| Summary: | 碩士 === 國立中山大學 === 財務管理學系研究所 === 95 === Copula functions represent a methodology which can describe the dependence structure of multi-dimension random variable, and has recently become the most significant new tool to handle risk factors in finance such as Value-at Risk( VaR) which was probably the most widely used risk measure in financial institutions. In this paper, Copula and the forecast function of Garch model are well combined, and a new method Conditional-Copula-Garch is built for measure the dependence of financial data and compute the VaR of portfolios. Copula-Garch models allow for very flexible joint distribution by splitting the marginal behaviors form the dependence relation unlike the traditional approaches for the estimation VaR, such as variance-covariance, and the Monte Carlo approaches whereas demand the joint distribution to be known. This work presents an application of the Copula-Garch model in the estimation of VaR of a portfolio composed by NASDAQ and TAIEX (Taiwan stock exchanged capitalization weighted index) stock indices.
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