Copula approach to fitting bivariate time series
We apply the GARCH-copula method to estimate Value at Risk (VaR) for European and Stockholm stock indices. First, marginal distributions are estimated by the ARMA-GARCH model with normal, Student-t, and skewed t distributions. Then we investigate the tails of innovations of ARMA-GARCH models using the Peaks over thresholds method and find that the distributions of stock returns are asymmetric