The combination of genetic algorithm in the optimization of the stock portfolio in the financial decision of investors

Abstract The purpose of this research is to combine the genetic algorithm in the optimization of the stock portfolio in the financial decision making of investors; in a simulation project, the final use of the input data is to build the simulation model. This process includes collecting input data, analyzing the input data, and using these analyzed input data in the simulation model. The statistical population of the research includes 20 symbols (companies) from among the industries (Vabsadar, Vetjarat, Akhaber, Fakhuz, Fars, Balbar, Tapampi, Khasapa, Khodro, Sasharq, Sosofi, Shobhorn, Shapna, Ghopino, Fould, Ghasabat, Kesra, Vanbank, Vanneft, Veniki) and the information related to the daily stock price and the daily index value from Decembre 22, 2008 to January 16, 2020 was considered as a sample. The tool for collecting information and data is using the Phipiran site, and the amount of beta (risk) of stocks is calculated monthly using Excel software, and the frequency of return and beta (risk) calculated using Spss software, and distribution functions were discussed using Easy fit software; the results showed that if the agents are beginners to earn more profit than normal behavior and accept 40% risk, the amount of profit obtained after optimizing the model with genetic algorithm is more than the initial model. If the agents are professionals to earn more profit than risk-averse behavior and accept 80% risk, the amount of profit obtained after optimizing the model with genetic algorithm is more than the initial model. Extended Abstract Introduction Today, in order to reduce the investment risk, investors in the financial markets prefer to allocate capital to a portfolil consisting of several shares rather than investing in only one share; because this enables them to bear a lower level of risk in order to achieve a certain amount of return in a certain period of time. An issue that has occupied the minds of many financial analysts and investors for many years is how to choose stocks and optimize the investment portfolio over time in a way that meets the investor's expectations in order to maximize the return on investment. When investors are exposed to uncertainty, the investment portfolio selection framework should include a quantitative measure of uncertainty to achieve the expected return or a quantitative measure of risk (Shahraki Sanavi, 2023). Today, with the increasing growth and changes of financial markets in developed and developing countries,