2017/09/04 by Daniela Castro‐Camilo, Miguel de Carvalho, Camilo, Daniela Castro +3
Economics, Econometrics and Finance · #Complex Systems and Time Series Analysis #FOS: Economics and business #Financial Risk and Volatility Modeling #Market Dynamics and Volatility #Statistical Finance (q-fin.ST)
paper · pdf · doi:10.48550/arxiv.1709.01198
openalex publication_date 2017/09/04 · openalex created_date 2022/09/20 · openalex updated_date 2026/07/28
Extremal dependence between international stock markets is of particular\ninterest in today's global financial landscape. However, previous studies have\nshown this dependence is not necessarily stationary over time. We concern\nourselves with modeling extreme value dependence when that dependence is\nchanging over time, or other suitable covariate. Working within a framework of\nasymptotic dependence, we introduce a regression model for the angular density\nof a bivariate extreme value distribution that allows us to assess how extremal\ndependence evolves over a covariate. We apply the proposed model to assess the\ndynamics governing extremal dependence of some leading European stock markets\nover the last three decades, and find evidence of an increase in extremal\ndependence over recent years.\n