Gulpinar, Nalan and Katata, Kabir (2014) Modelling oil and gas supply disruption risks using extreme-value theory and copula. Journal of Applied Statistics, Volume 41 (Number 1). pp. 2-25. doi:10.1080/02664763.2013.827160 ISSN 0266-4763.

Research output not available from this repository.

Request-a-Copy directly from author or use local Library Get it For Me service.

Request Changes to record.

Abstract

In this paper, we are concerned with modelling oil and gas supply disruption risks using extreme-value theory and copula. We analyse financial and volumetric losses due to both oil and gas supply disruptions and investigate their dependence structure using real data. In order to illustrate the impact of crude oil and natural gas supply disruptions on an energy-dependent economy, Nigeria is considered as a case study. Computational studies illustrate that the generalized extreme-value distribution anticipates higher financial losses and extreme-value copulas produce the best fit for financial and volumetric losses compared with normal copulas. Moreover, multivariate financial losses exhibit stronger positive dependence than volumetric losses.

Item Type:	Journal Article
Divisions:	Faculty of Social Sciences > Warwick Business School > Operational Research & Management Sciences Faculty of Social Sciences > Warwick Business School
Journal or Publication Title:	Journal of Applied Statistics
Publisher:	Routledge
ISSN:	0266-4763
Official Date:	January 2014
Dates:	Date Event January 2014 Published 6 September 2013 Available 17 July 2013 Accepted 26 March 2013 Submitted
Volume:	Volume 41
Number:	Number 1
Page Range:	pp. 2-25
DOI:	10.1080/02664763.2013.827160
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access

Request changes or add full text files to a record

Repository staff actions (login required)

View Item