Research Article: 2024 Vol: 30 Issue: 5
Sayadporvali alyar, Islamic Azad University, Iran
Saeed Jabarzadeh Kankarloi, Islamic Azad University, Iran
Jamal Bahri sales, Islamic Azad University, Iran
Ahmed Jafarian, Islamic Azad University, Iran
Citation Information: Alyar. S., Kankarloi, S, J., sales J, B., Jafarian A (2024). Investigating the classification of indicators that determine the credit category of companies. Academy of Entrepreneurship Journal, 30(5), 1-11.
Financing decisions play an important role in determining growth, investment and production strategies. Access to low financing costs is one of the economic feasibility obligations in the field of development, and credit plays an important role in obtaining financing. The purpose of this research is to examine the classification of indicators that determine the credit rating of companies in Iran. Rating agencies must pay attention to quantitative and qualitative factors to determine the credit rating. For this purpose, in this research, first, the credit rating literature was examined and the indicators defining the credit rating were extracted in two parts, qualitative and quantitative indicators. Then the opinion of the experts was collected using questionnaires and interviews. Binomial test was used to test the research hypotheses, which takes into account the importance of each of the indicators in determining the credit category, and the Friedman test was used for the superiority of the indicators. The result of the research shows that10indicators are the most important indicators that determine the credit rating of companies
credit category; Debt solvency; Binomial test; qualitative indicator; Quantitative indicator Background of the study
In determining strategies for growth, investment and production, financing decisions play an important role. Access to low financing costs, one of the obligations of economic feasibility in the context of development, credit plays an important role in obtaining financing (Amiri, M., & Biglari Kami, M. 2013). Credit rating is an expression of the issuer's ability and willingness to fulfill financial obligations in a complete and timely manner (Standard & Poor's, 2011) and includes two types of credit rating bonds, debt rating and issuer credit bonds (issuer). In the classification of debt securities, the probability of default or delay in payment of principal and debt securities is considered, and in the classification of credit issuers (issuers), the evaluation of the overall credit participation is considered (Wang and Vidigaran, 2010, 130). This research seeks to investigate the classification markers that characterize the negative participation. Investors, lenders and analysts of financial stocks use credit ratings as an indicator of the quality of the participation and the risk of the stock (Ahmadi, Moussa 2016). Although credit ratings are not considered recommendations for investors, they act as one of the indicators of stock evaluation (Abad, P., Alsakka, R., & ap Gwilym, O. 2018). Credit ratings as a solution to information asymmetry and increasing the efficiency of the capital market can be explained and interpreted because of the different motivations of market operators for requesting credit rating, their common statement is to eliminate the information asymmetry in relation to the credit status of an issuer or Debt sheet and increase efficiency of the capital market are also present Aysun, A. (2016). Reliability classification can be interpreted as a screening technique that is used to reduce the problems of asymmetric information (Bello, Qasim, Ahmed Vand, Maitham 2019).
Banks use internal ratings to assess creditworthiness, but investors in the capital market rely on ratings provided by rating agencies. Classification Institutions Classification is usually done in two ways give The first condition is when the participation is significant There is a request for classification and the second condition is that the institutions of classification without participation take special steps for classification do This division into classifications is usually discounted between senior and junior classifications. Senior credit rating agencies are active in both cases, but junior credit rating agencies are more active in the first case (intellectual). (Bone, R. B. 2010). Modi's is one of the world's three most trusted institutions , Standard & Poor's Wages exist. Each method is standard These are functionally self-contained. Nihad Modi's indicator for determining credit participation High deficiency and sufficiency are subject to evaluation. Nihad Standard & Poor's also examines the business risks and financial risks of creditworthy companies.give Finally, Nihad Fitch, in order to determine the quality of participation, deals with the analysis of indicators of lack of financial and quality of non-financial (Daneshvar, Shahram, 2012). We will soon witness the existence of such institutions through the management of Islamic research and development. Because the Tehran Stock Exchange Organization has realized the existence of the necessary institutions (Dayanti Dilami, Zahra. 2014). This is the real need There are criteria that can be used to determine reliable participation. These indicators are used in every environment and every class Yes, they will be different. Therefore, this research is for the first time in the form of a scientific work-Interest extraction is one of the most important indicators determining the level of credibility in Iran.
Investors, lenders, and financial analysts use credit ratings as an indicator of company quality and risk. do Credit ratings were used as one of the evaluation indicators do Credibility criteria can be explained and interpreted as a solution for asymmetry of information and the efficiency of the capital market (Dorfleitner, G., Grebler, J., & Utz, S. 2019). Timely cancellation In early or modern security, the problem is that it becomes more prominent Representation. This is indicative of the fact that before investors invest, the information is less than the quality of a publisher and market. They have, while the publisher itself has more complete information. Therefore, it is possible to choose a safe investment option spent (Ebrahimi, Marzieh and Daryaber, Abdullah 2011). Do it efficiently Ash is better than one sheet of paper. Agreed for a while Unless there is information about the quality of an instrument that is considered to be a good deal, there is no secret information. Later", after a tool or a publisher has discovered itself first However, the problems became apparent However, sometimes a publisher can take covert actions E performance that has a negative effect on the return on the final investment (Gray, S., Mirkovic, A., & Ragunathan, V. 2006). Frictions created by hedges in the marketplace provide value-added opportunities for bearers of quality risk. do These valuable opportunities can reduce the information asymmetry between the issuer and the investor by providing credit ratings. hi commercial Residents who provide loans to borrowers and supervise them do (same source).
Rejection Bandi Credibility, a statement of the issuer's ability and willingness to meet financial obligations in a timely and complete manner (Grunert, J., Norden, L., & Weber, M. 2005). Credibility levels play a role in the dependence of information on the dominance of information asymmetry in the process of information exchange. This position is rejected Bandits are called «information asymmetry». One of the most important problems in the rights of investors is that they are informed about the events that take place in their participation, that is, there is information asymmetry between the external investors and the internal control of the participation. Therefore, this space is the space in which the institutions have performed the credit rating and economic evaluation Afrainanda. The target institutions are rejected The clause is that it will be returned Yes, make up for the lack of information for investors with proven returns (Hájek, P. 2012).
Other statements are pending Bandi Musisaat Rada Decentralized appropriation of resources contribute to the economy (Hwang, R. C., Chung, H., & Chu, C. K. 2010).
Users
From a participation perspective, credit rating is of great practical importance because it affects the participation's cost of debt, financing structure, and the ability to continue operating the participation (Jiang, X., & Packer, F. 2017). For firms with high creditworthiness, it facilitates market entry with ease and lower financing rates (Jollineau, S. J., Tanlu, L. J., & Winn, A. 2014).
The credit rating literature states that ratings serve two purposes from a capital perspective. Confirms the financial terms of the current participation for the investors (initial cancellation) and announces changes in the previous financial terms of the participation (revocation of changes) (Keller, T. 2006). Credit ratings are valuable to investors as long as they do not need to spend additional costs for research or monitoring publishers (Khazaei, A. H., & Farahanifard, S. 2021).
Risk assessment is reliable
The word risk, especially in financial markets, is often associated with the potential loss of an investor. Credit risk is the possibility of issuer default, which is related to non-payment of interest or principal obligation. In financial markets, investors are often interested in measuring risk participation before deciding on the level of investment. by decadeIn the 1980s, the demand for information related to risk analysis has increased greatly and many methodologies have been developed based on this demand (Kohi Hassan and Rooh Elah Gholami. 2012).
Credit ratings are used by investors to assess the risk of creditworthy borrowers (Kumar, K., & Haynes, J. D. 2003). Risk credibility is an important issue for any participation at any time period. Financial institutions including banks participated in credit rating to reduce credit risk (ASDI). (Langohr, H., & Langohr, P. 2010).
The role of credit ratings in financial markets
Naqsh is another classification of reliability in the performance market. This map focuses on the topic of how credit ratings contribute to market operations and how they have a particular impact on market participants. Basically, rating reduces an investor's ability to make better judgments than others. In this scenario, the classification as an equalizer Acts in the capital markets and helps the investors to be in the same conditions (Mahmoud, A. H., & Ghayouri, M. A. 2011). The main task of proper credit rating from the financial perspective is to help strengthen the efficiency and transparency of capital markets by reducing the information asymmetry between borrowers and lenders. (Marcin, T. 2009), (MurciaI, F. C. D. S., Dal-Ri Murcia, F., Rover, S., & Borba, J. A. 2014).
There are reliable classification institutions in the world, and as a result of the investigation, classification is done based on real data. Most of the research conducted on classification reliability has focused less on factors that change the facility of data submission do However, all credit rating agencies acknowledge that credit rating is derived from a number of factors. Table 1 Further, the investigation is presented in two parts, internal and external. After studying the research literature (including previous research and reliability classification), this research has focused on quantitative variables and qualitative variables (Poon, W. P., & Chan, K. C. 2008).
| Table 1 Background of Internal and External Research Respectively | ||||
| Row | Author(s) (year of research) | Research title | Research methodology | The most important findings and results related to the research |
| 1 | Ahmadi, Musa (1396) | Institutional Financial Rating Credit; Accusations and demands. Participation Classification Credential Evidence | Traffic | The role played by credit rating institutions requires serious attention to wealth discounting accounting practices, standards, and standards used by them. |
| 2 | Rezai and Wadigaran (1398) | Classification of Challenges of Implementation of Credit Model Expected in Iran Banks in Cross-Sectional Form | Analysis Hierarchical Fuzzy Techniques | They designed the expected reliability loss model by using the analysis hierarchy technique and with the help of the innovative approach.WASPAS) proposed better strategies to remove the obstacles in the implementation model of credit risk in Iran's banks. |
| 3 | Amiri and Biglari Comi (2013) | Classification of reproduction companies in Tehran Stock Exchange | The Tapsis Valgorithm Neural Network | Results marked95% of the classifications are done correctly |
| 4 | Ebrahimi and Daryabar (1391) | Risk management, fiduciary analysis in banking systems, regression analysis, logistic regression, and neural networks | Analysis of fuzzy data regression logistic and neural network | Eight indicators affecting credit risk are short-term loans to total assets, short-term loans to net sales, ratio of total debt to total assets, proposed business, past repayment, equity to total assets, current assets to fixed assets and rate of return on selected assets. Shad |
| 5 | well and slavery (1391) | Classification of trusted customers in the legal sector industry using cloud data analysis | Dissolve cover data | They examined three financial indicators and concluded that all indicators are significant at the satisfaction level of 95%. |
| 6 | Safari et al.1390) | Designing Model Classification Credit Clients Legal Commercial Banks | Dissolve cover data | Financial and non-financial variables included in 27 explanatory variables were investigated using two models of data analysis using a synthetic approach (financial and non-financial). Finally, according to the results obtained from the factor analysis and the judgment of the experts, eight indicators were selected as the final indicators covering the financial and non-financial dimensions. |
| 7 | Puroli Aliyar et al.1401) | Rating of credit companies accepted in Tehran Stock Exchange | Dissolving cover data | By using10 Indicators of Deficiency and Deficiency are used to classify credit participation |
| 8 | Balu and Ahmad Vand (1399) | Model for Peshbani Nicole participates in Bourse Oraq Bahadar Tehran | Delphi Fuzzy Methodology | It was observed that only accounting ratios were introduced under the title of Nikol Sharmati. |
| 9 | Ra'i and Roosh (1391) | Validation of legal clients of small and medium-sized banks using the validity and reliability model | Modeling and modeling | For evaluation, five financial ratios, current ratio, debt ratio, ratio before interest before deduction of interest, finance to cost, net interest to total assets, net interest to sales were used. |
| 10 | This is (2016) | Structural Changes in Credit Rating Standards from 1985 to 2007 for US Companies | Multivariate Regression and Correlation | And it came to the conclusion that there was no pattern of variation in the balance of capitalTrust companyYes, summerAbsent from 1985 to 2002. After 2002, it is conservative. |
| 11 | Chiang Vipakra (2017) | Classification of domestic and international credit agencies | Statistical regression logistic regression | The capital market has given importance to Chinese companies and the influence of the stock price is considered to be negative. |
| 12 | Forever and ever (2018) | Impact of Level Ratings and Convergence Ratings on the Impact of Overarching Actions | Multivariate regression | Downgrading of countries with high ranking will spread to high and low-ranking teenagers, while low-ranking teenagers will have less influence on high-ranking teenagers. |
| 13 | Magnificent (2019) | The role of credit rating agencies in fixing the gaps And financial participation is small |
Descriptive | Credit rating is a cost-effective way to finance participation, and high credit rating reduces information asymmetry. |
| 14 | Durflitzo Degran (2020) | The effectiveness of collective participation and environmental performance in predicting credit ratings | Multivariate regression | Marked thatCSP indicator correlation is used to predict rank reliability. Participation with high CSP has low risk and consequently high reliability. |
| 15 | Hajk (2012) | Reliability analysis using fuzzy adaptive rule-based systemsOh | Setham Hi Rules Fuzzy Algorithm Genetics | The results and indicators are classified according to the reliability criteria assigned to each participant using high-accuracy high-accuracy features and if-know rules. |
| 16 | Wang et al (2010) | Predictive ranking of credit issuers using a semi-parametric approach | Semiparametric Probability | A proposed model for validation using29 Market, Accounting, and Industry Performance Indicators The modern demand model has a higher probability than the marginal model. |
| 17 | Abrahand and Chandani (2021) | Elements of classification: A systematic review and further investigation | Dissolving content | Check mark48% of the studies have focused on the developmental constructs of the modern classification system without assessing the underlying constructs. |
| 18 | Marcin (2013) | Application of latent data analysis in discriminant validity | Regression logistic regression | Profitability has a positive relationship with reliability and pyramid has a negative relationship. Capital intensity is significant. Lack of participation and opportunities has a positive relationship with reliability. |
| 19 | Kamastra et al (2001) | Predictive Rating Papers Borrowing using Lajit | Test effect indicators are highly reliable | The relative debt relationship is negative. |
| 20 | Amiri and Biglari Comi (2013) | Abandoned credible reproductive participation using high quality standards | Tapasis and the nervous system | They concluded that neural network provides better classification of participants than other methods. |
The present research in terms of the approach, the naturalistic research, the purpose of the research, practical research, the nature of the research, the lack of data, the identification method, the descriptive method, and the post-event research (ali-comparative). This investigation is conducted to obtain information about the existence of relationship between variables (Rai Reza and Bouzarsaroosh. 2013).
For this approved literature classification was included The credit rating is superior and the studies conducted in this field are considered and the most important indicators affecting the credit rating are included.23 markers were extracted. Markers That's enoughThey were classified into 6 classes and 7 classes according to table 2 (Safari Saeed, Ebrahimi Shaghaghi, Marzieh and Tahiri Fard, Morteza. 2013)
| Table 2 Markers are Highly Effective And Reliable | ||
| The most effective indicators determining reliability | ||
| Qualitative indicators | Factors Industry | Risk market industry |
| Operational environment | Diversified geographic industry | |
| Capacity surplus industry | ||
| Competitive situation | Stock market | |
| Quality management | Financing policies | |
| Board size | ||
| Separation of Managing Director from Board of Directors | ||
| Managing Director | ||
| Leadership participation | Relative to non-executive members of the Board of Directors | |
| Rotational Institutional Auditing | ||
| Original or subsidiary | ||
| Annual adjustments | ||
| Environmental accounting | Rosh Kurdish present black | |
| Investment accounting method | ||
| Markers are lacking | Relative profitability | Returning assets |
| Relative liquidity | Current liabilities and assets | |
| Covering Relatives | Operating cash flow would be due tomorrow | |
| Cash flow would be operationally independent | ||
| Relative performance | Fixed assets with ownership rights | |
| Structural relations | Office pyramid | |
| Capitalism | High debts and accumulated assets | |
| Relative to the owner | ||
| Accounting figures | Percentage change in fixed assets | |
Due to the fact that he was born in Iran There is no formal classification of reliability and most of the indicators that have been determined from the literature review are based on the environment outside of Iran. E was prepared and specially submitted for the expert's attention (Ratings, S. P. G. 2019). These experts include risk managers and some credit managers of banks and credit rating consulting companies, consultants of the Tehran Stock Exchange and some people outside the banks or the capital market in this field (Salimpour, Maryam. 2015). The questionnaire is designed in such a way that experts should answer three areas. First, the researcher should measure the importance of the indicators that determine the reliability of the spectrum5. Specify the letter, then in the case of qualitative indicators, confirm the proposed reduction of indicators or suggest indicators, and finally, in each group of indicators, if they think that another indicator should be added, it will be mentioned.
Finally27. Questionnaire submission and examination. Cronbach's alpha coefficient was used to check the reliability of the questionnaire. Likert scale test is ordinal because values are calculated from 1 to 5 and therefore two-item test is used to test hypotheses. For each of the indicators that characterize the research, the following hypotheses exist.
The amount of research found in the table 3 Has come
| Table 3 Cronbach's Alpha Coefficient of the Questionnaire | ||
| Quantitative Questionnaire | Number of experts | Cronbach's alpha coefficient |
| 23 | 27 | 989/0 |
A two-sentence test compares two groups. If the significance level is less than5% means that the ratio of two groups is not equal and it is obligatory. The Likert scale of the questionnaire is marked as 1 to 5. 1 is an indicator of unimportance in determining reliability, and 2 is low importance, 3 is not significant, 4 is important, and 5 is essential in determining reliability (Shankar, S. 2019). Therefore, the indicators are in the determining level of reliability that are important or important from the point of view of experts. That is, three options (equal 6/0=5/3) are in the factor rejection hypothesis. The results are divided into two groups according to each of the indicators. The first group includes distinctions 1, 2, and 3, and the second group includes distinctions 4 and 5, that is, important and important. If the probability of the first group is more than 6/0, the hypothesis is confirmed and the indicator is not considered as a reliable factor in the opinion of experts Table 4.
| Table 4 The Results of the Two-Sentence Test in the Table4 is Marked | ||||
| The number | Potentially observed | Level of significance | ||
| Risk market industry | Group I | 2 | 1/0 | 000/0 |
| Group II | 23 | 9/0 | ||
| Diversified geographic industry | Group I | 13 | 5/0 | 145/0 |
| Group II | 14 | 5/0 | ||
| Capacity surplus industry | Group I | 14 | 5/0 | 250/0 |
| Group II | 13 | 5/0 | ||
| Stock market | Group I | 2 | 1/0 | 000/0 |
| Group II | 25 | 9/0 | ||
| Financing policies | Group I | 1 | 0 | 000/0 |
| Group II | 25 | 1 | ||
| Board size | Group I | 20 | 7/0 | 095/0 |
| Group II | 7 | 3/0 | ||
| Separation of Managing Director from Board of Directors | Group I | 14 | 5/0 | 250/0 |
| Group II | 13 | 5/0 | ||
| Managing Director | Group I | 14 | 5/0 | 250/0 |
| Group II | 13 | 5/0 | ||
| Relative to non-executive members of the Board of Directors | Group I | 18 | 7/0 | 309/0 |
| Group II | 9 | 3/0 | ||
| Rotational Institutional Auditing | Group I | 16 | 6/0 | 542/0 |
| Group II | 11 | 4/0 | ||
| Original or subsidiary | Group I | 15 | 6/0 | 387/0 |
| Group II | 12 | 4/0 | ||
| Annual adjustments | Group I | 13 | 5/0 | 145/0 |
| Group II | 14 | 5/0 | ||
| Rosh Kurdish present black | Group I | 18 | 7/0 | 309/0 |
| Group II | 9 | 3/0 | ||
| Investment accounting method | Group I | 21 | 8/0 | 309/0 |
| Group II | 6 | 2/0 | ||
| Returning assets | Group I | 2 | 1/0 | 000/0 |
| Group II | 25 | 9/0 | ||
| Current liabilities and assets | Group I | 8 | 3/0 | 000/0 |
| Group II | 19 | 7/0 | ||
| Operating cash flow would be due tomorrow | Group I | 1 | 0 | 000/0 |
| Group II | 26 | 1 | ||
| Cash flow would be operationally independent | Group I | 2 | 1/0 | 000/0 |
| Group II | 25 | 9/0 | ||
| Fixed assets with ownership rights | Group I | 16 | 6/0 | 542/0 |
| Group II | 11 | 4/0 | ||
| Office pyramid | Group I | 0 | 0 | 000/0 |
| Group II | 27 | 1 | ||
| High debts and accumulated assets | Group I | 4 | 1/0 | 000/0 |
| Group II | 23 | 9/0 | ||
| Relative to the owner | Group I | 6 | 2/0 | 000/0 |
| Group II | 21 | 8/0 | ||
| Percentage change in fixed assets | Group I | 14 | 5/0 | 250/0 |
| Fall II | 13 | 5/0 | ||
The results of the two-jumla test are marked23, 10 indicators play a role in determining the reliability of participation. Indicators of geographical diversity of the industry, excess capacity of the industry, separation of the managing director from the board of directors, stability of the managing director, annual adjustments, proportion of non-executive members of the board of directors, rotation of the audit firm, original or subsidiary, method of rotation of assets, fixed assets and ownership rights and percentage. The change in assets is not significant and the indicators of the size of the management team and the accounting methods of the investments, although they are meaningful, are not considered to be reliable because of the confirmation assumption.
Then, the indicators that determine the reliability are evaluated by the experts with the Farid test. This test deals with the classification of their views on these indicators Table 5.
| Table 5 Comparative Level of Significance Indicators Using Azmoun Farid Min |
| The number27 |
| Give the quantity statistics034/744 |
| Degree of freedom 9 |
| level of significance000/0 |
Considering that the level of significance is lower than5%, so the indicators do not have the same priority in determining the reliability level and the higher the average rating of each indicator, the more important it is in determining the reliability level. further results of friedman are given in table 6.
| Table 6 Classification Indicators Determining Reliability | ||
| marker | Average grade | Interference between markers |
| Risk market industry | 41/48 | 7 |
| Stock market | 19/57 | 2 |
| Financing policies | Jul-52 | 3 |
| Returning Assets | Nov-51 | 4 |
| Current liabilities to assets ratio | Aug-37 | 10 |
| The flow of the final operation will be given tomorrow | 76/50 | 5 |
| Cash Flow Operating Independent Debt | Sep-47 | 9 |
| Long-term debt compared to long-term deposits | May-48 | 6 |
| The financial pyramid | Mar-58 | 1 |
| Relative to the owner | 35/47 | 8 |
The results indicate; the top indicators determining creditworthiness are financial pyramid, stock market, financing policies, return on assets, operating cash flow to total debt, long term debt to total assets ratio, industry risk market, ownership ratio, and debt to asset ratio. Dwell
Ranking companies by introducing the top companies in the industry, determine their position in the competitive environment based on indicators. This causes, on the one hand, the weaker participations to assess their distance with the superior participations and to modify appropriate strategies to reach them. On the other hand, superior participation with defined programs and appropriate strategies is self-sustaining wash up in addition to these cases; the provision of information also provides a suitable opportunity for investors to make appropriate investments. The collection of these cases has led to increased competition in the market and increased competition in the market also has benefits that can generally be said to lead to the development of society.1383).
Despite the existence of three international credit rating institutions, some countries have permanently established institutions for rating credit companies in order to be able to classify companies according to local conditions.
Unfortunately, there is no formal external credit rating system in iran, but the need for it is foreseen in the laws of stock exchange and securities. However, the determination of the credit rating of the company requires the completion of studies and the creation of a coherent database, which is a prerequisite for the real rating in iran.
This research has initially extracted the reliability indicators in the form of a library. Institutions are ranked among the best in the world and studies conducted have been considered as indicators high deficiency should also be considered qualitatively. Then, through exploratory interviews with experts and through questionnaires, they have determined the indicators that determine the reliability in the environment of iran. Research results indicative 23 indicators are specified that their priority in determining the rank should not be the same. This research is not similar in iran and the world. There are credit rating institutions in the world, and as a result, researchers do not need to determine the rating, but consider the effective indicators of the credit rating. Including by integrating performance measures of collective participation (csp) into a risk-reliability model for the years 2003 to 2017, the rate of improvement of reliability predictors through multivariate regression analysis and their analysis showed that csp indicator integration is reliable for negative, participation in unpleasant phenomena throughout the life of every economic enterprise, using data from a sample consisting of 100 companies from selected industries in the stock market and tehran, using empirical studies, delphi and fuzzy methods, factors and potential indicators. Effectively identified nicole participation. Finally, it was "observed that only" the accounting ratios introduced as the motivation of corporate defaults and other indicators including market indicators, macroeconomic indicators, non-financial indicators and interest rate indicators, do not have a map in predicting this event in the tehran stock exchange. . This research has also considered the indicators of accounting ratios as an indicator of reliability. According to the fact that the reliable markers differ according to the political, social and economic conditions of each child, the opinion of the experts in this field can be helpful to provide a model that is based on the environment of iran. The number of experts in this field is very less and the researcher has tried to discover the views of most of these experts. After the reliability indicators are determined, the participants can be ranked using mathematical or statistical models that require research.
Abad, P., Alsakka, R., & ap Gwilym, O. (2018). The influence of rating levels and rating convergence on the spillover effects of sovereign credit actions. Journal of International Money and Finance, 85, 40-57.
Indexed at, Google Scholar, Cross Ref
Ahmadi, Moussa (2016). Financial institution credit rating; Requirements and prerequisites of Burhan Credit Rating Company
Amiri, M., & Biglari Kami, M. (2013). Credit Rating Companies with Multi-Criteria Decision Making Models and Artificial Neural Network Model. Journal of basic and applied scientific research, 3(5), 536-546.
Asadi, Elahe; Torki, Leila and Daee Karim Zade, Saeed (2013). Ranking of stock exchange companies from the viewpoints of banks and financial institutions with improved AHP.DEA. Journal of Social Issues & Humanities 1(5). 88-93
Aysun, A. (2016). Structural shifts in credit rating standards. Researchgate. Net.
Indexed at, Google Scholar, Cross Ref
Bello, Qasim, Ahmed Vand, Maitham (2019). A model for predicting the default of a company in the Tehran Stock Exchange. Journal of Experimental Accounting Research, 10(36). [In Persian].
Bone, R. B. (2010). Determinants of corporate ratings in the oil industry: The Repsol-YPF case. REAd-Revista Eletrônica de Administração, 16(1), 70-90.
Daneshvar, Shahram, (2012), The use of MOSAT classification increases the transparency of the market, Dunyai Ekhtaz newspaper 322800. [In Persian].
Dorfleitner, G., Grebler, J., & Utz, S. (2019). The Impact of Corporate Social and Environment Performance on Credit Rating Prediction: North America versus Europe. Journal of Risk (Forthcoming).
Indexed at, Google Scholar, Cross Ref
Dayanti Dilami, Zahra (2014). Research method in accounting, first edition, Adalat Novin Publishing. [In Persian].
Ebrahimi, Marzieh and Daryaber, Abdullah (2011). Credit risk management in the banking system - data coverage analysis approach, logistic regression and neural network, Investment Knowledge Quarterly, 2.35-62 [In Persian].
Gray, S., Mirkovic, A., & Ragunathan, V. (2006). The determinants of credit ratings: Australian evidence. Australian Journal of Management, 31(2), 333-354.
Indexed at, Google Scholar, Cross Ref
Grunert, J., Norden, L., & Weber, M. (2005). The role of non-financial factors in internal credit ratings. Journal of banking & finance, 29(2), 509-531.
Indexed at, Google Scholar, Cross Ref
Hájek, P. (2012). Credit rating analysis using adaptive fuzzy rule-based systems: an industry-specific approach. Central European Journal of Operations Research, 20, 421-434.
Indexed at, Google Scholar, Cross Ref
Hwang, R. C., Chung, H., & Chu, C. K. (2010). Predicting issuer credit ratings using a semiparametric method. Journal of Empirical Finance, 17(1), 120-137.
Indexed at, Google Scholar, Cross Ref
Jiang, X., & Packer, F. (2017). Credit ratings of domestic and global agencies: What drives the differences in China and how are they priced?.
Jollineau, S. J., Tanlu, L. J., & Winn, A. (2014). Evaluating proposed remedies for credit rating agency failures. The Accounting Review, 89(4), 1399-1420.
Indexed at, Google Scholar, Cross Ref
Keller, T. (2006). The role and function of rating agencies. Press & Communications CH-4002 Basel, Switzerland E-mail: publications@ bis. or g Fax:+ 41 61 280 9100 and+ 41 61 280 8100 This publication is available on the BIS website (www. bis. org), 39.
Khazaei, A. H., & Farahanifard, S. (2021). The Potential Impacts of Credit Rating Agencies on the Islamic Republic of Iran’s economic performance. Journal of Iran's Economic Essays (JIEE), 18(35), 193-224.
Kohi Hassan & Rooh Elah Gholami (2012). Credit rating of legal clients in the industrial sector using the Data Envelopment Analysis (DEA) model Quantitative Studies in Management 3, 115 [In Persian].
Kumar, K., & Haynes, J. D. (2003). Forecasting credit ratings Using ANN and statistical techniques. International journal of business studies, 11(1), 91-108.
Langohr, H., & Langohr, P. (2010). The rating agencies and their credit ratings: What they are, how they work, and why they are relevant. John Wiley & Sons.
Indexed at, Google Scholar, Cross Ref
Mahmoud, a. H., & ghayouri, m. A. (2011). Credit rating in terms of financial ability to pay the principle and interest on debts, using data envelopment analysis techniques (case study: companies listed in tehran stock exchange).
Marcin, T. (2009). Application of Data Envelopment Analysis in Credit Scoring (Doctoral dissertation, Master’s Thesis in Financial Mathematics, Technical Report).
MurciaI, F. C. D. S., Dal-Ri Murcia, F., Rover, S., & Borba, J. A. (2014). The determinants of credit rating: Brazilian evidence. BAR-Brazilian Administration Review, 11, 188-209.
Indexed at, Google Scholar, Cross Ref
Poon, W. P., & Chan, K. C. (2008). An empirical examination of the informational content of credit ratings in China. Journal of Business Research, 61(7), 790-797.
Indexed at, Google Scholar, Cross Ref
Rai Reza & Bouzarsaroosh (2013). Validation of legal customers of small and medium banks using logit and probit models. Economic research quarterly (Iranian Islamic approach) - 44, 131-145 [In Persian].
Safari Saeed, Ebrahimi Shaghaghi, Marzieh , Tahiri Fard,& Morteza. (2013). Designing a credit rating model for legal customers in commercial banks using data coverage analysis; A comparative study of financial and non-financial indicators. Economic Sciences Research Journal . 12, 13-40[In Persian].
Salimpour, Maryam. (2015). A look beyond the performance of credit rating agencies. New Economy Journal 4 (113), 42-58204 [In Persian].
Shankar, S. (2019). The Role of credit rating agencies in addressing gaps in micro and small enterprise financing: The Case of India. In Unlocking sme finance in asia (pp. 72-87). Routledge.
Indexed at, Google Scholar, Cross Ref
Ratings, S. P. G. (2019). Guide to credit rating essentials: What are credit ratings and how do they work. Standard & Poor’s Financial Services LLC, 1-22.
Received: 21-Jun-2024, Manuscript No. AEJ-24-15093; Editor assigned: 24-Jun-2024, PreQC No. AEJ-24-15093 (PQ); Reviewed: 09-Jul-2024, QC No. AEJ-24-15093; Revised: 14-Jul-2024, Manuscript No. AEJ-24-15093 (R); Published: 21-Jul-2024