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

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    Type
    Article
    Authors
    Castro, Daniela
    de Carvalho, Miguel cc
    Wadsworth, Jennifer
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Date
    2018-03-09
    Online Publication Date
    2018-03-09
    Print Publication Date
    2018-03
    Permanent link to this record
    http://hdl.handle.net/10754/627548
    
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    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.
    Citation
    Castro-Camilo D, de Carvalho M, Wadsworth J (2018) Time-varying extreme value dependence with application to leading European stock markets. The Annals of Applied Statistics 12: 283–309. Available: http://dx.doi.org/10.1214/17-AOAS1089.
    Sponsors
    We thank the Editor, Associate Editor, and two anonymous referees. We extend our thanks to António Rua, Vanda Inácio de Carvalho, and Claudia Wehrhahn for helpful discussions. Part of this work was written while D. Castro-Camilo was visiting the University of Cambridge—Statistical Laboratory, and while M. de Carvalho was visiting Banco de Portugal. Supported in part by Fundação para a Ciência e a Tecnologia, through UID/MAT/00006/2013 and by the Chilean National Science Foundation through Fondecyt 11121186, “Constrained Inference Problems in Extreme Value Modeling”.
    Publisher
    Institute of Mathematical Statistics
    Journal
    The Annals of Applied Statistics
    DOI
    10.1214/17-AOAS1089
    arXiv
    1709.01198
    Additional Links
    https://projecteuclid.org/euclid.aoas/1520564473
    ae974a485f413a2113503eed53cd6c53
    10.1214/17-AOAS1089
    Scopus Count
    Collections
    Articles; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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