The University of Southampton
University of Southampton Institutional Repository

An Application of Extreme Value Theory for Measuring Financial Risk in BRICS Economies

An Application of Extreme Value Theory for Measuring Financial Risk in BRICS Economies
An Application of Extreme Value Theory for Measuring Financial Risk in BRICS Economies
Characterization and quantification of the tail behaviour of rare events is an important issue in financial risk management. In this paper, the extreme behaviour of stock market returns from BRICS over the period 1995–2015 is described using five parametric distributions based on extreme value theory, including two mixture distributions based on the student’s t distribution. The distributions are fitted to the data using the method of maximum likelihood. The generalized extreme value (GEV) distribution is found to give the best fit. Based on the GEV distribution, estimates of value at risk, VaRp(X) and expected shortfall, ESp(X) from the five countries are computed. In addition, the correlation structure and tail dependence of these markets are characterized using several copula models. The Gumbel copula gives the best fit with evidence of significant relationships for all the pairs of the markets. To account for the possibility that due to sampling variability, a different model might be selected as the preferred model in a new sample from the same population, a short bootstrapping exercise was performed.
2198-5804
Afuecheta, Emmanuel
947cc127-d327-46e5-badd-3c11ed9a87cb
Utazi, Chigozie Edson
97af8901-3d52-46c5-8d16-e68e29057aa6
Ranganai, Edmore
6b9a5533-2aa4-4934-a574-1205f831ec51
Nnanatu, Chibuzor Christopher
24be7c1b-a677-4086-91b4-a9d9b1efa5a3
Afuecheta, Emmanuel
947cc127-d327-46e5-badd-3c11ed9a87cb
Utazi, Chigozie Edson
97af8901-3d52-46c5-8d16-e68e29057aa6
Ranganai, Edmore
6b9a5533-2aa4-4934-a574-1205f831ec51
Nnanatu, Chibuzor Christopher
24be7c1b-a677-4086-91b4-a9d9b1efa5a3

Afuecheta, Emmanuel, Utazi, Chigozie Edson, Ranganai, Edmore and Nnanatu, Chibuzor Christopher (2020) An Application of Extreme Value Theory for Measuring Financial Risk in BRICS Economies. Annals of Data Science. (doi:10.1007/s40745-020-00294-w).

Record type: Article

Abstract

Characterization and quantification of the tail behaviour of rare events is an important issue in financial risk management. In this paper, the extreme behaviour of stock market returns from BRICS over the period 1995–2015 is described using five parametric distributions based on extreme value theory, including two mixture distributions based on the student’s t distribution. The distributions are fitted to the data using the method of maximum likelihood. The generalized extreme value (GEV) distribution is found to give the best fit. Based on the GEV distribution, estimates of value at risk, VaRp(X) and expected shortfall, ESp(X) from the five countries are computed. In addition, the correlation structure and tail dependence of these markets are characterized using several copula models. The Gumbel copula gives the best fit with evidence of significant relationships for all the pairs of the markets. To account for the possibility that due to sampling variability, a different model might be selected as the preferred model in a new sample from the same population, a short bootstrapping exercise was performed.

This record has no associated files available for download.

More information

Published date: 22 June 2020
Additional Information: © 2020, Springer-Verlag GmbH Germany

Identifiers

Local EPrints ID: 458053
URI: http://eprints.soton.ac.uk/id/eprint/458053
ISSN: 2198-5804
PURE UUID: fd61d5b8-8196-4c46-9fe3-128c4c4d7ba6

Catalogue record

Date deposited: 27 Jun 2022 17:09
Last modified: 16 Mar 2024 16:41

Export record

Altmetrics

Contributors

Author: Emmanuel Afuecheta
Author: Chigozie Edson Utazi
Author: Edmore Ranganai
Author: Chibuzor Christopher Nnanatu

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×