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Dynamic D-Vine copula model with applications to Value-at-Risk (VaR)

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Academic year: 2017

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Table 4.1 provides a few descriptive statistics of our data sets. We can see from the table that the average returns of all indexes become negative in the crisis period and the standard deviations increase
Table 4.2: Estimates from the univariate ARMA-GARCH models for the non-crisis period.
Table 4.3: Estimates from the univariate ARMA-GARCH models for the crisis period.
Table 4.4: Estimation results of the dynamic D-vine copula for the non-crisis period. Bivariate Copula θ 1 θ 2 ω 1 α 1 β 1 ω 2 α 2 β 2 Tree 1 FTSE, CAC BB1 tvp 0.7813 0.3303 -0.7987 0.3795 (0.0863) (0.0635) (0.2189) (0.0195) CAC, DAX BB1 tvp 0.7252 1.6422
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