Research On Robust Optimization Portfolio Based On Scenario Generation

Financial markets are unpredictability and volatility. How to overcome the volatility, limit the unknown impact on the earnings in a certain tolerance range, obtain high earnings with high stability is a new direction of the financial sector. Classical finance theory and research methods have a certain accomplishments on the direction of increasing revenue, but go to stuck at the direction of stability and they can not solve the internal stability and external anti-interference ability of the financial models. Thus, one method which is called robust and famous for enhancing the stability is introduced in the financial sector. it succeed in improving earnings but also solving the model’s internal stability and external interference.(1) In this paper, use the scenario generation methods of stochastic programming and vector autoregressive method to generate a two-stage scenario tree. On this basis, conduct the research on the robust optimization of the portfolio.(2) Introduce a robust second-order cone optimization approach to transform the utility maximization model. Through a detailed theoretical analysis, get the robust second-order cone optimization model. On the basis of robust second-order cone optimization model, take into account the friction of the financial markets in the multi-stage transaction, introduce the friction coefficient, robust second-order cone optimization model for a friction market was detailed derived.(3) Use the share data of China’s financial market, contrast and analysis the optimization results of utility maximization model and robust second-order cone optimization models, significantly discover that the introduction of robustness increase the earnings, at the same time greatly improving the model’s internal stability and external interference.(4) Use the share data of China’s financial market, contrast and analysis the optimization results of robust second-order cone optimization models and robust second-order cone optimization model under a friction market, significantly discover that the introduction of the friction coefficient caused the loss of market efficiency, resulting in deviation from optimal benefits and the minimum standard.