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To investigate the importance of asymmetric
dependence structures for portfolio
value-at-risk (VaR) and
conditional VaR (CVaR) calculations, we introduce bivariate copula
functions with two GJR-GARCH models as marginals. The results show
that the copula models and the competing dynamic conditional
correlation (DCC) model are valid for almost all two-asset
portfolios with different weights. However, among models validated
with standard procedures, copula models with asymmetric dependence
structures can save capital charges for market risks and reduce
potential loss compared with those with symmetric dependence
structures and with the competing DCC model, implying that
asymmetric dependence structures are of great importance in
improving VaR and CVaR calculations not only from a statistical but
also an economic perspective. |