TY - JOUR ID - 104107 TI - 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 JO - Petroleum Business Review JA - PBR LA - en SN - 2645-4726 AU - Tavakkoli Mohammadi, Mohammad AU - Alimoradi, Abbas AU - Sarvi, Mohsen AD - Assistant Professor, Accounting and Finance Department, Petroleum Faculty of Tehran, Petroleum University of Technology, Tehran, Iran. AD - M.A. Student in Finance, Petroleum Faculty of Tehran, Petroleum University of Technology, Tehran, Iran. Y1 - 2019 PY - 2019 VL - 3 IS - 1 SP - 1 EP - 15 KW - Liquidity Indicators KW - Operational efficiency KW - Genetic Algorithm KW - Markowitz Model KW - Optimum Portfolio DO - 10.22050/pbr.2019.104107 N2 - 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. UR - https://pbr.put.ac.ir/article_104107.html L1 - https://pbr.put.ac.ir/article_104107_9ec41570a0bdb74eb49cbb9c8b75d4b5.pdf ER -