financial ratio

Open Access Article

1 - An investigation of the smoothing of financial Ratios by management and the effect on decision users
R. Shabahang M. Hemmat far

The study investigates the smoothing of financial ratios by management and the effects offinancial in formation in accepted companies population in tehran securities exchange.In the study using deductive, inductive approach, firstly with expressing theoritical concepts More

The study investigates the smoothing of financial ratios by management and the effects offinancial in formation in accepted companies population in tehran securities exchange.In the study using deductive, inductive approach, firstly with expressing theoritical concepts andfirst model going toward details of study (Financial statement) ends to inductive result and statistictests.It is disscused two hypothesis in the study, according to theorical bases: which the first oneinvestigates existence financial ratio smoothing and the second one smoothing Analysis of variance(ANOVA) statistics method is used.For testing the first method panel data multiple regression is used For testing second hypothesies.Testing the first hypotesies indecated that financial ratios smoothing behavior in 5% significantlevel for some under the study years (76-81) observed for the most of the investigated.Financial ratios the second hypothesis indicated that the mentioned factors on smoothing index ofsome investigeted financial ratios were efficacious.Among these effective factors the most power Full Factors on financial ratios smoothing indexhas been Agency debt, and the most weak factor has been the size of company. Manuscript profile

Open Access Article

2 - Bankruptcy Prediction Using Artifical Neural Networks with Camparsion to the Altman Model
M.R. Setayesh D. Ahadianpoor Parvin

This research has been done under title: Bankruptcy Prediction using Artificsl Neural Networks withcamparsion to the Altman Model.The goal of this study is to provide exact explanation and presentation of theoretical basis of research andmeasurement of usefulness bankru More

This research has been done under title: Bankruptcy Prediction using Artificsl Neural Networks withcamparsion to the Altman Model.The goal of this study is to provide exact explanation and presentation of theoretical basis of research andmeasurement of usefulness bankruptcy financial models. We presented the research hypotheses in order toprovide suitable scientific context for the study.Hypothese 1: Artificsl Neural Networks and Altman models are suitable instrumental for prediction ofbankruptcy.Hypothese 2: In prediction of bankruptcy one firm, have significant difference the resultsof this two models.The means of the research statements (Balance sheets, Income statement, cash flow statement) of thecompanies which were accepted in Tehran Stock Exchange. The library method was employed in datagathering. Statistical population of research includes active companies whose financial statements areaccessable in Tehran Stock Exchange. The statistical sample of the research includes active companies inproductive industries, from 1379 to 1384.In order to analysis data, We used statistical metods of nonparametric binomial, and for cointegrationsignificant difference two models employed wilcoxon signed- rank test and sign test for hypothese 2. Afteranalyzing the data the results gained id confirmed and supported by above tests Manuscript profile

Open Access Article

3 - Provide financial policy by predicting financial statement fraud
Seyed jalal Ahmadi Khosrow Faghani Makrani Naghi Fazeli

Background: Management responsibility is creating the right organizational climate in which fraud is the worst crime. methods of identifying fraud play an important role in preventing fraud. Objective: To provide financial policy to management in predicting financial fr More

Background: Management responsibility is creating the right organizational climate in which fraud is the worst crime. methods of identifying fraud play an important role in preventing fraud. Objective: To provide financial policy to management in predicting financial fraud by using neural network data mining Research method: Descriptive-applied research method and time domain is also from 2008 to 2017. In this study, financial ratios for both fraudulent and non-fraudulent samples and network data mining were analyzed. Pearson's correlation coefficient was then examined for the model linearity for financial ratios and the elimination of independent correlated variables. In the next step, the neural network method was used to provide financial policy to management regarding the prediction of financial statement fraud. Findings: The decision tree method is effective in providing financial policy to management in predicting financial statement fraud. Conclusion: Since the decision tree method has 65.4% correct forecast, it can be effective in providing financial policy to management to predict fraud. Manuscript profile

Open Access Article

4 - The study of effective factors on probability of default banks' credit facilities (The case study of legal customer of Export Development Bank of Iran)
شمس اله شیرین بخش ندا یوسفی جهانگیر قربان زاد

The aim of this research is to verify effective factors of legal counterparty creditrisk of Export Development Bank of Iran (EDBI), and design a probability of defaultmeasurement model using logit regression.330 probability samples were selected from companies that took More

The aim of this research is to verify effective factors of legal counterparty creditrisk of Export Development Bank of Iran (EDBI), and design a probability of defaultmeasurement model using logit regression.330 probability samples were selected from companies that took loans in year 1387(2008-2009) including 256 good pay bank customers and 65 bad pay bank customers.Seven variables have been recognized which have significant influence atcompanies' credit risk among 13 selected financial ratios as effective explanatoryvariables in default probability based on statistics indexes and economic and financialtheories. after significant examining total of the regression with LR statistic finalmodel in 5% level of significance created by them.The results expressed that cash flow on total debt ratio (CSDT), assets turnoverratio (SATA), current ratio (CACD) and liquidity ratio (LR) have a reverse effect oncredit risk. Free cash flow ratio (RETA), total debt ratio (TDTE) and current debts tonet worth ratio (CDTE) have a direct effect on credit risk. Manuscript profile

Open Access Article

5 - Evaluating the Performance of Companies Listed in Tehran Stock Exchange based on Financial Ratios Using DEA (The Case of Chemical & Medical Company)
Younos Vakil Alroaia

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Open Access Article

6 - The investigation of effecting Factors on the issue of qualified auditing report: Application of neural network method
پیمان امینی کامران محمدی شعیب عباسی

Nowadays, competition has a fundamental role in auditing profession. Hence, thetime and cost reduction and auditing quality enhancement are necessary viaapplication of management principles and techniques. The main propose of this paper,the investigating of effecting Fa More

Nowadays, competition has a fundamental role in auditing profession. Hence, thetime and cost reduction and auditing quality enhancement are necessary viaapplication of management principles and techniques. The main propose of this paper,the investigating of effecting Factors on the issue of qualified auditing report and inorder to, determined 7 of Financial and 2 Non- Financial Variables used in reliableresearches. In order to data analysis, the new model of neural network is used and theinput variable method is applied to determine the significance of relationship betweenvariables.The results revealed that net profit to sale ratio maximum relationship, and there aftercurrent ratio, the ratio of total liabilities to total assets, firm size, the qualifications oflast year report, the ratio of accounts receivable to total assets, the number of timesinventory rated, quick ratio and type auditing institute had significant effect on theissue of qualified auditing report. Manuscript profile

Open Access Article

7 - Factors Affecting the Transparency of Financial Information in the Insurance Industry
Amirreza Nematolahi Roya Darabi Fatemeh Sarraf Yadollah Nouri fard

There are many factors in the transparency of financial information, the most important and most effective of which are financial components. In this research, we merely consider financial insurance agents in transparency of financial information because of, insurance a More

There are many factors in the transparency of financial information, the most important and most effective of which are financial components. In this research, we merely consider financial insurance agents in transparency of financial information because of, insurance accounting specific nature.The purpose of this study was to investigate the effective relationship between financial insurance factors and financial information transparency of the insurance industry.To determine the final financial components of insurance, experts of the insurance industry were consulted and a researcher-made questionnaire was used to collect data.The research sample consisted of 151 managers and experts in the insurance industry selected by random sampling method. The realm of this research is 2017 and city of Tehran. One-sample t-test was used to analyze the data in a small phase.The results indicate that financial insurance factors have a meaningful relationship with the transparency of financial information in the insurance industry, but violations were also found in the research components.The results of the ranking showed that the disclosure of leverage ratios and deferred loss accounts has the highest degree of significance. Manuscript profile

Open Access Article

8 - The Ranking of Financial Efficiency of Companies Accepted in Stock Exchange of Tehran between 2013 to 2016 through Financial Ratio Approach and Using DEA
Abbas Sheikh Abomasoudi Seyyed AmirHossin Mirghaderi

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Open Access Article

9 - Evaluating the Efficiency of Two-stage Networks using Ratio Analysis
Asieh sadat Hatami Morteza Shafiee Mozhdeh Rabbani Mohammad Reza Mozaffari

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Open Access Article

10 - A Model to Predict Bankruptcy using the Mechanisms of Corporate Governance and financial ratios
ghazaleh Alibabaee Hamed Khanmohammadi

Improving the economic and business environment is the most important factor in preventing bankruptcy, therefor, Artificial intelligence uses to predict the bankruptcy of companies in the future. In this study, companies in the Tehran Stock Exchange over a period of 10 More

Improving the economic and business environment is the most important factor in preventing bankruptcy, therefor, Artificial intelligence uses to predict the bankruptcy of companies in the future. In this study, companies in the Tehran Stock Exchange over a period of 10 years in terms of bankruptcy localized model of Kurdistani-Tatli based on the Altman model were examined and companies were identified as bankrupt and healthy. Research data were collected, categorized and refined using secondary data extracted from financial statements and through the database of the Exchange Organization and the Central Bank.The models used to evaluate the data and predict the bankruptcy of companies are artificial intelligence models . Artificial neural network, combination of neural network and genetic algorithm and the K-nearest neighbor method has been used. They were also compared in terms of prediction accuracy. The output of the models indicates that the addition of corporate governance indicators to the financial ratios indicators has not improved the results. Therefore, financial ratios alone are sufficient for predicting and determining bankruptcy. The proposed model of this research based on accuracy is a combined model of neural network and genetic algorithm that has the highest accuracy. Genetic algorithm improves the optimal results of the neural network and provides a more optimal answer. Manuscript profile

Open Access Article

11 - Comparing the superiority of Glomar stock using multi-criteria decision-making models, Taxonomy and PROMETHEE
farzaneh hashemloo hashem nikoumaram taghi torabi

The distribution of capital market resources depends on the presence of market participants, and the main issue we are facing is the decision to allocate resources, the selection of suitable securities for investment, and the formation of optimal stock portfolios. The d More

The distribution of capital market resources depends on the presence of market participants, and the main issue we are facing is the decision to allocate resources, the selection of suitable securities for investment, and the formation of optimal stock portfolios. The development of new techniques in operational research and financial science, along with advances in computer science and technology, has led to the emergence of models, including multi-criteria decision-making models for selecting stock portfolios.Based on the fundamental analysis of stock valuation, 18 financial ratios in 6 groups of profitability, liquidity, activity, leverage, market value, and ownership were used to evaluate 30 companies during 2011-2017. Two methods, Taxonomy and PROMETHEE, is done to rank the sample shares and compare the result. The results showed that the ranking of the Shannon- PROMETHEE entropy model in comparison with the taxonomic-factor analysis models has a better prediction of stock returns. Manuscript profile

Open Access Article

12 - Modeling Customers Credit Rating Based on Life Cycle and Financial Ratios: Approach of Discriminant Analysis
abdolreza valiolahi vahidreza mirabi mohmmad hosein ranjbar

The aim of this study was to present a model of legal customers credit rating based on financial ratios and firm life cycle. The statistical population of research consist the all legal customers of bank of industry and mine in 2019 in a number of 132 firms. So, a numbe More

The aim of this study was to present a model of legal customers credit rating based on financial ratios and firm life cycle. The statistical population of research consist the all legal customers of bank of industry and mine in 2019 in a number of 132 firms. So, a number of 11 financial ratios beside of firms’ life cycle were studied through the analysis of variance test, independent test of chi-square and discriminant analysis and the results showed that firms’ financial ratios in different credit rates, are statistically different. Also the findings indicated that there is significant relationship between firms’ life cycle and credit rates and distinguished through discriminant analysis that using this method and estimating discriminant functions can determine the credit rate of firms with the accuracy of 97.7 percent. Manuscript profile

Open Access Article

13 - Modeling The Effective variables on investment efficiency: evidence from Tehran Stock Exchange.
Zahra Tahmooresi qodratallah talebnia Rasoul Baradaran Hassanzadeh Nemat Allah Mousavi hamidreza vakilifard

The main aim of this study is to present a pattern for determining and measuring investment efficiency in accordance with the market conditions of Iran. To do so, studying previous studies and thematic literature, 17 variables were identified to present an optimal inves More

The main aim of this study is to present a pattern for determining and measuring investment efficiency in accordance with the market conditions of Iran. To do so, studying previous studies and thematic literature, 17 variables were identified to present an optimal investment efficiency model. Using panel data and the use of eviews9 & stata 14 software, it was suggested to provide a concrete investment efficiency pattern based on the cash flow of investment activities was undertaken. The statistical population of this study includes 129 companies listed on the stock exchange during the time period of 2007- 2016. Finally, the final model of the research, with the abbreviation title of (ineff) and the participation of 11 variables including company size, leverage, company's age, Qtubin, sales growth, return on assets, ratio of operating profit to assets, ratio of operating cash flow to assets, liquidity ratio, standard deviation of operating cash flows and cash ratio with a coefficient of 45% was estimated Manuscript profile

Open Access Article

14 - Ranking P/E Predictor Factors In Tehran Stock Exchange With Using The Harmony Search Meta Heuristic Algorithm
Mozhgan Safa Hossein Panahian

The price to Earnings ratio (PE) is one of the oldest and most commonly used tools for stock valuation.  Although P / E calculation is very simple, its interpretation is practically difficult. In certain circumstances, this is a very rational ratio, and at other ti More

The price to Earnings ratio (PE) is one of the oldest and most commonly used tools for stock valuation.  Although P / E calculation is very simple, its interpretation is practically difficult. In certain circumstances, this is a very rational ratio, and at other times it is completely meaningless. Hence, investors often use this term incorrectly and in their decisions weigh too much. The important thing that can help investors analyze this ratio is to pay attention to the criteria approved by financial experts. Based on the analysis of financial ratios, there are various methods and techniques for determining the factors affecting the price / profit ratio (P / E) of stocks .One of these methods is to use the key variables of the company and its fundamental analysis .In this research, the Harmonic Cross-Innovative Algorithm (HS) has been used to examine the effective measures on the P / E ratio .For this purpose, a sample of 87 companies during the 10-year period (2006-2015) was selected from listed companies in Tehran Stock Exchange . By studying theoretical fundamentals and research background, 27 financial variables that were effective on the P / E ratio were selected. The outputs of the Harmonic Ranking algorithm showed that stock returns, P / B and P / S ratios had the highest impact and coin prices had the least effect on P / E ratios, respectively.   Manuscript profile

Open Access Article

15 - Credit rating of manufacturing corporations in Tehran stock exchange withmulti-criteriadecision-makingandartificial neural network models
Maghsoud Amiri Morteza Bakyhoskoie Mehdi Biglari Kami

This paper is investigated the credit rating of manufacturing firms in Tehran Stock Exchange. In this regard, have been extracted  financial ratios of  public stock companies during the three years from the financial statements. This financial ratios indicates More

This paper is investigated the credit rating of manufacturing firms in Tehran Stock Exchange. In this regard, have been extracted  financial ratios of  public stock companies during the three years from the financial statements. This financial ratios indicates the ability to pay principal and interest of loan. Initially, 50 companies were selected and ranked by the TOPSIS method. Financial ratios are as a criterion and weight of the each criterion are determined by using Shannon entropy method. Then the ranking, companies are classified into four categories. The artificial neural network is trained to classify and after training the neural network are tested. Statistical results show robust classification of neural network. Then all the companies included in this study are classified by neural network. Manuscript profile

Open Access Article

16 - Developing a Model for the Assessment and Evaluation of Financial Health in Iran
Mohammad Reza Pourali

Financial health is defined as capability of making  profit and the continuation of industrial entity activity. This research aims at the determination and recognition of financial components and features affecting health and presentation of a model based on Multin More

Financial health is defined as capability of making  profit and the continuation of industrial entity activity. This research aims at the determination and recognition of financial components and features affecting health and presentation of a model based on Multinomial logistic Regression (MLR) approach to assess and evaluate financial health in Iran. companies in this research have been divided into three groups as to their financial health state called; healthy, intermediate and distressed.In order to test the accuracy of prediction and trath-value of the extracted model , the selected companies at every level of health were divided as symmetrical pairs in to control and experimental groups.Using Excel software 15 financial ratios were calculated in 5 states of liquidity, leverage, activity , market value and Value creation . SPSS (17) was used to test hypotheses , (ANOVA) and Kruskal-Wallis statistical variance analysis to compare the average and SD of ratios at 5% level of error. Research findings show that there is significant statistical differences among these companies according to different levels of financial health based on leverage, activity and market value ratios. But the liquidity and  Value creation  state difference of these three levels is significant and the components affecting financial health are as quick ,current , debt , the proportion of net working capital to total assets ratios, EVA and MVA.  Based on Dunnett and Tukey tests the distressed companies are the factors yielding the difference. i.e. distressed companies are statistically on one side and intermediate and healthy ones on the other side of distribution. As a resalt two models were presented, one for distressed companies and another one for intermediate and healthy ones. The test of model prediction accuracy in the experimental group at three levels of distressed , intermediate , healthy and total are subsequently 70% , 92% , 100%, 88.88% and shows 66% , 79.16% , 77.7% and 76.92% of prediction accuracy and classification in the control group. Manuscript profile

Open Access Article

17 - Purchasing stock in Stock Exchange (Application of MADM Models)
Abbas Toloie-Eshlaghy Iman Gharib Keyvan Dadras Davood Gharakhani

Investors based on financial ratios analysis of bourse companies can choose and purchase different company to invest. This study suggests use of MADM techniques to assist investors to make decision on investing. In this study we try to improve analysis of financial rati More

Investors based on financial ratios analysis of bourse companies can choose and purchase different company to invest. This study suggests use of MADM techniques to assist investors to make decision on investing. In this study we try to improve analysis of financial ratios with MADM techniques .We select 25 Cement companies from Tehran Stock Exchange. We collect required data from 1385 till 1389 from audited basic financial statement. At first determine weight of indicators with use of Entropy technique and then we can rank studied companies from financial indicators points of view with TOPSIS،ELECTRE & VIKOR and then with Copeland we rank them. The survey results show that the Cement companies of Ilam, Fars, Iran ghach, Khazar, Hormozgan, Kordestan are the highest ranking and results show that the Cement companies of Isfahan, Urmia, Ardebil, Hormozgan, and Behbahan are the lowest ranking. Finally، "The results of this study can help investors to choose superior company for investment with financial statement perspective.                                              Manuscript profile

Open Access Article

18 - Predicting Liquidity Trap in Companies with Financial Clinic Approach
Mahnaz Nojavan Mahmoud Lari

Financial reporting has significant attention for users. The main objective of financial reporting is to provide information to predict cash flows and  to assess the financial position.One of the tools uses to determine the company's financial position is analysis More

Financial reporting has significant attention for users. The main objective of financial reporting is to provide information to predict cash flows and  to assess the financial position.One of the tools uses to determine the company's financial position is analysis of financial ratios. Financial ratios are designed to help evaluation of  financial statements. Managing  of the company's liquidity is one of  the most important duties of senior executives and the amount and speed of rotation of the liquidity of a company makes it profitable and competitive. The main objective of this research is to explain model predictions of liquidity traps and to review the relationship between liquidity trap  with financial clinic approach in companies listed in Tehran stock exchange during the period of 2010 -2014. In this regard, four hypotheses developed by using correlation and regression analysis. The results of the research indicate that there is significant relationship of time by creating Liquidity trap between the lack of favorable efficiency,  unfavorable combination of current assets, lack of effective follow-up collection of receivables and other ill treatment cost - but it is not meaningful.    Manuscript profile

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19 - Financial Assessment of Banks and Financial Institutes in Stock Exchange by Means of an Enhanced Two stage DEA Model
Mohammad Izadikhah

10.22034/amfa.2020.1910507.1491

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20 - Presenting a New Bankruptcy Prediction Model Based on Adjusted Financial Ratios According to the General Price Index
Naimeh Jebelli Iman Dadashi Mohammad Javad Zare Bahnamiri

10.22034/amfa.2020.1884838.1339

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21 - Evaluating the Factors Affecting on Credit Ratings of Accepted Corporates in Tehran Securities Exchange by Using Factor Analysis and AHP
Ahmad Mohammaddoost Mir Feiz Falah Shams Dialestani Madjid Eshaghi Gordji Ali Ebadian

10.22034/amfa.2020.1899553.1421

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22 - Financial Performance Evaluation of Companies Using Decision Trees Algorithm and Multi-Criteria Decision-Making Techniques with an Emphasis on Investor’s Risk-Taking Behavior
Zinat Ansari Rezvan Hejazi Yaghoob Zeraat kish Zabihallah Khani Masoum Abadi

10.22034/amfa.2020.1897171.1405

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23 - Experimental Comparison of Financial Distress Prediction Models Using Imbalanced data sets
Seyed Behrooz Razavi Ghomi Alireza Mehrazin Mohammad Reza Shoorvarzi Abolghasem Masih Abadi

10.22034/amfa.2021.1905055.1461

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24 - Developing Financial Distress Prediction Models Based on Imbalanced Dataset: Random Undersampling and Clustering Based Undersampling Approaches
Seyed behrooz Razavi ghomi Alireza Mehrazin Mohammad reza shoorvarzi Abolghasem Masih Abadi

10.22034/amfa.2022.1956898.1743

So far, distress prediction models have been based on balanced, such sampling is not consistent with the reality of the statistical community of companies. If the data are balanced, the bias in sample selection may lead to an underestimation of typeI error and an overes More

So far, distress prediction models have been based on balanced, such sampling is not consistent with the reality of the statistical community of companies. If the data are balanced, the bias in sample selection may lead to an underestimation of typeI error and an overestimation of the typeII error of models. Although imbalanced data-based models are compatible with reality, they have a higher typeI error compared to balanced data-based models. The cost of typeI error is more important to Beneficiaries than the cost of typeII error. In this study, for reducing typeI error of imbalanced data-based models, random and clustering-based undersampling were used. Tested data included 760 companies since 2007-2007 with 4 different degrees and the results of the H1 to H3 test represented them. In all cases of the typeI error, typeII error of balanced data-based models were lower and more, respectively, compared to imbalanced data-based models; also, in most cases, the geometric mean of balanced data-based models was higher compared to imbalanced data-based models, respectively. The results of testing H4 to H6 show that in most cases, typeI error, typeII error and the geometric mean criterion of models based on modified imbalanced data were less, more, and more, respectiively compared to the models based on imbalanced data, in other words, applying Undersampling methods on imbalanced training data led to a decrease in typeI error and an increase in typeII error and geometric mean criteria. As a result using models based on modified imbalanced data is suggested to Beneficiaries Manuscript profile

Open Access Article

25 - A mathematical model to predict corporate bankruptcy using financial, managerial and economic variables And compare it with other models
Jafar Zarin Babak Jamshidinavid Mehrdad Ghanbari Afshin Baghfalaki

10.22034/amfa.2021.1916300.1526

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Open Access Article

26 - Early Warning Model for Solvency of Insurance Companies Using Machine Learning: Case Study of Iranian Insurance Companies
Saeed Naseri Khezerlou Atousa Goodarzi

Stakeholders of an organization avoid undesirable outcomes caused by ignoring the risks. Various models and tools can be used to predict future outcomes, aiming to avoid the undesirable ones. Early warning models are one of the approaches that could help them in doing s More

Stakeholders of an organization avoid undesirable outcomes caused by ignoring the risks. Various models and tools can be used to predict future outcomes, aiming to avoid the undesirable ones. Early warning models are one of the approaches that could help them in doing so. This study focuses on developing an early warning system using machine learning algorithms for predicting solvency in the insurance industry. This study analyses 23 financial ratios from Iranian general insurance companies listed on the Tehran Stock Exchange between 2015 and 2020. The model uses Decision Tree, Random Forest, Artificial Neural Networks, Gradient Boosting Machine and XGBoost algorithms, with Boruta as a feature selection method. The dependent variable is the solvency margin ratio, and the other 22 ratios are the independent variables, which Boruta reduces to 7 variables. Firstly, the performance of the machine learning models on two datasets, one with 22 independent variables and one with 7, is compared based on RMSE values. The XGBoost algorithm performs the best on both data sets. Additionally, the study predicts the 2020 values for 19 insurance companies, performs stage classifications, and compares actual stages to predicted stages. In this analysis, Random Forest has the best estimate accuracy on both data sets, while Gradient Boosting Machine has the best estimate accuracy on the Boruta data set. Finally, the study compares the machine learning models' results in terms of capital adequacy classification, where Random Forest performs the best on both data sets, and Gradient Boosting Machine on the Boruta data set. Manuscript profile

Open Access Article

27 - Predicting Social Responsibility Reporting using Financial Ratios
Mohammad Javad Zare Bahnamiri mahsa golkar niloofar Beiky

The purpose of this research is to investigate the prediction of corporate social responsibility reporting using financial ratios. To answer the research question, four prediction models of linear regression, K Nearest Neighbor, decision tree, and deep learning were inv More

The purpose of this research is to investigate the prediction of corporate social responsibility reporting using financial ratios. To answer the research question, four prediction models of linear regression, K Nearest Neighbor, decision tree, and deep learning were investigated. Also, 61 financial ratios were used according to previous research using data related to listed and non-listed companies of Iran from the years 2012 to 2018. According to the re-sults obtained from the estimation of each of the proposed prediction mod-els, it can be stated that the k-nearest neighbor model has the lowest RMSE value, and in fact, this model predicts the amount of social responsibility with less error than other models. The linear regression model with the high-est RMSE value has a weaker performance than other models. LSTM model and decision tree respectively had the lowest RMSE value after the k-nearest neighbor model. As a result, since the LSTM model requires a large number of test sam-ples for deeper learning, it could not achieve high performance in the evaluated data set. Based on the investigations, it can be stated that the current research does not have a similar example inside or outside of Iran. Manuscript profile

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28 - Investigate Factors Affecting on the Performance of Agricultural Machinery Companies Based on Taxonomy Algorithm
Vahide Hajihassani

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29 - A Learning Automaton Based Algorithm for Bankruptcy Prediction of Acceptable Firms within Power and Energy Exchange
Seyed Mahdi Mazhari Hassan Monsef Hooman Mirzaei

In today's world, insurance of productive capital investment and reducing economic risk causes more fundraising and therefore the greatest economic boom cycle. One way to arrive capital investment security is to predict bankruptcy of a business unit. As the Iranian powe More

In today's world, insurance of productive capital investment and reducing economic risk causes more fundraising and therefore the greatest economic boom cycle. One way to arrive capital investment security is to predict bankruptcy of a business unit. As the Iranian power and energy stock is going to start working by 2012, providing suitable bits of advice to investors would be a priority. This paper proposes a new solution approach for bankruptcy prediction of the Iranian power and energy industries. To do so, an evolutionary algorithm premised on Learning Automata is employed and adapted to the problem. Two sets of firms related to power and energy industries that are listed on the Tehran Stock Exchange (TSE) are selected as the training and test data, respectively. The developed algorithm is conducted on both train and test data, and the efficiency of the proposed method is evaluated via several scenarios. It was practically seen in simulations that the learning automata-based algorithm could achieve an accuracy of 91% and 88% over the train and test data, respectively. Besides these, the same data sets are also conducted by other methods such as MDA and Logit, and the obtained results are compared with reality. The yielded results prove the accuracy as well as the efficiency of the proposed solution technique   Manuscript profile

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30 - An Investigation on the Impact of the Financial Ratios and Growth Rates on Future Abnormal Stock Returns (Case Study: Companies Listed in the Cement Industry)
Delir Nasera-badai Bizhan Khazduzi Omid Mahmoudi Khoshroo

This survey has been done among companies listed in the cement industry in Tehran Stock Exchange during eight years from 1380 to1388. The paper studies the effect of the simultaneous use of financial ratios and growth rates on future stock returns which is proven unusua More

This survey has been done among companies listed in the cement industry in Tehran Stock Exchange during eight years from 1380 to1388. The paper studies the effect of the simultaneous use of financial ratios and growth rates on future stock returns which is proven unusual. The data has been collected by using the new software named: “Rahavard Novin”. The results are based on the after event method and using F and T-tests and linear regression statistical analysis. The results show that the hypothesis has not been confirmed yet. That is, the use of financial ratios and growth rates do not affect future abnormal stock returns simultaneously. Using stepwise regression test, the final model was driven. Thus, only the operational ratios do not have simultaneous effects on the use of financial ratios. Finally, the results obtained from the overall test of the research hypotheses do not confirm the simultaneous impact of the financial ratios on future abnormal stock returns. However, the items in the financial statements reflect the accrual impact of items of financial statements on the process of economic decision making, the influence of the information content of all items is not the same. In other words, liquidity ratios have the highest effect and other ratios like profitability, investment and operational ratios reportedly have high effects on the abnormal stock returns.   Manuscript profile

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31 - Using integrated Fuzzy Multi-Criteria decision making model for evaluation and ranking the manufacturing firms in Tehran Stock Exchange
Ali Mohtashami Rahman Hasan Alipoor Heris

This paper aims to evaluate the financial performance of manufacturing industries member of the Tehran Stock Exchange.The MCDM method is applied to Evaluate five industry members of the Tehran Stock Exchange. Each industry includesseveral companies. Evaluation criteria More

This paper aims to evaluate the financial performance of manufacturing industries member of the Tehran Stock Exchange.The MCDM method is applied to Evaluate five industry members of the Tehran Stock Exchange. Each industry includesseveral companies. Evaluation criteria in this study were identified using literature research and data are needed for the years1386 to 1391, the Tehran Stock Exchange databases were collected. FAHP method is applied to determine the weight ofcriteria. After determining the weight of criteria, TOPSIS and VIKOR are applied as compromised methods to evaluate thecompanies. In the compromised method the distances of positive ideal solution and negative idea solution are consideredsimultaneously. On the other hand, the maximum distances of ideal solution are also considered. Finally, using the result ofTOPSIS and VIKOR and then taking advantage of the linear assignment method, and the results of calculations carried outpriorities final step after each stage is given. In the end, the conclusion is presented. Manuscript profile

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32 - The Comparison of Bankruptcy Predicting Power Models by Zaougin, Zmijewski and Shirata in Tehran Stock Exchange
Farzin Rezaei Mehdi Goldooz

Bankruptcy anticipation is a phenomenon which has been increasingly favored by investors, banks and financial and credit institutes. Since the potential signs of bankruptcy would be understood a few months before the real appearance of it, so the timely and accurate ant More

Bankruptcy anticipation is a phenomenon which has been increasingly favored by investors, banks and financial and credit institutes. Since the potential signs of bankruptcy would be understood a few months before the real appearance of it, so the timely and accurate anticipation of this crisis will give the opportunity to managers and creditors in order to adopt preventable activities. The aim of this study was to explore the applicability of the Zaougin, Zmijewski and Shirata’s models. Initially, the independent variables of the two samples were investigated, using F test to review the accuracy of segregation of two bankrupted and un-bankrupted  samples and then to examine the difference in importance of independent variables models, the magnitude of cooperation in group between variables. Sample selection and suitability of variables with less error criteria and meaningful cooperation test was carried out. Data were run using two statistical difference analysis and logistic regression (in three methods, inter, forward and backward). The results indicate the accuracy of Shirata’s model at 98.6%, Zaougin’s model at 87% and Zmijewski model at 89.6% in accordance with Iran environmental conditions Manuscript profile

Open Access Article

33 - Business Restructuring as a Method of Strengtening Company’s Financial Position
Inese Mavlutova Vitalina Babenko Volodymyr Dykan Nataliia Prokopenko Sergiy Kalinichenko Iryna Tokmakova

10.22094/joie.2020.677839

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Open Access Article

34 - The Comparative Investigation of Financial Ratio Effects on Decision-making of Bank Managers (Governmental and Private) by the Use of Analytical Hierarchy Process (AHP) Technique
Rasoul Baradaran Hassanzadeh Farhad Nejhad Irani Mahrokh Lotfollahi Haggi

The managers and the experts who give credit to the customers are the two groups for whom the financial information relavent to performance is so important. Accordingly, they consider some information like financial ratios to investigate the status of the company on the More

The managers and the experts who give credit to the customers are the two groups for whom the financial information relavent to performance is so important. Accordingly, they consider some information like financial ratios to investigate the status of the company on the basis of which they make the appropriate decision. Analyzing the financial ratios has been done since a long time ago. In this study, at first, the importance of the different financial performance criteria was investigated by considering the ideas of the bank experts and by using the technique of AHP. After that, the ratios were put in order of priority and the four main groups were considered in order to get the ideas of the experts and the managers ofthebanks(public and private),therateofincompatibilitywas computed.It is clear that ordering in priority could be used as a suitable guide for the experts and the managers of both private and public banks, according to which they can consider the financial ratios to give credit to their customers and compare it with the ranking technique of horizontal ordering. This study was done to find the difference between the main changes of financial performance, and tried to find a sound relationship between liquidity, efficiency, investment, and profitability among the public and private banks. By using the statistical ways of computing the analysis of variance tow-way within-subjects (ANOVA), it was found that there is no difference between the general financial operations and the decision of the managers of the private and public banks of the two provinces; West Azerbaijan and East Azerbaijan. Then,By using the T-test  it was found that there is no difference between the sub financial operations (such as liquidity, profitability, efficiency and investment) that may affect the decision making process of the bank managers of the private and public banks of the two provinces;West Azerbaijan and East Azerbaijan. Manuscript profile

Open Access Article

35 - Evaluating the Effect of Financial Health Indexes from the Aspect of Inhibiting and Opportunistic Behaviors of Income Management in Companies with Different Investment Opportunities
Omid Sabaghiyan Toosi Zahra Moradi Shohreh Yazdani

This research has compared effect of financial health indicators from the perspective of deterrence and opportunism in income management behaviors, based on the analysis of data from 320 companies during the years 2010-2020 using Eviews software in companies with differ More

This research has compared effect of financial health indicators from the perspective of deterrence and opportunism in income management behaviors, based on the analysis of data from 320 companies during the years 2010-2020 using Eviews software in companies with different investment opportunities. To test the hypotheses of the statistical population using the middle of 4 methods MEQLDTA, MB, PPEQGMEQLD and GrowthPPE, and classified into two groups of companies with high and low investment opportunities. Hypotheses tested in OLS and ARMA methods. Then, based on the cumulative analysis of financial health factors, these variables were weighted. The results show that the variables of ROA with weight of (-7), RER with weight of (-4) and LDR with weight of (-3) were respectively effective in playing the role of deterrent from income management motivation. On the other hand, variables of LEV with weight of (+6), DLOSS with weight of (+5) and INDIR with weight of (+4) were respectively recognized as effective factors on the opportunistic behavior of income management in companies with different investment opportunities. In companies with low investment opportunities that are separated by MB method, based on the optimal value of the coefficient of determination and the negative relationship of financial health indicators, it is more likely that this group has high financial health based on the inhibition of income management’s motivation. On the other hand, the findings show that in companies with low investment opportunity separated by the Growthppe method, the opportunistic behavior of income management is more evident. Manuscript profile

Open Access Article

36 - Choosing the Best Company for Investment According To the Financial Factors in the Neutrosophic Environment (Case Study: Automotive Industry)
Mohsen Imeni Bardia Pouresmaeil Motlagh Faezeh Pirouz Azadeh Shemshad

10.30495/fomj.2023.1971807.1081

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Open Access Article

37 - Using of Dupont Analysis with Emphasis on Earnings Management and Performance Management in predicting profitability of the insurance industry
Seyed fakhreddin Fakhrhosseini Meysam Kaviani

One of the goals of financial reporting is to provide useful information to facilitate decision making. Accounting information system is one of the sources of information provision for users to decide. The use of the Dupont analysis as a tool for measuring performance d More

One of the goals of financial reporting is to provide useful information to facilitate decision making. Accounting information system is one of the sources of information provision for users to decide. The use of the Dupont analysis as a tool for measuring performance dates back to the 1920s and its ability to use it to predict profitability is one of the interesting issues of financial management and investment. The present article seeks to answer the question of whether the components of the Dupont ratio, with emphasis on profit and performance management, can be used to predict operating profitability in the insurance industry. So, in order to investigate this, 14 insurance industry companies were selected as systematic sampling method. The data collected during a period of 6 years and between 2015 and 2020 are taken into account that the results of regression analysis show that the marginal changes in earnings at 99% confidence level have a significant effect on future profitability as well as performance management It can affect the profit margin through the margin of profit, and profit management (upward and downward) does not affect the profit margin on future profitability Manuscript profile

Open Access Article

38 - Estimating the Efficiency of Banks by DEA Approach and Investigating its Relationship with Financial Ratios
Fatemeh Mesgarpour Amiri Naser Yadollah zadeh Tabari

The evaluation of performance of banks due to its crucial role in most economic activitiesand health maintenance of financial markets and economic conditions has always been considered On the other hand, because of the responsibility of DEA models - especially in d More

The evaluation of performance of banks due to its crucial role in most economic activitiesand health maintenance of financial markets and economic conditions has always been considered On the other hand, because of the responsibility of DEA models - especially in detecting and determining the efficiency of banks has led to the use of the above-mentioned models is extensive. The goal of this article is to offer DEA for evaluating the performance of banks. Efficient and inefficient banks have been identified and finally, for the inefficient banking units the reference model has been introduced. In addition, the relationship between financial ratios and efficiency has been studied. The results show that 9 of the 20 units were efficient and the rest were inefficient. 8 financial ratios are presented: capital adequacy ratio, profitability ratios, management ratio and the asset quality ratio had the most direct relationship with performance. Manuscript profile

Open Access Article

39 - The Value Relevance of Information in Annual and Interim Financial Statements in Tehran Stock Market
M. MoradzadehFard M. Alemi S. Behzadpoor

The main goal of investors is achieving wealth and it realizes through stock return. Therefore evaluating stock return is a main matter in stock market. So providing required information to interpret firm's condition and profitability is a primary purpose of financia More

The main goal of investors is achieving wealth and it realizes through stock return. Therefore evaluating stock return is a main matter in stock market. So providing required information to interpret firm's condition and profitability is a primary purpose of financial reporting. Accordingly financial statements and supply notes are important information resource for investors. The objective of this study is examining the value relevance of information in annual and interim financial statements to explain stock return .This research investigates the relationship between financial reports information and abnormal return by using financial ratios, firm's size and cash flow from operation. So the existence of relationship between them could be criteria for investors to anticipate interim and annual abnormal return and facilitate investing decisions. Overall, the findings show that for explaining stock return interim financial statements are more informative than annual financial statements. Manuscript profile

Open Access Article

40 - بررسی رابطه کیفیت سود و ساختار سرمایه (مطالعه موردی: شرکت‌های غیرمالی پذیرش شده در بورس اوراق بهادار تهران)
سید سجاد علم الهدی عبداله دریابر سمانه طریقی

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41 - Predicting Emotional Tendency of Investors Using financial ratios based on principal component analysis method
Reza Taghavi iman dadashi Mohammad Javad Zare Bahnamiri Hamid Reza Gholamnia Roshan

10.30495/fed.2023.698847

AbstractOne of the proven topics in psychology is the influence of people's emotion's on the decision-making process and their judgment about future events. In such a way that when people have positive emotions, they make optimistic choices and when they have negative e More

AbstractOne of the proven topics in psychology is the influence of people's emotion's on the decision-making process and their judgment about future events. In such a way that when people have positive emotions, they make optimistic choices and when they have negative emotions, they make pessimistic choices. Therefore, the emotional tendencies of investors indicate the margin of optimism and pessimism of shareholders towards a share. The purpose of this study is to use financial ratios to predict the emotional tendencies of investor's. To answer the research questions, data related to 97 financial ratios belonging to companies listed on the Tehran Stock Exchange during the period 2006 and 2018 have been used. In order to derive effective financial ratios, the neighborhood component analysis algorithm method was used, which ultimately led to the selection of 7 ratios. To measure the emotional tendencies of investor's, four indicators of relative strength, psychological line, trading volume and stock turnover adjustment rate have been applied. Finally, we have combined these indicators with the help of PCA method. The results showed that the ratios of percentage changes in sales changes, net profit to assets and the ratio of inventory changes to sales changes have a positive and significant effect on investor's feelings.                                                                                               Manuscript profile

Open Access Article

42 - Company value prediction based on deep learning methods
Seyedeh Maryam Babanezhad Bagheri Abbasali PourAghajan M. Mehdi Abbasian Feridoni

10.30495/fed.2023.705603

Abstract Prediction and clear understanding of the behavior of a phenomenon plays a major role in adopting strategies and decisions. All-round development and deepening of the capital market as the driving engine of economic development requires the public trust of par More

Abstract Prediction and clear understanding of the behavior of a phenomenon plays a major role in adopting strategies and decisions. All-round development and deepening of the capital market as the driving engine of economic development requires the public trust of participants in its efficiency and correctness in determining the fair price of securities. On the other hand, predicting company value, price fluctuations, or stock returns is very important in portfolio selection, asset management, and even stock pricing of newly listed companies.In this research, using the data of 159 companies during a 10-year period including 2011-2020 and the factors affecting the company's value, including financial ratios, corporate governance mechanisms, macroeconomic factors, and the stock market, the company's value has been predicted. In this research, two structures of deep learning methods including GRU and BLSTM are used for better evaluation. The results of examining the data collected using deep learning techniques indicated that the combined model with a lower RMSE error than the GRU model predicted the value of the company. Manuscript profile

Open Access Article

43 - Designing Credit Risk Early-warning System for Individual and Corporate Customers of the Banks using Neural Network Models, Survival Probability Function and Support Vector Machine
Roya Derakhshani Mirfeiz Fallah hosein jahangirnia Reza Gholami jamkarani Hamidreza kordlouie

Credit risk is the probability of default of the borrower or the counterparty of the bank in fulfilling its obligations, according to the agreed terms. In other words, uncertainty about receiving future investment income is called risk, which is of great importance in b More

Credit risk is the probability of default of the borrower or the counterparty of the bank in fulfilling its obligations, according to the agreed terms. In other words, uncertainty about receiving future investment income is called risk, which is of great importance in banks. The purpose of this article is to estimate the credit risk of individual and corporate customers. In this study, the statistical information of 400 individual customers and7500 corporate customers was used. In this regard, the results of neural network model and support vector machine model have been compared. The obtained results have shown that the components considered in this study based on their personal, financial and economic characteristics had significant effects on the probability of customer default and credit risk calculation. Also, the results of this study showed that the application of control policies at the beginning of the repayment period suggests facilities that have the highest probability of default with long life and high repayment. The comparison of the results of the prediction accuracy shows the higher explanatory power of the support vector machine model and the use of the survival probability function than the simple neural network model for both groups of customers. Manuscript profile

Open Access Article

44 - Evaluating the Effect of Content of Inflation Accounting Information in Comparison with Historical Information in Designing Bankruptcy Prediction Models Based on Traditional and Meta-Innovative Approaches
Naeemeh Jebelli Iman dadashi

10.30495/faar.2023.705557

AbstractBankruptcy Prediction is one of the branches of finance that has received more attention in in recent research as bankruptcy patterns have been developed. In most of the researches in the field of Prediction the financial performance of companies and in particul More

AbstractBankruptcy Prediction is one of the branches of finance that has received more attention in in recent research as bankruptcy patterns have been developed. In most of the researches in the field of Prediction the financial performance of companies and in particular, bankruptcy, only Predicting or comparing the predictive power of models using historical information of financial statements has been done. Since historical accounting information has been used more in Iran, the main purpose of this study is to consider the effects of inflation on input variables in designing a bankruptcy prediction model. Therefore, the variables in design of two different models were classified into two groups of financial ratios, adjusted and historical. Then, the ratios were identified using the LARS algorithm that had the highest ability to differentiate between bankrupt and non-bankrupt companies. Finally, the final bankruptcy prediction model was designed using the logit regression test and SVM and Naive Bayesian algorithms. For this purpose, the data of 50 companies listed on the Tehran Stock Exchange were used, which had experienced bankruptcy according to Article 141 of the Commercial Code. The results of this study indicate that the financial ratios adjusted based on the price index are more suitable predictor for corporate bankruptcy. Also, the bankruptcy prediction model designed by SVM algorithm can be a very good predictor for corporate bankruptcy with 99.4% accuracy. Manuscript profile

Open Access Article

45 - Predicting Emotional Tendency of Investors Using Support Vector Machine (SVM) and Decision Tree (DT) Techniques
reza taghavi iman dadashi mohammad javad zare bahnamiri hasmidreza gholamnia roshan

Investor's emotional tendencies indicate the margin of shareholder's optimism and pessimism towards a stock. Investors' emotions, under the influence of psychological phenomena, direct people's behavior and, in many cases, make people to deviate from the rational behavi More

Investor's emotional tendencies indicate the margin of shareholder's optimism and pessimism towards a stock. Investors' emotions, under the influence of psychological phenomena, direct people's behavior and, in many cases, make people to deviate from the rational behavior. The purpose of this study is to use meta-innovative methods to predict the emotional tendencies of investors. In this study, using 97 financial ratios related to 176 companies listed on the Tehran Stock Exchange during the period between 2006 and 2018, investors' emotional tendencies have been predicted with the help of support vector machine (SVM) and decision tree (DT) techniques.To measure the emotional tendencies of investors, four indicators of relative strength, psychological line, trading volume and stock turnover adjustment rate have been applied. Finally, we have combined these indicators with the help of PCA method. Mean absolute error (MAE) and root mean square error (RMSE) values were used to compare predicting methods. The results of data analysis indicate that the prediction error of the support vector machine method is less than the decision tree. Manuscript profile

Open Access Article

46 - Presenting a Model Based on Evaluation of Performance Banks Listed in Tehran Stock Exchange Using Data Mining Approach
elham adakh arefeh fadaviasghari Mohammad Ebrahim Mohamad Pourzarandi

With the growth of private banks , financial and credit institutions, competition for better services has increased. Given the importance of the issue, it is necessary to develop a comprehensive model for evaluating banks. Every organization needs to evaluate its perfor More

With the growth of private banks , financial and credit institutions, competition for better services has increased. Given the importance of the issue, it is necessary to develop a comprehensive model for evaluating banks. Every organization needs to evaluate its performance to understand its strengths and weaknesses, especially in dynamic environments. The issue of performance appraisal is so widespread that even management experts say: "What cannot be evaluated cannot be managed".Banks, like other organizations in Iran, need performance evaluation to provide more diverse and faster services as well as their development. [6]This study aimed to present a model to evaluate the performance of banks listed in Tehran Stock Exchange using data mining approach. In this research, four data mining models of decision tree C5.0, decision tree C4.5, Naive Bayes classifier, and random forest were implemented and compared to evaluat the performance of banks. To this end, 28 financial ratios (e.g., profitability ratios, liquidity, quality management, asset quality, and capital adequacy) in 18 banks of Tehran Stock Exchange during 2014-2017 were selected as independent variables. In addition, the performance of banks in three categories of acceptable, unacceptable, and moderate was selected as the dependent variable of the study. According to the results, the decision tree C5.0 with the accuracy of 94.4% was the most efficient model proposed in this research. Manuscript profile

Open Access Article

47 - Imaged ﬁnancial Ratios and Bankruptcy Prediction using Convolutional Neural Networks
abbasali haghparast alireza momeni Aziz Gord fardin mansoori

Convolutional neural networks are being applied to identiﬁcation problems in a variety of ﬁelds, and in some areas are showing higher discrimination accuracies than conventional methods. Hence, in this research, an attempt is made to apply a convolutional neural network More

Convolutional neural networks are being applied to identiﬁcation problems in a variety of ﬁelds, and in some areas are showing higher discrimination accuracies than conventional methods. Hence, in this research, an attempt is made to apply a convolutional neural network to the prediction of corporate bankruptcy. The ﬁnancial statements ratios has been choice 66 companies that have been delisted from the Iran Stock Market due to de facto bankruptcy as well as the ﬁnancial statements of 66 listed companies over 2000 to 2019 ﬁnancial periods. In this method, a set of ﬁnancial ratios are derived from the ﬁnancial statements and represented as a grayscale image. The image generated by this process is utilized for training and testing a convolutional neural network. The images for the bankrupt and continuing enterprises classes are used for training the convolutional neural network based on GoogLeNet. The findings shows, in prediction of going concern of firms, Convolutional neural network has predicted with 50 percent of precision. This means that 50 percent of continues firms and 50 percent of bankrupt firms has been predicted precisely. Manuscript profile

Open Access Article

48 - Solving Imbalanced Data Distribution Problem in Bankruptcy Prediction by Cost-Sensitive Learning Method
seyed behrooz razavi ebrahim abbasi

This study aimed to add cost-sensitive learning technique to imbalanced data-based bankruptcy prediction models in order to reduce type I error and increase the geometric mean criterion of overall accuracy to reduce the misclassification costs of bankrupt companies for More

This study aimed to add cost-sensitive learning technique to imbalanced data-based bankruptcy prediction models in order to reduce type I error and increase the geometric mean criterion of overall accuracy to reduce the misclassification costs of bankrupt companies for stakeholders. For this purpose, type I error, type II error, and the geometric mean of overall accuracy of bankruptcy models based on cost-sensitive learning were compared with bankruptcy prediction models with highly imbalanced datasets. The statistical sample included 1200 year-companies since 2001- 2020, consisting of 90% healthy companies and 10% bankrupt companies. Hypotheses test results showed that adding a cost-sensitive learning technique to the bankruptcy prediction models led to a significant decrease in the type I error, a significant increase in the type II error, and a significant increase in geometric mean of accuracy of imbalanced data-based models at 95% confidence level. Also, with the increase in the misclassification cost of bankrupt companies, type I error had a downward trend and the II type error had an upward trend, and the geometric mean of accuracy had an upward trend. Manuscript profile

Open Access Article

49 - Hybrid PCA-ANFIS approach and Dove Swarm Optimization for predicting Financial Distress
sina Kheradyar Mohammad Hasan Gholizadeh Forough Lotfi

In this study, an Adaptive Neuro Fuzzy Inference System (ANFIS) based on Principal Component Analysis (PCA) is proposed for predicting the financial distress of companies. This system not only has the ability to adapt and learn, but also reduces the error, because it av More

In this study, an Adaptive Neuro Fuzzy Inference System (ANFIS) based on Principal Component Analysis (PCA) is proposed for predicting the financial distress of companies. This system not only has the ability to adapt and learn, but also reduces the error, because it avoids additional parameters when input variables are too high. In order to confirm the effectiveness of this model, 181 listed companies in the Tehran Stock Exchange (905 companies-years) were selected by using systematic samples from 2011 to 2015, which 58 of those were distressed and 847 companies-years were healthy. These companies were randomly divided into two sets: a training set for designing model and a check set for validating the model. The results of the research show that the Adaptive Neuro Fuzzy Inference System based on Principal Component Analysis is capable for predicting the financial distress of companies accepted in Tehran Stock Exchange and when the proposed model is combined with Dove Swarm Optimization metaheuristic algorithm, Reducing the error value increases the accuracy of the model. Therefore, it can be seen that the use of a complementary algorithm can increase the predictability of the PCA-ANFIS model. Manuscript profile

Open Access Article

50 - The Bankruptcy prediction of Tehran Stock Exchange Using Firefly Algorithm (FA)
ali bayat Seyyed Ali Reza Ahmadi majid mohamadi

Investor, stockholders, managers, beneficiaries, with broke of company, would lost their assets. Thus, existence of mechanism which could be evaluating and expecting of financial crisis of companies, is essential. A lot of research, implemented about expecting of bankru More

Investor, stockholders, managers, beneficiaries, with broke of company, would lost their assets. Thus, existence of mechanism which could be evaluating and expecting of financial crisis of companies, is essential. A lot of research, implemented about expecting of bankrupt, which using of smart intelligence algorithms and ultra-discovery, were of the models of recent decay. In this study, with using of information of stock exchange center of TEHRAN (1390-1395), 45 successful firms and 25 bankrupt firms, have been researched. Financial ratios were of the variables of this study, which these variables with using of ultra-discovery algorithm of glowworm, identified as one of the models of smart intelligence and effective ratios in bankrupting. It includes of 9 financial ratios and in long with this process, valid and broke firms have been ranked. Two hypothesis have been codified for this study, which the result of them, in order to justified of these hypothesis, indicating of 95/12 correct expecting of first year, 5/36 for second year, and 80/48 for third year. Manuscript profile

Open Access Article

51 - The Effect of Managers' Ability on The Relationship Between the Quality of Accounting Information and Investor Behavior and Trading Performance
kevan azizi farzad eivani hadis abdi Seyed Javad Dellavari

10.30495/jdaa.2024.709473

AbstractIn the behavioral financial paradigm, the human hypothesis as a rational being that always succeeds in optimizing its interests is questioned. Proponents of behavioral finance know that the knowledge of "psychological inclinations" in the field of investment is More

AbstractIn the behavioral financial paradigm, the human hypothesis as a rational being that always succeeds in optimizing its interests is questioned. Proponents of behavioral finance know that the knowledge of "psychological inclinations" in the field of investment is absolutely necessary and requires serious development of the field of study. Accordingly, the purpose of this study was to investigate the relationship between financial ratios as a measure of accounting information on the pattern of behavior and trading performance of investors and also to investigate the effect of managers' ability on this relationship. In order to achieve the research goal, 105 companies were selected from the companies listed on the Tehran Stock Exchange, by systematic elimination method and tested using EViews and Stata software. The results of testing the hypotheses have shown that among the components of financial ratios; There was a significant relationship between current ratio, current ratio, gross profit ratio, total debt to equity ratio, total debt to total assets ratio, return on assets ratio and earnings per share ratio with investors' trading behavior and performance. The present results showed that in the content of accounting information, especially using some financial ratios, investors' trading behavior and performance can be predicted. On the other hand, the findings indicate a significant effect of managers' ability on the relationship between financial ratios (current ratio, instantaneous ratio, gross profit ratio and earnings per share ratio) and the trading behavior and performance of investors. Manuscript profile

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