The Portfolio Theory And Empirical Research Based On CVaR

The risk measure method of CVaR(Conditional Value-at-Risk) is developed on the basis of VaR. CVaR is better to reflect the potential risk than VaR. CVaR has application in many aspects, for instance measurement of the credit risks, confirmation of the inner risk capital, capital collocation, financial supervision and so on. The main research of this paper is the theory of portfolio based on CVaR.The main content of this paper is: ①Comparing CVaR with VaR based on the empirical research on the stock market of our country. ②Analyzing and studying the efficient frontier of mean-CVaR under normal distribution condition. ③Studying the effect of some constraints on the efficient frontier of mean-CVaR, such as believe degree, weight coefficient and transaction cost.This paper divides five chapters altogether.Chapter one proposes the studying background and meaning, introduces the domestic and international scholars' study and the existing problem, puts forward the innovation of this paper.Chapter two makes a brief instruction to the theory of portfolio from traditional portfolio theory and modern portfolio theory, such as mean-variance, mean-semivariance, mean-deviation, mean-semideviation and Sharpe model, studies the mean-VaR and defect.Chapter three is the main content of this paper, puts forward the mean-CVaR portfolio model. Firstly, it introduces the definition, the calculation, the parameter selecting and the application. Secondly, it puts forward the mean-CVaR model and analyses the frontier of mean-CVaR and the effect of believe degree on the frontier under normal distribution condition, concludes that the solution of mean-CVaR is same with the solution of mean-variance under normal distribution. Thirdly, it compares CVaR with VaR based on the empirical research on the stock market of our country and makes a conclusion that CVaR is better than VaR.Chapter four is a part of empirical research, also the main content of this paper. Firstly, it empirically studies the efficient frontier of mean-CVaR under normal distribution condition mentioned in chapter three and compares with the efficient frontier of mean-variance. Secondly, it empirically studies the effect of some constraints on the efficient frontier of mean-CVaR, such as believe degree, weight coefficient and transaction cost. Thirdly, aiming at the actuality of our finance market, it gives some advices to accelerate the application of CVaR in our country.