Does Asymmetric Dependence Structure Matter? A Value-at-Risk View

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.