| dc.description.abstract | This paper implements the statistical modelling of the dependence structure of bivariate currency
exchange rates using the concept of copulas. The GARCH-EVT-Copula model is applied to
estimate the portfolio Value-at-Risk (VaR) of currency exchange rates. First the univariate ARMAGARCH
model is used to filter the return series. The generalized Pareto distribution is then fitted
to the tails of the standardized residuals to model the distributions marginal residuals. Dependences
between transformed residuals are modeled using bivariate copulas. Finally the portfolio VaR is
estimated based on Monte Carlo simulations on an equally weighted portfolio of four currency
exchange rates. The empirical results demonstrate that the Student’s t copula provide the most
appropriate representation of the dependence structure of the currency exchange rates. The
backtesting results also demonstrate that the semi-parametric approach provide accurate estimates
of portfolio risk on the basis of statistical coverage tests compared to benchmark GARCH models.
Keywords: Backtesting, copulas, currency exchange rate, dependence modelling, GARCH-EVTCopula
model, portfolio risk, Value-at-Risk. | en_US |
