We generalise estimators of the lower and upper tail dependence coefficient to the general multivariate tail dependence function and study their statistical properties. Tail dependence measures come as a response to the incapability of the correlation coefficient as an extreme dependence measure. We run a Monte Carlo simulation study to assess the performance of the nonparametric estimators. We also employ selected estimators in two empirical applications to detect and measure the general multivariate non-positive tail dependence in financial data, which popular parametric copula models commonly applied in the financial literature fail to capture.

Item Type: Article
Uncontrolled Keywords: Tail dependence Copula Nonparametric estimation Financial asset returns
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HG Finance
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of > Centre for Computational Finance and Economic Agents
Depositing User: Jim Jamieson
Date Deposited: 09 Jul 2015 12:26
Last Modified: 09 Jul 2015 12:26
URI: http://repository.essex.ac.uk/id/eprint/14060

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