IMPROVED GENETIC ALGORITHM TO OPTIMAL PORTFOLIO WITH RISK CONTROL

摘要

A modified model of optimal investment port folio in a random market with risk constraints is presented. An improved genetic algorithm (GA) is proposed to solve this nonlinear optimal problem. The numerical simulation of a large-scale investment combination for Shanghai stock market shows that GA has the advantage of faster convergence and wider adaptability than traditional optimization algorithm. This result alsodemonstrates that the improved GA performs better than the basic GA.