Dependence Analysis for the Exchange Rate Data using Extreme Value Copulas

This article considers the bivariate generalized extreme value (BGEV) distribution and the bivariate generalized Pareto distribution (BGPD) to model the tail probability and tail dependence of the fi nancial return series based on month-ly and daily maxima of BHT/USD, EUR/USD foreign exchange data, respectively. The selection and estimation of the copula is based on the maximum likelihood estimation(MLE) approach which is proposed for nine parametric models of dependence function for both distributions. The copula parameters are estimatedby Inference For Margins(IFM) approach and then select best fi tting model by Akaike Information Criterion (AIC) value