%0 Journal Article %T Investigating the Effects of New Corporate Liquidity and Market Operational Performance Indicators on the Markowitz Model Portfolio Returns Using Genetic Algorithm: A Case Study on Refineries and Petrochemical Companies Listed on Tehran Stock Exchange %J Petroleum Business Review %I Petroleum University of Technology %Z 2645-4726 %A Tavakkoli Mohammadi, Mohammad %A Alimoradi, Abbas %A Sarvi, Mohsen %D 2019 %\ 03/01/2019 %V 3 %N 1 %P 1-15 %! Investigating the Effects of New Corporate Liquidity and Market Operational Performance Indicators on the Markowitz Model Portfolio Returns Using Genetic Algorithm: A Case Study on Refineries and Petrochemical Companies Listed on Tehran Stock Exchange %K Liquidity Indicators %K Operational efficiency %K Genetic Algorithm %K Markowitz Model %K Optimum Portfolio %R 10.22050/pbr.2019.104107 %X The research on the Markowitz model and optimization of its portfolio using a variety of evaluation indicators and metaheuristic-algorithms has always been the focus of attention of accounting and finance researchers. The results of studies carried out by various types of optimization method are different in the Markowitz modified models. The purpose of this study is to measure the optimal portfolio and its corresponding return with respect to the portfolio in the traditional Markowitz model as well as comparing the position of the refining and petrochemical companies versus stock market outperformers through integrating the operational criteria and the new indicators of liquidity by using the genetic algorithm in the Markowitz model. Therefore, financial data related to the research variables of 35 cases of refinery and petrochemical companies listed on Tehran Stock Exchange (TSE) from 2012 to 2016 fiscal years were extracted from Rahavard Novin database software and simulated by the genetic algorithm. The results show that returns on the stock portfolios optimized using the genetic algorithm without considering the liquidity limitations and filters are significantly and positively different from the returns on the stock portfolios optimized with regarding the liquidity limitations and filters. Furthermore, the application of liquidity limitations and filters to the formation of the optimal stock portfolios leads to a conservative increase in the choice of stocks (portfolio formation), which results in a reduction in the risk and return of investment in such portfolios. %U https://pbr.put.ac.ir/article_104107_9ec41570a0bdb74eb49cbb9c8b75d4b5.pdf