Time-varying extreme value dependence with application to leading European stock markets

Castro-Camilo, D. , de Carvalho, M. and Wadsworth, J. (2018) Time-varying extreme value dependence with application to leading European stock markets. Annals of Applied Statistics, 12(1), pp. 283-309. (doi: 10.1214/17-AOAS1089)

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Extremal dependence between international stock markets is of particular interest in today’s global financial landscape. However, previous studies have shown this dependence is not necessarily stationary over time. We concern ourselves with modeling extreme value dependence when that dependence is changing over time, or other suitable covariate. Working within a framework of asymptotic dependence, we introduce a regression model for the angular density of a bivariate extreme value distribution that allows us to assess how extremal dependence evolves over a covariate. We apply the proposed model to assess the dynamics governing extremal dependence of some leading European stock markets over the last three decades, and find evidence of an increase in extremal dependence over recent years.

Item Type:Articles
Keywords:Angular measure, bivariate extreme values, European stock market, integration risk, statistics of extremes.
Glasgow Author(s) Enlighten ID:Castro-Camilo, Dr Daniela
Authors: Castro-Camilo, D., de Carvalho, M., and Wadsworth, J.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Annals of Applied Statistics
Publisher:Institute of Mathematical Statistics
ISSN (Online):1941-7330
Published Online:09 March 2018
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