The aim of this study is to optimize Stock portfolios by considering uncertain returns and the investment’ s utility function in the Tehran Stock Exchange. For this purpose, a two-stage recursive algorithm and a utility function have been used. Securities are selected according to the list of 50 most active companies that was published by the Securities and Exchange Organization per season between the years 1390 to 1394. Considering the returns in this five-year period, the returns vector and covariance matrix are determined and after modeling the optimal portfolio is presented. The results show that the optimal portfolio includes: Iran Transfo (0. 15), Eghtesad Novin Bank (0. 1), Saipa (0. 15), Ghadir Investment Company (0. 15), Foolad Mobarakeh Esfahan (0. 15), Mokhaberat Iran (0. 15) and Meli Sanaye Mess Iran (0. 15). The quality of the results is compared with real returns in the following year (1395). The results show the high accuracy of the algorithm.

Managing a single portfolio is a basic assumption in most research. However, in reality, an advisor manages many accounts at the same time,therefore, there is a significant dependency among portfolios and a correlation between decisions on one portfolio with the performance of others, so the results of the multi-portfolio are different from classic models (single portfolio management, that portfolios are optimized independently) due to market impact and the trade dependency of one account to the other accounts. We propose a structural model to optimize accounts simultaneously, considering interdependences, decision correlation and mutual behavioral effects of managed portfolios. Moreover, to compare and analyze both single-portfolio and multi-portfolio approaches, real data from Tehran Stock Exchange in 1398 are used and the model is solved with GAMS. Results indicate that multi-portfolio optimization excels other approaches and consequence notable improvement in the perspective of the customer and advisor. Also, for the validation of the proposed model, the selected Stocks are considered in pairs to solve the model and the results show the proper performance of the model with different Stocks, thus indicating the validity of the model.

Markowitz’ s return– risk model for Stock portfolio selection it is criticized. Many factors directly or indirectly influence Stock markets and make movements of asset prices very uncertain and unpredictable. The purpose of this study was to investigate the selection of Stock portfolios from companies admitted to Tehran Stock Exchange using the theory of Damsper-Schaffer. This research is descriptive-correlative method and is of applied research type. The statistical population of the study consisted of all companies listed on the Tehran Stock Exchange between 2010 and 2015, which has been studied and studied by 108 companies throughout the period of research in the Stock exchange. The research data were extracted from financial statements of companies and analyzed using regression models using combination data. The findings of the research showed that the results of the hypothesis test showed that the EPS variables, income / price ratio (P / E), ratio of payment (PR), price to sales ratio (P / S), debt Long-term equity traders (LTDER), price / cash flow ratios (P / CF), and margin squeeze (PM) in the Demerster-Schaeffer theory model.

"Regulations on paragraph c, article 15 of the law of the fourth economic, social and cultural development plan of the Islamic republic of Iran concerning the investment of foreigners in Stock Exchange" which was passed on 31 may 2005, made it possible for foreign investors to invest in Tehran Stock Market. But unfortunately few foreign investors have been inclined to invest in this market. Observing the above-mentioned rules would help us to realize if they are suitable enough to promote foreign investment or they need amendments. In this article the foregoing regulations especially restrictions will be recognized and also the relevant rules will be considered.

The process of selecting Stock portfolios for investment is one of the issues that has been considered by many researchers. 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, investors are studied to select the best investment portfolio according to the amount of risk and return. The purpose of this research is to create an intelligent model for selecting the optimal Stock portfolio using research algorithms. The proposed model examines the different types of investments that an investor can and is willing to consider in order to form his or her investment portfolio. For this purpose, the expected risk and return of companies listed on the Tehran Stock Exchange have been examined on a monthly basis. The statistical sample of the research includes the financial data of 237 Iranian Stock exchange companies during the years 1390 to 1398. The results show that the LISFLA algorithm is able to select a portfolio using the Marquis model for risk-averse and risk-averse investors.

Choosing a Stock portfolio in investment discussions is a difficult and difficult task. Deciding which Stock is in a better position compared to other Stocks and deserves to be selected and placed in one's investment portfolio, and how to allocate capital between these Stocks, is a complex issue. Considering the importance of the issue,The main purpose of this research was to investigate the selection of the portfolio of Stock assets based on the method, risk and return of the Stock market in the Tehran Stock market. This study is post-event in terms of practical and methodological purpose, the data collected annually from 1391 to 1402, which includes twenty active companies in the Iranian Stock market. which was selected using the risk minimization model based on the Markotiz model of the optimal portfolio. The results and analysis show that the selection of the efficient portfolio is based on the efficiency frontier diagram of the latest Stock price of the companies based on yield and risk, for example,Amir Kabir Kashan steel has less risk and more yield than all the items. Pars Industrial Carbon Black is less risky than Fan Avran Petrochemical, Chemical Daro Pars. However, it is less efficient compared to Techno-Avaran petrochemicals, but it is more efficient compared to Dorofos chemical. Khuzestan steel has the highest risk and zero return of all items and should not be chosen. Chador Melo, Khark Petrochemical, Mobarakeh Steel have more risk and very very little return,And should not be chosen.

Efficient Asset allocation and investment portfolio selection are among the most critical and challenging issues in investment management and a continuous concern for investors. When investors invest in the capital market, they expect their portfolio to perform well. Therefore, this study determines the optimal Stock portfolio of agricultural companies in the Tehran Stock Exchange (TSE). Thirty-two most important agriculture companies in the (TSE), with monthly data from 2014-2020, were selected from Iran's two most essential agriculture industries, the food and beverage industries, and the sugar industry. Two portfolios for the food and beverage industry and sugar industry goals: minimizing portfolio variance and maximizing portfolio return using the Markowitz model with two different scenarios and applying two minimum investment constraints of 1% and optimized maximum investment of 20% without considering these two constraints. The efficiency, variance, and Sharp ratios are also calculated. The results showed that both food and beverage industry portfolios and the sugar industry portfolios became more efficient when optimized to maximize portfolio returns. The result also indicates the food and beverage industry was more efficient than the portfolio of the sugar industry. In this portfolio, the amount of investment for the shares of Salmin Company was 86. 7% and for Mehram Company was 13. 3%.

portfolio is combination of assets by an investor for investment. Process of selecting optimal Stock basket is one of issue, which is paid attention by scholars. Various criteria of this process have changed by the time and this condition is necessary as optimal for making decision. Several criteria are included in selecting Stock basket and it is necessary to use optimal tools for making better decision. Aim of this research is creating intelligent model in order to select optimal Stock basket throughout adjusted differential evolution algorithm. Thus, we investigated risk and returns of companies listed at Tehran Stock exchange annually. Sample study of research includes 102 companies during 2009 and 2013. Results of research showed that selected model by considering interaction between risk and expected return leads to selected optimal Stock basket.

The main objective of this research is to design a comprehensive model for Stock portfolio optimization in a capital market bubble using smart strategic management, a model that can reduce risks arising from severe market fluctuations and improve long-term investment returns. In the turbulent environment of financial markets and the increasing presence of new technologies, investors and capital managers need to look beyond traditional portfolio management methods and must shape their investment strategies by relying on smart, data-driven concepts and advanced analytics. In this regard, the present research, focusing on the development of smart tools and methods, tries to identify the structure and processes that, with the help of advanced technologies and data analysis, enable the formation of a systematic and resilient approach to facing capital market bubbles. This qualitative research is based on content analysis and was conducted through targeted interviews with capital managers, financial experts, and academics in the field of financial management and investment. The findings show that designing an intelligent model for portfolio management in a market bubble, while creating convergence in the investment decision-making process and effectively utilizing environmental information, can promote collaborative behavior in investment teams and define new motivational structures. In this way, investors will be able to optimize their investment portfolios in the long term and benefit from their competitive capabilities while reducing investment risks and increasing returns.

One of the most applicable optimization approaches used in different sciences is Meta-heuristic Algorithms. This study, by new Meta-heuristic Algorithms, Symbiotic Organisms Search (SOS), introduces the model for selection of optimum portfolio and then the result is compared with the result of older algorithm, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Therefore, the ten-month information of operation of 50 top companies in the Stock Exchange is extracted and estimated an optimized portfolio with the objectives of maximum efficiency and minimum risk by Symbiotic Organisms Search (SOS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) is estimated. The results of the algorithm showed that despite the ability of these algorithms to portfolio optimization, SOS algorithm has a higher ability to optimization.