Dynamic Nonlinear Correlation Studies on Stock and Oil Market Based on Copula
He Xin1, *, Zhang Guofu2
Identifiers and Pagination:Year: 2015
First Page: 405
Last Page: 409
Publisher Id: TOPEJ-8-405
Article History:Received Date: 26/5/2015
Revision Received Date: 14/7/2015
Acceptance Date: 10/8/2015
Electronic publication date: 15/9/2015
Collection year: 2015
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Employing the dataset of WTI oil spot price and stock price index in China，Brazil, India, US, German, France, UK and Japan, this paper obtains five subintervals of whole sample range through a nonparametric multiple change point algorithms. Furthermore, it analyzes dependence between oil spot price and stock price index through copula model and computes the value of VaR and ES based on simulation for every subinterval. It reveals that dependence between oil spot price and stock price index during financial crisis is an asymmetric tail dependence. The value of VaR and ES of the oil spot price and stock price index shows irregular fluctuation.