Risk analysis in Asian emerging markets using canonical vine copula and extreme value theory

Abstract

© 2014 by the Mathematical Association of Thailand. All rights reserved. Normal distributions are appropriate to describe the behavior of stock market returns only when returns do not exhibit extreme behavior. This study examined extreme value theory (EVT) to capture more precisely the tail distribution of market risk with vine copula and to identify the dependence structures between Asian emerging markets. We used value at risk (VaR) and conditional value at risk (CVaR), based on simulation method, to measure the market risk and portfolio optimization. Our empirical findings are that the conditional dependence between asymmetric volatility among five markets are positive and have the dependence between Indian and Thai stronger than other markets. The results of VaR and CVaR show that the Chinese market has the highest risk.