Research On VaR Model For Risks' Coupling Theory And Numerical Simulation Technology And Its Applications

At present, value at risk (VaR) approach often ignores risks' coupling influence, which underestimates the financial risk. Since coupling risks haven't linear additivity and linear correlation is not sufficient to describe nonlinear dependence structure for coupling risks, the risk measure problem under risks' coupling effect becomes very complex and difficult. So, it is very important to build coupling risks' measure system for financial risk management. The work presented in this dissertation extends VaR approach using risks' coupling theory and measures coupling risks using numerical simulation technology. In order to gain the credit risk's parameters in the risks' coupling model, default probability is obtained from stock's price according to the concept of default distance, default probability model about Chinese listed company is proposed and credit rating system is built. Using the theory of copulas to describe the dependence structure of coupling risks, the paper builds VaR risks' coupling model and proposes numerical simulation technology about the model, extends the application of VaR approach; proposes the pricing model of convertible bond which takes the credit risk into account based on the intensity model, uses radial basis function approach to solve the valuation model and measures the VaR of convertible bond; designs interest rate risk hedge strategy under nonparallel shift of the yield curve, verifies the hedge strategy's effect using VaR approach. In order to describe the characteristics of stock return's distribution which are fat-tails and exaggerate volatility, Normal Distribution is replaced by Generalized Error Distribution in GARCH model, the simulated distribution with copulas dependence is made using Monte Carlo simulation. Through simulating default behaves of Chinese listed companies, capital portfolio's VaR and efficient frontier of Mean-CVaR model under risks' coupling effect are gained. The result shows that default probability model can identify the credit risk of Chinese listed companies effectively; credit rating system gives Chinese listed companies' credit rating results and the results are positive correlated with the corresponding rating results from Xinhua Finance; VaR risks' coupling model can reflect credit risk, market risk and the coupled effect between risks, and exactly measures the total risk of financial capital. ST listed company's credit risk is bigger, and its total risk can be underestimated if only measuring its market risk; considering credit risk, the theory value of convertible bond be closer to its market price, if ignores credit risk, can underestimates its total risk; interest rate risk hedge strategy under nonparallel shift of the yield curve reduces the VaR of hedging portfolio effectively. The researches have important reference value for financial risk management and investment decision.