The Alpha Investment Portfolio Model Based On The Dynamic Prospect Utility And Empirical Research

Through three decades’ reform and opening-up, China’s economy has developed greatly. Moreover, China’s financial market has been improved increasingly and has developed significantly, offering important financial supports to the development of the real economy. In China, the development of financial market drives the development of financial agents and institutions which provide financial services, such as investment consultation and risk management, to investors and play a positive role in helping investors increase their wealth and control investment risk. However, because China’s stock market is very young and the market system is not perfect, lots of problems emerge in the market and investors face big market risk in the process of investment. It is an important issue to discuss about how to build an effective investment model to help investors obtain investment return under the control of investment risk.Markowitz brought forth the classic portfolio model and discussed a portfolio theory which balanced return and risk. Based on Markowitz’s portfolio theory, William F. Sharpe and John Lintner put forward the Capital Asset Pricing Model(CAPM) according to the general equilibrium method. They pointed out that the return of assets could be explained by market risk factor. However, many studies have shown that the return of stock assets is difficult to be explained by market risk factors alone, and there are many “price anomalies” in the market. Investors begin to seek various investment methods, expecting to obtain excess return. Jensen M. C. brought forth the Jensen Alpha indicator to represent excess return in investment. All investment methods which build a portfolio by selecting Alpha assets could be named Alpha investment methods collectively. In the China’s stock market, all investors want to know that how to build an effective Alpha portfolio model to obtain excess returns under the control of investment risk, which is also the main topic to be discussed in this paper. Particularly, there are three parts:1. From the perspective of company value, select the company value indicators which can represent company competitive advantages in many aspects, and integrate with the market trend indicator, then establish the Alpha asset selection criteria based on multi-source information integration for investment asset selection. In consideration of the investment risk, the risk-free asset is selected in the portfolio with the risk assets, and the variable-weight Alpha portfolio model is built. The Realized-GARCH model of integrated high frequency data is selected to describe the assets’ abnormal marginal distribution. The Clayton-Copula function is used to express the nonlinear correlation between assets. The VaR model based on the Realized-GARCH-Clayton-Copula function is built to express the risk constraint of the variable-weight Alpha portfolio model. In consideration of the investors’ dynamic reference point and lost aversion coefficient, build a dynamic prospect utility function to take the place of the expected utility function. In this way, the variable-weight Alpha portfolio model base on the dynamic prospect utility is built. The empirical researches with actual data have demonstrated that the assets selected by the Alpha asset selection criteria based on multi-source information integration can obtain the excess return, and the variable-weight Alpha portfolio model base on the dynamic prospect utility has the advantage of obtaining the excess return under the control of investment risk.2. Stock Index Futures are used in this paper to take the place of the risk-free asset so as to control the Alpha portfolio’s investment risk. The Realized-GARCH model of integrated high frequency data is selected to describe portfolio assets’ abnormal marginal distribution. The Clayton-Copula function is used to express the dynamic nonlinear correlation between portfolio assets. The VaR model based on the Realized-GARCH-Clayton-Copula function is built to express the risk constraint of the Alpha portfolio hedging model. In this way, the Alpha portfolio hedging mode based on the dynamic prospect utility is built. The empirical researches with actual data have demonstrated that reestablishment of an investment portfolio hedging model produces better effects, suggesting that financial derivatives have the advantage of controlling investment risk.3. Multi-strategy integrated investment method is applied to improve the Alpha portfolio model. In consideration of Stock Index Futures’ asset allocation function and margin advantages, technical analysis is used to divide market status, Portable Alpha investment strategy is created based on the market state transformation. The Realized-GARCH model is selected to describe assets’ abnormal marginal distribution. The Mix-Copula function, which is based on multiple market status, is used to estimate several assets’ complex dynamic the nonlinear correlation. The VaR model based on the Realized-GARCH-Mix-Copula function is built to express dynamic investment’s risk constraint. In addition, the multi-strategy integration Alpha portfolio model based on the dynamic prospect utility is built. The empirical researches with actual data have demonstrated that the multi-strategy integration Alpha portfolio model based on the dynamic prospect utility produces better effects, suggesting that the flexible use of various financial derivatives in the investment portfolio has obvious advantages.