Work

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

Year: 2018

Type: article

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.

Source: The Annals of Applied Statistics

DOI: 10.1214/17-aoas1089

Authors: Daniela Castro-Camilo, Miguel de Carvalho, Jennifer Wadsworth

Institutions: Lancaster University, University of Edinburgh

Language: English

Topic: Financial Risk and Volatility Modeling

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: bronze

Funders: National Science Foundation, University of Cambridge, Fundação para a Ciência e a Tecnologia

Award: Centro de Estatística e Aplicações