The Portfolio Investment Based On Genetic Algorithm And Examples Analysis

Portfolio based on uncertain environment, any income will be accompanied by certain risks, in order to spread a great risk and get a more stable investment income, can be in a variety of securities in different proportion to carry out investment, the key of portfolio is based on the preferences of investors, make a banlance between income and risk, identify a variety of securities in the portfolio of proportion, so can get a satisfied portfolio.The genetic algorithm is a kind of searching method which simulates the natural evolution. Its simple and easy to implement, especially it doesn't need the special field knowledge, but simple uses fitness function as an assessment to instruct the search process, so it has been used in very broad fields. Now the genetic algorithm has got a lot of fruits and scholars begin to pay attention to it. This paper gives a brief introduction to the basic conception and theories of the genetic algorithm. And it also provides a detailed explanation on the components of the genetic algorithm, with the emphasis on the strategies of selection, crossover, mutation and the basic theorem—schema theorem.This paper combines portfolio and genetic algorithm, and bring up a portfolio based on genetic algorithm. Through study of some portfolio model,considering the practrcality of moder portfolio selection theory, we propose a constrained portfolio selection model based on the no short sale, transaction costs and minimun lot constraints. Due to these complex constrains our proposed problem becomes a mixed integer optimization problem and traditional algorithm can't solve it efficiently. Thus, an improved genetic algorithm is designed to solve our proposed problem.At last, from China's securities market as evidence, can be see the portfolio and algorithm that we proposed is feasibility and validity.