Research Of The Portfolio Investment Based On Improved Genetic Algorithm

With the continuous development of China’s economy,China’s financial system is becoming more and more perfect,and the demand for asset management is increasing.How to reduce the risk in the case of guaranteed income has become the focus of attention of investors,but there is not a widely effective method to measure the risk and an effective search algorithm to solve complex optimization problems.Based on the single objective CVaR model and multi-objective portfolio based on entropy,using improved genetic algorithm to solve the model,search ability is stronger and can jump out of local convergence of the algorithm,the topic has certain theoretical significance and practical value.The paper first summarizes the relevant research results of portfolio theory and genetic algorithm,analyses the rationality of entropy theory to the investment risk measurement;then according to the actual investment behavior of single target based CVaR model is extended by improved genetic algorithm crossover probability and mutation probability in maintaining the diversity of groups at the same time,to ensure the convergence of genetic algorithm;then the beautiful Oriental Fortune 50 stock index as the research sample,using the improved genetic algorithm;finally an entropy risk measure and CVaR as objective function,a multi-objective portfolio,then the improved multi-objective genetic algorithm,which can predict premature convergence.The empirical results show that the extended model and multi-objective optimization model are effective,and the improved multi-objective genetic algorithm can optimize the solution process of the model.