Open Access
Issue
MATEC Web Conf.
Volume 100, 2017
13th Global Congress on Manufacturing and Management (GCMM 2016)
Article Number 05079
Number of page(s) 7
Section Part 5: Management Engineering
DOI https://doi.org/10.1051/matecconf/201710005079
Published online 08 March 2017
  1. Engle R.E. Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models. Journal of Business & Economic Statistics,2002,7:339–350. [CrossRef] [Google Scholar]
  2. Rodriguez.J.C. Measuring Financial Contagion: A Copula Approach, Journal of Empirical Finance, 2003,14: 401–423. [CrossRef] [Google Scholar]
  3. Embrechts P, Hoeing A, Juri A. Using copula to bound the value at Risk for functions of dependent risks. Finance and Stochastics, 2003, 7:145–167. [CrossRef] [Google Scholar]
  4. Fan J, Jiang J·Zhang, et al, Time-Dependent Diffusion Models for Term Structure Dynamics, Statistica Sinica, 2003, 13: 965~992. [Google Scholar]
  5. Chen M, Chen G. A nonparametric test of conditional autoregressive heteroscedasticity for threshold autoregressive models . The Canadian Journal of Statistics, 2008,4:649–666. [Google Scholar]
  6. R B Nelsen, An Introduction to Copulas, Springer, New York,2006:51–155. [Google Scholar]
  7. Zhang Xuegong, Zhichao Xue, et al. Analysis of financial market based on Copula-SV-t Pair-Correlation, journal of Finance and Economics, 2016.04:71-76 (In Chinese). [Google Scholar]
  8. Yi Wen-de. Conditional dependence modelsof assets based on and its applications of portfolios Copula functions. Systems Engineering-Theory and Practice, 2011, 6:1004-1013 (In Chinese). [Google Scholar]
  9. WenX, WeiY, HuangD. Measuring contagion between energy market and stock market during financial crisis:a copula approach. Energy economics,2012,34(5):1435-1446(In Chinese). [CrossRef] [Google Scholar]
  10. Kunlapath S, Tatevik Z, et al. Interdependence of oil pricess and stock market indices:a copula approach. Energy Economics, 2014,44(4):331–339. [CrossRef] [Google Scholar]
  11. Yao Den-bao, Liu Xiao-xing, Hang Xu. Dynamic Correlation Structure Between Market Liquidity and Market Expectation: An Analysis Based on ARMA-GJR-LARCH-Copula Model, Chinese Journal of Management Science, 2016.2 (4):1–10(In Chinese). [Google Scholar]
  12. YuWen-hua. Study on Extreme Value Dependence Measurement of Shanghai and Shenzhen Composite Index—Based on the Four Types of Time-Varying Copula Model, Journal of southwest jiaotong university 2013,7(4):90-96(In Chinese). [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.