The Optimal Portfolio Decision Model With Mean-VaR Risk Control

The Mean-variance model, which utilize the mean and variance of return to measure the investment return and risk respectively, is widely used in portfolio optimization. As the further study on the financial risk measurement methods, Value-at-Risk (VaR) model has been extensively used in financial companies for its simplicity and convenience. In the thesis, optimal portfolio decision model was analyzed and risk measurement methods were discussed. Based on the traditional mean-variance controlled optimal portfolio risk model, optimal portfolio decision-making with mean-VaR risk was considered, then single-period and multi-period and portfolio decision model were established with the risk-free assets and transaction costs. The solutions of the model were got by numerical simulation of genetic algorithm and analyzed. The results show that the multi-period portfolio decision model outperforms the single-period portfolio decision model with mean-VaR risk control. The results can be of significance for the investor to do better risk management and rational investment, at the same time it provide a reference for effective investment decisions.