Predicting the optimal stock portfolio approach of meta-heuristic algorithm and Markov decision process

One of the most attractive areas for decision-making in the face of uncertainty is optimal stock portfolio. In decision making for investment, two factors are very important and are the basis of investment. These two factors are risk and return, and in this regard, the study and study of investors to select the best investment portfolio is done according to the amount of risk and its return. A portfolio is a combination of assets formed by an investor to invest. The process of selecting a stock portfolio is one of the issues that have been the focus of many researchers. The aim of this study is to create an optimal stock portfolio using the predicted data. The statistical sample of the research includes the financial data of Iranian stock exchange companies during the years 1390 to 1397. In this study, using stock regression algorithm to predict stock returns, and finally using Markov method and spectral clustering algorithm, the necessary filter to select the appropriate initial data was performed and cultural meta-processing method with prediction data, It provided the optimal portfolio of stocks for the investor group with risk-taking as well as risk-averse. The research results show that the cultural transcendental algorithm, according to Sharp's method, has the ability to create an optimal stock portfolio using predicted data using the Marquis method for venture capitalists and risk averse investors.