RESEARCH ARTICLE


Dynamic Nonlinear Correlation Studies on Stock and Oil Market Based on Copula



He Xin1, *, Zhang Guofu2
1 Department of Information Management, Beijing Institute of Petrochemical Technology, Beijing, 102617, China
2 Department of Information Management, Tianjin University of Science and Technology, Tianjin, 300457, China


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© 2015 Xin and Guofu

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.

* Address correspondence to this author at the Department of information management, Beijing Institute of Petrochemical Technology, Beijing, 102617, China; Tel: +86 10 52489515; Fax: +86 10 58850501-1987; E-mail: hexin@bipt.edu.cn


Abstract

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.

Keywords: Copula, Dependence, Oil, Stock, Nonparametric, Price.