2017/09/04 by Daniela Castro Camilo, Daniela Castro‐Camilo, Camilo, Daniela Castro +5
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) #q-fin.ST
paper · pdf · doi:10.48550/arxiv.1709.01198
23 pages
openalex publication_date 2017/09/04 · arxiv created 2017/09/05 · arxiv updated 2017/09/06 · openalex created_date 2022/09/20 · openalex updated_date 2026/07/28
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.