Pricing And Risk Measuring Of Financial Multi-asset Based On The Copula Theory

Copula functions provide a flexible and useful statistic tool to construct the multivariate joint distribution and to analyze the multivariate dependency structure. The paper studies the application of the Copula theory in the financial field including modeling and analysis of financial assets pricing and risk measurement. The main work of the dissertation is as follows:It is briefly reviewed that the basic theories and methods, recently empirical research and then provides the technical methods and makes the prospect on the key research in the future. There are problems in recent application of Copula theory, such as many researches are in the field of financial risk management, during the course of being used, only the Copula-GARCH model is considered, and rare Copula models are used in the derivate assets pricing. As for these reasons, the paper does some work analyzing the application of the Copula theory in the financial field from five points of view.1. The Copula-GARCH model has widely been used in the multivariate time series to measure the dependence of the assets returns rather than assets volatilities. The SV model can describe the volatility more exactly than the GARCH model. The Copula-SV model is used to analyze the dependence of the assets returns and volatilities at the same time.2. The research of high-frequency data has been prevail but now is fasten on one variant mostly and rare multivariate high-frequency data problems are studied. Realized volatility is a volatility estimator based on high-frequency data. Modeling the Copula-RV we analyze the dynamic dependence structure of Shanghai and Shenzhen stock markets.3. There are many difficulties in derivative pricing such as the departure from normality, emerging from the smile effect and market incompleteness. Many models about derivative pricing are based derivative. The main advantage of Copula functions enables to pricing derivatives based on several options. This paper models multivariate options pricing model based on the Copula theory and presents the modeling methods.4. The Copula functions are the joint distribution of multivariate. They enable us to tackle the problem of specification of marginal univariate separately from the specification of multivariate comovement and the dependence. The copulas do not depend on the marginal distributions explained by the simulation test and they play an important role in the construction of multivariate distributions.