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Time-varying extreme value dependence with application to leading European stock markets. (English) Zbl 1393.62024

Summary: 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.

MSC:

62G32 Statistics of extreme values; tail inference
62G05 Nonparametric estimation
62H12 Estimation in multivariate analysis
62P05 Applications of statistics to actuarial sciences and financial mathematics
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