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dc.contributor.authorJianxu Liuen_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.contributor.authorPanisara Phochanachanen_US
dc.contributor.authorJiechen Tangen_US
dc.description.abstract© Springer International Publishing Switzerland 2015. In the context of existing downside correlations, we proposed multi-dimensional elliptical and asymmetric copula with CES models to measure the dependence of G7 stock market returns and forecast their systemic risk. Our analysis firstly used several GARCH families with asymmetric distribution to fit G7 stock returns, and selected the best to our marginal distributions in terms of AIC and BIC. Second, the multivariate copulas were used to measure dependence structures of G7 stock returns. Last, the best modeling copula with CES was used to examine systemic risk of G7 stock markets. By comparison, we find the mixed C-vine copula has the best performance among all multivariate copulas. Moreover, the pre-crisis period features lower levels of risk contribution, while risk contribution increases gradually while the crisis unfolds, and the contribution of each stock market to the aggregate financial risk is not invariant.en_US
dc.subjectComputer Scienceen_US
dc.titleVolatility and dependence for systemic risk measurement of the international financial systemen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)en_US
article.volume9376en_US Mai Universityen_US Ming University of Science and Technologyen_US
Appears in Collections:CMUL: Journal Articles

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