Copula based volatility models and extreme value theory for portfolio simulation with an application to asian stock markets

Abstract

Many empirical works used risk modeling under the assumption of Gaussian distribution to investigate the market risk. The Gaussian assumption may not be appropriate for risk estimation techniques in some situations. In this study, we used the extreme value theory (EVT) to examine more precisely the tail distribution of market risk and incorporate high dimensional copulas to explore the dependence between stock markets. We gathered data of stock markets from Asean countries (Thailand, Singapore, Malaysia, Indonesia and the Philippines) to simulate the portfolio analysis during and post subprime crisis. The results found that D-vine copula GARCH-EVT model can simulate the efficient frontier of portfolios greater than other models. Furthermore, we also found the positive dependence for the overall markets.