In this paper we propose a method to estimate the value-at-risk (VaR) of a portfolio based on
a combination of time series, extreme value theory and copula fitting. Given multivariate
financial data, we use a univariate ARMA-GARCH model for each return series. We then fit a
generalized Pareto distribution to the tails of the residuals to model the distributions of
marginal residuals, followed by a bivariate extreme value copula fitting, which is used to
estimate portfolio VaR via simulation. As a first step, this method is applied to two portfolios …