List of articles (by subject) Financial Engineering
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Open Access Article
1 - Portfolio Optimization Based on Semi Variance and Another Perspective of Value at Risk Using NSGA II, MOACO, and MOABC Algorithms
Reza Aghamohammadi Reza Tehrani Abbas RaadThis study examines the criterion of value at risk from another perspective and presents a new type of mean-value at Risk model. To solve the portfolio optimization problem in Tehran Stock Exchange, we use NSGA II, MOACO, and MOABC algorithms and then compare the mean-p MoreThis study examines the criterion of value at risk from another perspective and presents a new type of mean-value at Risk model. To solve the portfolio optimization problem in Tehran Stock Exchange, we use NSGA II, MOACO, and MOABC algorithms and then compare the mean-pVaR model with the mean-SV model. Given that, finding the best answer is very important in meta-heuristic methods, we use the concept of dominance in the discussion of multi-objective optimization to find the best answers and show that, at low iterations, the performance of the NSGA II algorithm is better than the MOABC and MOACO algorithms in solving the portfolio optimization problem. As the iteration increases, the performance of the algorithms improves, but the rate of improvement is not the same, in a way, the performance of the MOABC algorithm is better than that of the NSGA II and MOACO algorithms. Then, to compare the performance of the “mean-percentage of Value at Risk” model and the “mean-semi variance” model, we examine both models in the standard mean-variance model and show that the mean-pVaR model, compared to the mean-SV model, Has better performance in stock portfolio optimization. Manuscript profile -
Open Access Article
2 - Forecasting the Tehran Stock market by Machine Learning Methods using a New Loss Function
Mahsa Tavakoli Hassan DoostiStock market forecasting has attracted so many researchers and investors that ‎many studies have been done in this field. These studies have led to the ‎development of many predictive methods, the most widely used of which are ‎machine learning-based methods MoreStock market forecasting has attracted so many researchers and investors that ‎many studies have been done in this field. These studies have led to the ‎development of many predictive methods, the most widely used of which are ‎machine learning-based methods. In machine learning-based methods, loss ‎function has a key role in determining the model weights. In this study a new loss ‎function is introduced, that has some special features, making the investing in the ‎stock market more accurate and profitable than other popular techniques. To ‎assess its accuracy, a two-stage experiment has been designed using data of ‎Tehran Stock market. In the first part of the experiment, we select the most ‎accurate algorithm among some of the well-known machine learning algorithms ‎based on artificial neural network, ANN, support vector machine, SVM. In the ‎second stage of the experiment, the various popular loss functions are compared ‎with the proposed one. As a result, we introduce a new neural network using a ‎new loss function, which is trained based on genetic algorithm. This network has ‎been shown to be more accurate than other well-known and common networks ‎such as long short-term memory (LSTM) for both train and test data.‎ Manuscript profile -
Open Access Article
3 - Designing Native Decision-Making Model for Selecting Venture Capital Investment in Emerging Companies
Mohammadreza Radfar Gholamreza Zomorodian Mansoureh Aligholi Mehrzad Minouei Farhad HanifiVenture capital companies play an important role in the economy of countries and greatly influences economic and employment growth. VC is the provision of capital for companies and entrepreneurs that is prone to leaping and growing value and, of course, a lot of risk. H MoreVenture capital companies play an important role in the economy of countries and greatly influences economic and employment growth. VC is the provision of capital for companies and entrepreneurs that is prone to leaping and growing value and, of course, a lot of risk. However, the volume of venture capital in our country is far less than the economic capacity. Many of analysts consider having no model for venture capital in our country as the main reason for this. Therefore, the present study by the qualitative method aims to design decision-making native model for selecting venture capital investment in emerging companies. To achieve this goal, by collecting qualitative data through literature reviews and having deep interview with experts and venture capital firms, a native decision-making model for selecting venture capital in emerging companies is presented. The methodology of this research based on purpose, is fundamental and through the qualitative methods, thematic analysis method is used. Purposeful sampling method is used and interviewing experts continued to theoretical saturation level that means the number of selected samples includes 16 elites. The native decision-making model for selecting venture capital in emerging companies presented in this research has 16 main themes and 86 sub-themes. Manuscript profile -
Open Access Article
4 - Pattern Explanation of Micro and Macro variables on Return of Stock Trading Strategies
atefeh yazdani varzi Erfan memarian Seyed Ali Nabavi ChashmiIn the research, pattern explanation of micro and macro variables on return on stock trading strategies has been dealt with. Based on data collected, existence of momentum and contrarian strategies in Tehran Stock Exchange market has been studied. To collect data and ma MoreIn the research, pattern explanation of micro and macro variables on return on stock trading strategies has been dealt with. Based on data collected, existence of momentum and contrarian strategies in Tehran Stock Exchange market has been studied. To collect data and make statistical analysis, Excel Spread Sheet software, and statistical SPSS and R software packages have been used. Through usage made of various statistical models, the relationship between variable of return on stock and other variables added has been studied so that based on which stock trading strategy would be predicted, for the next 12 months. To do so, three statistical models of autoregressive time series (with no auxiliary variable), linear regression, and Markov-switching have been applied. Using the model’s fit criteria, these three models have been compared and best of them has been selected. Based on selected model, stock trading strategy for the next 12 months has been predicted. Markov model showed that within next 12 months, using contrarian strategy i.e. selling previous winners and purchasing previous losers can be profitable. According to the research findings, from among micro variables (base volume, trade volume, institutional investment, and free float) and from among macro variables (currency and inflation rates), only three variables of the first (base volume, institutional investment, and free float) are effective on stock trading strategy; and, they can be used as auxiliary variables to predict return on stock and to specify stock trading strategy in future as a result. Manuscript profile -
Open Access Article
5 - Improving Stock Return Forecasting by Deep Learning Algorithm
Zahra Farshadfar Marcel ProkopczukImproving return forecasting is very important for both investors and researchers in financial markets. In this study we try to aim this object by two new methods. First, instead of using traditional variable, gold prices have been used as predictor and compare the resu MoreImproving return forecasting is very important for both investors and researchers in financial markets. In this study we try to aim this object by two new methods. First, instead of using traditional variable, gold prices have been used as predictor and compare the results with Goyal's variables. Second, unlike previous researches new machine learning algorithm called Deep learning (DP) has been used to improve return forecasting and then compare the results with historical average methods as bench mark model and use Diebold and Mariano’s and West’s statistic (DMW) for statistical evaluation. Results indicate that the applied DP model has higher accuracy compared to historical average model. It also indicates that out of sample prediction improvement does not always depend on high input variables numbers. On the other hand when using gold price as input variables, it is possible to improve this forecasting capability. Result also indicate that gold price has better accuracy than Goyal's variable to predicting out of sample return. Manuscript profile -
Open Access Article
6 - Stock price analysis using machine learning method(Non-sensory-parametric backup regression algorithm in linear and nonlinear mode)
Aliasgar Davoodi Kasbi Iman Dadashi Kaveh AzinfarThe most common starting point for investors when buying a stock is to look at the trend of price changes. In recent years, different models have been used to predict stock prices by researchers, and since artificial intelligence techniques, including neural networks, g MoreThe most common starting point for investors when buying a stock is to look at the trend of price changes. In recent years, different models have been used to predict stock prices by researchers, and since artificial intelligence techniques, including neural networks, genetic algorithms and fuzzy logic, have achieved successful re-sults in solving complex problems; in this regard, more exploitation Are. In this research, the prediction of stock prices of companies accepted in the Tehran Stock Exchange using artificial intelligence algorithm (non-sensory-parametric support vector regression algorithm in linear and nonlinear mode) has been investigated. The results of the research show that the PINSVR algorithm in nonlinear mode has been able to predict the stock price over the years, rather than linear mode. Manuscript profile -
Open Access Article
7 - Applying Optimized Mathematical Algorithms to Forecast Stock Price Average Accredited Banks in Tehran Stock Exchange and Iran Fara Bourse
Negar Aghaeefar Mohammad Ebrahim Mohammad Pourzarandi Mohammad Ali Afshar Kazemi Mehrzad MinoieThe effective role of capital in every country flows through giving guidelines for capital and resources, generalizing companies and sharing development projects with public, and also adding accredited companies stock market requires appropriate decision making for shar MoreThe effective role of capital in every country flows through giving guidelines for capital and resources, generalizing companies and sharing development projects with public, and also adding accredited companies stock market requires appropriate decision making for shareholders and investors who are willing to buy shares based on price mechanism. Forecasting stock price has always been a challenging task, since it is affected by many economic and non-economic factors and variables; therefore, selecting the best and the most efficient forecasting model is tough and essential. Up to now applying weighted mean called weighted mean price has been used to forecast industry average price for companies in the stock market and investors were forecasting based on this method. First we have identified 10 accredited banks in TSE and 10 banks in Iran Fara Bourse. In this article, by applying one of the mathematical optimizing techniques, industry means got calculated based on optimized parameters and compared with the industry average; in this statement we strived to find another variable that could forecast with less deviation. In the following study, by calculating frequency level of deviations, average for price forecasting in banking industry during five years is examined. Finally, the research suggests that, instead of using mean of industry average, it is better to use mean average of golden number, which will lead us to more accurate results. Manuscript profile -
Open Access Article
8 - Stock price prediction using the Chaid rule-based algorithm and particle swarm optimization (pso)
Aliasghar Davoodi Kasbi Iman DadashiStock prices in each industry are one of the major issues in the stock market. Given the increasing number of shareholders in the stock market and their attention to the price of different stocks in transactions, the prediction of the stock price trend has become signif MoreStock prices in each industry are one of the major issues in the stock market. Given the increasing number of shareholders in the stock market and their attention to the price of different stocks in transactions, the prediction of the stock price trend has become significant. Many people use the share price movement process when com-paring different stocks while investing, and also want to predict this trend to see if the trend continues to increase or decrease over time. In this research, stock price prediction for 1170 years -company during 2011-2016 (a six-year period) of listed companies in stock exchange has been studied using the machine learning method (Chaid rule-based algorithm and Particle Swarm Optimization Algorithm). The results of the research show that there is a significant relationship between earnings per share, e / p ratio, company size, inventory turnover ratio, and stock returns with stock prices. Also, particle swarm optimization (pso) algorithm has a good ability to predict stock prices. Manuscript profile -
Open Access Article
9 - Performance Evaluation of the Technical Analysis Indicators in Comparison with the Buy and Hold Strategy in Tehran Stock Exchange Indices
Ebrahim Abbasi Mohammad Ebrahim Samavi Emad KooshaTechnical analysis is one of the financial market analysis tools. Technical analysis is a method of anticipating prices and markets through studying historical market data. Based on the factors studied in this type of analysis, indicators are designed and presented to f MoreTechnical analysis is one of the financial market analysis tools. Technical analysis is a method of anticipating prices and markets through studying historical market data. Based on the factors studied in this type of analysis, indicators are designed and presented to facilitate decision-making on buy and sell stress and then buy and sell action in financial markets. This research evaluates performances and returns of 10 conventional technical analysis indicators based on the strategies set on the total stock exchange index, the total index of OTC market and 8 other (non-correlated) industry indices by using Meta Trader software from 2008 to 2018. Also, the significance of the difference between the returns of the indicators is tested using the buy and hold strategy. The results show a significant difference between the returns using some of the technical analysis indicators in some indices and buy and hold strategy. The effectiveness of technical analysis strategies varies across industries and EMA and SMA with respectively 6 and 5 repetitions, are the best strategies and BB with just one repetition has the least repetition. The investment industry index with the most repetition is the industry in which the strategies used in this study have been able to provide an acceptable return. Manuscript profile -
Open Access Article
10 - Integration of Liability Payment and New Funding Entries in the Optimal Design of a Supply Chain Network
Abbas Biglar Nima Hamta Mona Ahmadi RadIn recent years, the supply chain network design (SCND) problems that integrate financial issues have attracted the attention of managers and researchers. In this paper, in order to address an SCND problem, a mixed-integer nonlinear programming (MINLP) model developed t MoreIn recent years, the supply chain network design (SCND) problems that integrate financial issues have attracted the attention of managers and researchers. In this paper, in order to address an SCND problem, a mixed-integer nonlinear programming (MINLP) model developed that considers operational and financial decisions simultaneously for designing a deterministic multi-echelon, multi-product, and multi-period supply chain network. The developed model provides the possibility of opening or closing facilities at every time period to adapt to market fluctuations. The model also considers bank loans, liability repayment, and new capital from shareholders as decision variables, therefore, it provides an accounts payable policy for the company managers. In addition to common operational objectives(profit/cost) and constraints, we also applied the economic value added (EVA) index to measure the financial performance of supply chain and lower and/or upper limit value for financial ratios to ensure the company's financial health, while making decisions at strategic and tactical levels. To show the model applicability, data of a case study in the literature employed and solved using BARON solver in GAMS software. The results clearly show an improvement in the total value created for the company compared to the base model, so it can be applied as an effective decision tool. Manuscript profile -
Open Access Article
11 - An Agri-Fresh Food Supply Chain Network Design with Routing Optimization: A Case Study of ETKA Company
Navid Nasr Seyed Taghi Akhavan Niaki Mehdi Seifbarghy Ali Husseinzadeh KashanThe Supply Chain Network Design (SCND) with perishability is an active research topic. The Agri-fresh Food Supply Chain (AFSC) is a relevant topic to SCND and this study aims to model a new AFSC for a real-world case study. Regarding the traditional AFSC, the geographic MoreThe Supply Chain Network Design (SCND) with perishability is an active research topic. The Agri-fresh Food Supply Chain (AFSC) is a relevant topic to SCND and this study aims to model a new AFSC for a real-world case study. Regarding the traditional AFSC, the geographically dispersed small farmers transport their product individually to market for selling. This leads to a higher transportation cost, which is the major cause of farmers’ low profitability. This paper formulates a traditional product movement model to represent the existing AFSC. The concept of sharing economic approach is employed by the aggregate and collaborative transportation of products to minimize transportation inefficiency. This paper proposes an aggregate product movement with the vehicle routing model to re-design an AFSC for a case study in Iran based on the data of ETKA Company-the largest domestic agri-fresh food supply chain. A four-echelon, multi-period, Mixed Integer Non-Linear Programming (MINLP) approach for the proposed location-inventory-routing model is formulated for perishable products via considering the clustering of farmers to minimize the total distribution cost. Manuscript profile -
Open Access Article
12 - Multi-objective possibility model for selecting the optimal stock portfolio
Abdolmajid Abdolbaghi Ataabadi Alireza Nazemi Masoumeh SakiIn this paper, we use fuzzy numbers and possibility theory to model possibility. The purpose of this work is to determine the optimal investment model based on the neural network method for fuzzy LR, trapezoidal and triangular numbers in an optimal portfolio. It is list MoreIn this paper, we use fuzzy numbers and possibility theory to model possibility. The purpose of this work is to determine the optimal investment model based on the neural network method for fuzzy LR, trapezoidal and triangular numbers in an optimal portfolio. It is listed on the Tehran Stock Exchange to maximize "returns" and reduce "risk" to find the optimal portfolio. Therefore, to achieve this goal, the problem of multi-objective nonlinear programming is addressed. Also, by substituting the mean-variance model and the standard mean deviation instead of the Markowitz mean-variance model, the selection of the optimal portfolio in the possible space is examined. Finally, after calculating the model of the possibility of fuzzy numbers, we reach the optimal stock portfolio, which can be used to set the stock portfolio that has the highest returns and the lowest risk. Manuscript profile -
Open Access Article
13 - Designing and Evaluating Trading Strategies Based on Algorithmic Trading in Iran's Capital Market
Hamidreza Kordlouie Abbas Salehi Fard Mahdi Ebrahimi Moghaddam Shadi ShahverdianiOne of the important factors in making a profit through financial markets is a quick and correct response to market events, which is possible only by examining all aspects of the market. Today, to solve this challenge, the use of trading algo-rithms has become inevitabl MoreOne of the important factors in making a profit through financial markets is a quick and correct response to market events, which is possible only by examining all aspects of the market. Today, to solve this challenge, the use of trading algo-rithms has become inevitable and can be considered as transactions made by computers that these transactions are controlled and reviewed through algorithms. Depending on their type and purpose, these algorithms examine different aspects and, according to the strategies defined for them, make decisions and signal by order registration. These trading methods are growing rapidly in the world, espe-cially in strong and developed financial markets. Proper implementation of algo-rithmic transactions reduces transaction costs and increases the accuracy of inves-tors in their investments. One of the most widely used of these strategies is the trend-following strategy, which is welcomed by many traders. This strategy can be implemented in different ways and through different trading tools. In the pre-sent study, five types of them were examined and implemented on one of the most traded symbols of the Tehran Stock Exchange. The purpose of this study is to implement some of the popular strategies in algorithmic trading along with the introduction of algorithmic trading, its strategies in the Iranian stock market, which includes the study of its advantages and disadvantages. The present study is a cross-sectional retrospective and field survey in terms of applied purpose and in terms of data collection. Manuscript profile -
Open Access Article
14 - Determining the interest rate on deposits in the Iranian banking system: cooperative or competitive game between the central bank and followers?
Mehdi Memarpour Ashkan Hafezalkotob Mohammad Khalilzadeh Abbas Saghaei Roya SoltaniThis paper studies the monetary policies of the central bank to determine the inter-est rate on deposits in the interaction with the Iranian banking system in the form of Stackelberg and Nash equilibrium games. The leader of the game is the central bank of the Islamic R MoreThis paper studies the monetary policies of the central bank to determine the inter-est rate on deposits in the interaction with the Iranian banking system in the form of Stackelberg and Nash equilibrium games. The leader of the game is the central bank of the Islamic Republic of Iran, while the followers of the game include three banks called A, B, and C. The leader of the game regulates its monetary policies based on the relationship between inflation rate and interest rate on depos-its in the form of three scenarios of "legal deposit ratio", "legal deposit award rate", and "the rate of commissions received" from the followers. The follower players also determine "the interest rate on deposits," based on the scenarios of the leader player. The results of this research (2010-2019) by MINITAB Soft-ware indicated that in the studied year (2019), the strategy of the players of this game has been mostly Nash (more competitive) rather than cooperative. If the players of this game had chosen cooperative strategy (Stackelberg game), they would have achieved greater profit. Also, the optimal tool for the monetary policy of the leader and follower players has been the “increasing the legal reserve re-ward rate". Manuscript profile -
Open Access Article
15 - Portfolio optimization considering cardinality constraints and based on various risk factors using the differential evolution algorithm
Behnaz Ghadimi Mehrzad Minooei Gholamreza Zomorodian Mirfeiz FallahshamsAs the main achievement of the modern portfolio theory, portfolio diversifica-tion based on risk and return has attracted the attention of many researchers. The Markowitz mean-variance problem is a convex quadratic problem turned into a mixed-integer quadratic programmi MoreAs the main achievement of the modern portfolio theory, portfolio diversifica-tion based on risk and return has attracted the attention of many researchers. The Markowitz mean-variance problem is a convex quadratic problem turned into a mixed-integer quadratic programming problem when incorporating car-dinality constraints. Due to the high number of stocks in a market, this problem becomes an NP-hard problem. In this paper, a metaheuristic approach is pro-posed to solve the portfolio optimization problem with cardinality constraints using the differential evolution algorithm, while it is also intended to improve the solutions generated by the algorithm developed. In addition, variance, val-ue-at-risk, and conditional value-at-risk are assessed as risk measures. Candi-date models are solved for 50 top stocks introduced by the Tehran Stock Ex-change by considering the cardinality constraints of not more than five stocks within the portfolio and 24 trading periods. Finally, the obtained results are compared with the results of genetic algorithm. The results show that the pro-posed method has reached the optimal solution in a shorter time. Manuscript profile -
Open Access Article
16 - Investigating the effects of time variables of gold, crude oil and foreign exchange markets on herding behavior in Tehran Stock Foreign exchange
Sepideh Behnam Reza Tehrani Bita TabrizianDue to overlap between stock markets and financial markets, this study was an attempt to examine the herding behavior in the Iranian stock market and the crude oil, foreign exchange and gold markets. For this purpose, in this research, monthly data between 2011 and 2020 MoreDue to overlap between stock markets and financial markets, this study was an attempt to examine the herding behavior in the Iranian stock market and the crude oil, foreign exchange and gold markets. For this purpose, in this research, monthly data between 2011 and 2020 for Tehran Stock Foreign exchange were used. The results of the study based on two criteria explaining herding behavior indicate the existence of herding behavior of the stock market and crude oil, gold and foreign exchange markets. The results also show that it has had different ef-fects on herding behavior in different periods. This issue has also been different in increasing and decreasing market periods. Therefore, gold is introduced as an important asset that influences herding behavior. Also, during the decreasing period of the stock market, herding behavior is not affected by the exchange and crude oil market, and in this period, the behavior of investors and investment risks in the stock market can be predicted without considering the exchange and crude oil market. Manuscript profile -
Open Access Article
17 - Designing a Trading Strategy to Buy and Sell the Stock of Companies Listed on the New York Stock Exchange Based on Classification Learning Algorithms
Nasser Heydari Majid Zanjirdar Ali LalbarThis research investigated the development of a stock trading strategy for companies on the New York Stock Exchange (NYSE), a prominent global market. Data was acquired from established libraries and the Yahoo Finance database. The model employed technical analysis indi MoreThis research investigated the development of a stock trading strategy for companies on the New York Stock Exchange (NYSE), a prominent global market. Data was acquired from established libraries and the Yahoo Finance database. The model employed technical analysis indicators and oscillators as input features. Machine learning classification algorithms were used to design trading strategies, and the optimal model was identified based on statistical performance metrics. Accuracy, recall, and F-measure were utilized to evaluate the classification algorithms. Additionally, advanced statistical methods and various software tools were implemented, including Python, Spyder, SPSS, and Excel. The Kruskal-Wallis test was employed to assess the statistical differences between the designed strategies. A sample of 41 actively traded NYSE companies across diverse sectors such as financial services, healthcare, technology, communication services, consumer cyclicals, consumer staples, and energy were chosen using a filter-based approach on June 28th, 2021. The selection criteria included a market capitalization exceeding $200 billion and an average daily trading volume surpassing 1 million shares. Evaluation metrics revealed that the designed random forest trading strategy achieved a good fit with the data and exhibited statistically significant differences from other strategies based on classification learning algorithm. Manuscript profile -
Open Access Article
18 - The Modeling the Fixed Asset Investing with a Machine Learning Approach by Emphasizing the Role of Financial Criteria
Farzaneh SHamsdoost Omid Mahmoudi Khoshro Ataollah Mohammadi Malgharni Amir SheikhahmadiThe purpose of this research is to provide a growth model of fixed assets based on the financial criteria of companies admitted to the Tehran Stock Exchange. The current research is applied in terms of objective classification and descriptive-correlation in terms of met MoreThe purpose of this research is to provide a growth model of fixed assets based on the financial criteria of companies admitted to the Tehran Stock Exchange. The current research is applied in terms of objective classification and descriptive-correlation in terms of method. The research method is de-ductive-inductive. The statistical population of the current research is all the companies admitted to the Tehran Stock Exchange in the period from 2012-2021 and the financial information of 101 companies are use. Research hypotheses were tested using artificial intelligence algorithm. In this research, investment in fixed assets has been consider as a dependent variable, and financial criteria has been considered as primary independent variables. The results of research hypotheses testing using the methods of linear and non-linear algorithms of artificial intelligence PINSVR and KPLSR in predicting fixed asset investors of companies and by calculating the three errors criteria MAE, MSE and SMAPE in annual fixed assets. The asset forecasting in the next year of companies showed that the error difference between linear models and non-linear models is not so great that it can be claim that linear models are ineffective in predicting asset growth so that artificial intelligence algorithms are capable of predicting investment in company assets. Manuscript profile -
Open Access Article
19 - Determining the appropriate weights of criteria in multi-criteria decision-making using cooperative game: A case study of bank
Seyed Hadi Mousavi-Nasab Jalal Safari Ashkan HafezalkotobCriteria weighting is a crucial step in the entire decision-making process. Determining the appropriate weights will lead to more reliable results. This study aims to use a coalitional game method for calculating proper criteria weights in multi-criteria decision-making MoreCriteria weighting is a crucial step in the entire decision-making process. Determining the appropriate weights will lead to more reliable results. This study aims to use a coalitional game method for calculating proper criteria weights in multi-criteria decision-making (MCDM). In this paper, the Shapley value method is used to determine the weight of criteria. A numerical case study of 65 banks has been used to explain the efficiency of the proposed method. To this end, using the TOPSIS technique, the alternatives are ranked once in Shapley value and again in the Shannon entropy weighted matrix. Then the results are obtained applying Spearman rank correlation coefficient are compared to efficiency-based ranking using data envelopment analysis (DEA) as a powerful benchmarking method. In the proposed method, unlike many conventional weighting methods, the selection of criteria weights is made in a coalitional game with the participation of all criteria; the obtained weights are both intuitively and objectively fairer, and more reliable rankings are provided. According to the logical and fair calculation of weights, having a simple and understandable mathematical method, and no need for experts’ judgment, the proposed method can be used in real problems. Especially where realistic ranking has a significant impact on the equitable allocation and absorption of resources. Manuscript profile