Abstract
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.
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Liu, J., Sriboonchitta, S., Phochanachan, P., Tang, J. (2015). Volatility and Dependence for Systemic Risk Measurement of the International Financial System. In: Huynh, VN., Inuiguchi, M., Demoeux, T. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2015. Lecture Notes in Computer Science(), vol 9376. Springer, Cham. https://doi.org/10.1007/978-3-319-25135-6_37
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DOI: https://doi.org/10.1007/978-3-319-25135-6_37
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