Telling tales from the tails: High-dimensional tail interdependence

Arnold Polanski, Evarist Stoja, Frank Windmeijer

Research output: Contribution to journalArticle (Academic Journal)peer-review

1 Citation (Scopus)

Abstract

We propose a simple and flexible framework that allows for a comprehensive analysis of tail interdependence in high dimensions. We use co-exceedances to capture the structure of the dependence in the tails and, relying on the concept of multiinformation, define the coefficient of tail interdependence. Within this framework, we develop statistical tests of (i) independence in the tails, (ii) goodness-of-fit of the tail interdependence structure of a hypothesized model with the one observed in the data, and (iii) dependence symmetry between any two tails. We present an analysis of tail interdependence among 250 constituents of the SP250 index.
Original languageEnglish
Pages (from-to)779-794
Number of pages16
JournalJournal of Applied Econometrics
Volume34
Issue number5
Early online date22 May 2019
DOIs
Publication statusPublished - 1 Aug 2019

Structured keywords

  • ECON Econometrics
  • AF Financial Markets
  • ECON CEPS Data

Fingerprint Dive into the research topics of 'Telling tales from the tails: High-dimensional tail interdependence'. Together they form a unique fingerprint.

Cite this