Using Conditional Copula to Estimate Value-at-Risk in Vietnam's Foreign Exchange Market

Abstract

In this paper, we briefly review the basics of copula theory and the problem of estimating Value-at-Risk (VaR) of portfolio composed by several assets. We present two VaR estimation models in which each return series is assumed to follow AR(1)-GARCH(1, 1) model and the innovations are simultaneously generated using Gaussian copula and Student t copula. The presented models are applied to estimate VaR of a portfolio consisting of 6 currencies to VND. The results are compared with results from two VaR estimation models using AR(1)-GARCH(1, 1) model and the innovations are separately generated using univariate standard normal and Student t distribution