Extreme value analysis for financial risk management

N Nolde, Chen Zhou

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)

Abstract

This article reviews methods from extreme value analysis with applications to risk assessment in finance. It covers three main methodological paradigms: the classical framework for independent and identically distributed data with application to risk estimation for market and operational loss data, the multivariate framework for cross-sectional dependent data with application to systemic risk, and the methods for stationary serially dependent data applied to dynamic risk management. The article is addressed to statisticians with interest and possibly experience in financial risk management who are not familiar with extreme value analysis.

Original languageEnglish
Pages (from-to)217-240
Number of pages24
JournalAnnual Review of Statistics and Its Application
Volume8
DOIs
Publication statusPublished - 7 Mar 2021

Bibliographical note

Publisher Copyright:
© 2021 Annual Reviews Inc.. All rights reserved.

Fingerprint

Dive into the research topics of 'Extreme value analysis for financial risk management'. Together they form a unique fingerprint.

Cite this