Evaluating the Factors Affecting on Credit Ratings of Accepted Corporates in Tehran Securities Exchange by Using Factor Analysis and AHP
الموضوعات :Ahmad Mohammaddoost 1 , Mir Feiz Falah Shams Dialestani 2 , Madjid Eshaghi Gordji 3 , Ali Ebadian 4
1 - Department of Mathematics, Payame Noor University Tehran, Iran
2 - Business Faculty, Tehran Central Branch, Islamic Azad University, Tehran, Iran
3 - Department of Mathematics, Semnan University,, Semnan, Iran.
4 - Department of Mathematics, Urmia University, Urmia, Iran
الکلمات المفتاحية: Credit ratings, factor analysis, Financial ratios, analytic hierarchy process, Non-financial ratios,
ملخص المقالة :
Implementation credit rating for Corporates is influenced by Different circum-stances, systems, processes, and cultures in each country. In this study, we pro-posed a Factor analysis modified approach for determine important factors on real data set of 123 accepted corporate in Tehran Securities Exchange for the years 2009-2017 of diverse range of 52 variable. We estimated the priority score for 49 factors. The three factors, Debt to Equity Ratio, Current debt-to-equity ratio and proprietary ratio exclude due to high correlation with others. The results indicated that three macroeconomic factors: Price Index of Consumer Goods and Services, exchange rate and Interest rate determinants were more effective on the credit ratings. In addition, Financial Ratios and non-Financial Ratios such as Return on equity (ROE), Long-term debt-to-equity ratio, Benefit of the loan, ratio of com-modity to working capital, Current capital turnover, Return on Working Capital, Quick Ratio, Current Ratio, Net Profit margin, Gross profit margin, had effect on credit rating accepted corporate in Tehran Securities Exchange. The Nonparametric statistical test to validate the consistency between AHP ranking and Factor analysis revealed, the new approach has a moderated consistency with AHP. In conclusion, the Factor analysis modified approach could be applied significantly to evaluate efficiency and ranking factors with minimum loss of information.
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