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March 2018 Time-varying extreme value dependence with application to leading European stock markets
Daniela Castro-Camilo, Miguel de Carvalho, Jennifer Wadsworth
Ann. Appl. Stat. 12(1): 283-309 (March 2018). DOI: 10.1214/17-AOAS1089

Abstract

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.

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Daniela Castro-Camilo. Miguel de Carvalho. Jennifer Wadsworth. "Time-varying extreme value dependence with application to leading European stock markets." Ann. Appl. Stat. 12 (1) 283 - 309, March 2018. https://doi.org/10.1214/17-AOAS1089

Information

Received: 1 March 2017; Revised: 1 June 2017; Published: March 2018
First available in Project Euclid: 9 March 2018

zbMATH: 06894707
MathSciNet: MR3773394
Digital Object Identifier: 10.1214/17-AOAS1089

Keywords: Angular measure , bivariate extreme values , European stock market integration , risk , statistics of extremes

Rights: Copyright © 2018 Institute of Mathematical Statistics

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Vol.12 • No. 1 • March 2018
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