Credit rating modeling of pharmaceutical companies in Iran
Subject Areas : Journal of Investment Knowledgesaeed sirghani 1 , behrooz khodarahmi 2 , javad rezazadeh 3 , jalil delkhah 4
1 - PhD student in accounting, Accounting Department of TMU
2 - Associate Professor, Member of the academic staff of the accounting department of TMU
3 - Associate Professor, Member of the academic staff of the accounting department of TMU
4 - Assistant Professor, Member of the academic staff of the management department of TMU
Keywords: credit rating, exploratory research, Pharmaceutical industry, information asymmetry,
Abstract :
Information asymmetry has made it difficult for lenders and borrowers to make the right decisions regarding lending and borrowing that credit rating can solve these problems by clarifying the status and desirability of the borrower's credit. These problems are shown more in industries, including the pharmaceutical industry, which has specific restrictions and characteristics governing the industry in the country. Therefore, the aim of the current research is to present the credit rating models of companies for the pharmaceutical industry based on the characteristics and conditions governing the pharmaceutical industry in Iran and in the direction of enriching the knowledge of credit rating. The current research is based on studying and reviewing the texts and guidelines of Moody's rating agency and extracting the primary credit rating factors of companies active in the pharmaceutical industry, conducting interviews with experts and analysts of companies active in the pharmaceutical industry, conducting surveys and removing and adding effective factors on the credit rating of pharmaceutical industry companies. And by using formal and content validity tests and confirmatory factor analysis as well as binomial test, the final indicators of credit rating of pharmaceutical companies were extracted and finally, the priority and importance of these indicators were evaluated using Friedman's test.
کردستانی، غلامرضا (1393)، ارزیابی توان پیش بینی مدلهای ورشکستگی، دانش حسابرسی، 14 (55)، 31-57.
خواجوی، شکرالله، فرج پور، فرهنگ (1391)، تاثیر ویژگی‌های هیات مدیره بر مدلهای پیش بینی ورشکستگی آلتمن و اهلسن، پژوهشهای کاربردی در گزارشگری مالی، 1 (1)، 107-132.
ابراهیم زاده، امیر و سعیدی، پرویز (1397). تحلیل و واکاوی ریسک اعتباری و ارتباط آن با رتبه بندی اعتباری شرکت، فصلنامه علمی تخصصی مدیریت، حسابداری و اقتصاد، 2 (3)، 70-83.
شاهرخی، سیده سمانه و مشایخ، شهناز (1395). شناسایی شاخص های تعیین کننده رتبه اعتباری شرکتها، فصلنامه علمی پژوهشی دانش سرمایه گذاری، 5 (19)، 25-52.
شاهرخی، سیده سمانه و مشایخ، شهناز (1394)، نظام رتبه بندی اعتباری شرکتها در دنیا، پژوهش حسابداری، 16 (1)، 131-147.
حاجیها، زهره و قیلاوی، منی (1391). استفاده از تکنیک تحلیل پوششی داده ها برای سنجش کارایی شرکت های تولیدی پذیرفته شده در بورس اوراق بهادار تهران با استفاده از مدل مبتنی بر گزارشگری مالی. مجله مهندسی مالی و مدیریت اوراق بهادار، 12 (1)، 111-130.
حاجیها، زهره و قربانی، ایوب (1400)، بررسی تأثیر ریسک عدم بازپرداخت بدهیها بر رتبه‌بندی اعتباری با توجه به نقش تعدیلی محدودیت مالی، حسابداری مدیریت، 14 (15)، 1-13.
خانزاده، محمد، محقق نیا، محمدجواد و ابراهیمی، محمدحسن (1398). طراحی الگوی رتبه بندی اعتباری بانکهای اسلامی ایران. دوفصلنامه علمی تحقیقات مالی اسلامی، 9 (1)، 327-366.
قاسم پور، شیوا و ارضاء، امیرحسین (1396). رتبه بندی بانکهای خصوصی ایران بر اساس مدل کملز با استفاده از رویکرد ترکیبی فرآیند تحلیل سلسله مراتبی و آرس. فصلنامه راهبرد مدیریت مالی، 5(18)، 99-118.
قدیری مقدم، ابوالفضل، غلامپور فرد، محمد مسعود و نصیرزاده، فرزانه (1388). بررسی توانایی مدلهای پیش بینی ورشکستگی آلتمن و اهلسون در پیش بینی ورشکستگی شرکتهای بورس اوراق بهادار تهران، مجله دانش و توسعه، 28 (2)، 193-220.
محمودآبادی حمید و علی غیوری مقدم (1390)، رتبه بندی اعتباری از لحاظ توان مالی پرداخت اصل و فرع بدهیها با استفاده از شیوه تحلیل پوششی داده ها (مورد مطالعه: شرکتهای پذیرفته شده در بورس اوراق بهادار تهران)، مجله دانش حسابداری، 2 (4) ، 125-145.
Bone R.B (2006). Determinants of Corporate Ratings in the Oil Industry. the Repsol-YPF Case, Avaliado pelo sistema double blind review. 16 )1(. 1-21.
Gray, Stephen; Mirkovic, Alexsander and Ragunathan, Vanitha (2006). The Determinants of Credit Ratings: Australian Evidence. Australian Journal of Management. (31). 333-354
Keller, Thomas (2005). The role and function of rating agencies. BIS/PBC Seminar on Developing Corporate Bond Markets in Asia in Kunming, China
Cantor, R., & Packer, F. (1997). Differences of opinion and selection bias in the credit rating industry, Journal of Banking & Finance, 21(10), 1395-1417
Cantor, R., and Packer, F. (1994). The Credit Rating Industry, Federal Reserve Bank of New York Quarterly Review. 19(2). 1-26
Langohr, Herwig and Langohr, Patricia, (2009). The Rating Agencies and Their Credit Ratings: What They Are, How They Work, and Why They are Relevant, Wiley Finance Series. ISBN: 978-0-470-01800-2.
MurciaI, Flávia Cruz de Souza, Dal-Ri Murcia, Fernando, Rover, Suliani, & Borba, José Alonso. (2014). The determinants of credit rating: brazilian evidence. BAR - Brazilian Administration Review, 11(2), 188-209.
Dittrich, F. (2007). The Credit Rating Industry: Competition and Regulation. working paper, University of Cologne Department of Economics. http: ssrn.com
Frank, Simon James, (2009). Predicting Corporate Credit Ratings using Neural Network Models. for the degree of Master of Business Administration at the University of Stellenbosch.
Ederington, L. (1985). classification models and bond ratings, The Financial Review . 20(4). 237-261
Kamstra, Mark; Kennedy, Peter and Suan, Teck-Kin (2001). Combining bond rating forecasts using logit. The Financial Review. 37. 75-96
Ashbaugh-Skaife, H , Collins,D.W & LaFond, R. (2006). The effects of corporate governance on firms’ credit ratings. Journal of Accounting and Economics 42. 203-243.
Matthies A. (2013). Empirical Research on Corporate Credit Ratings: A Literature Review. , SFB 649 Discussion Paper. 1-28
Beaver, W. H. (1966). Financial Ratios as Predictors of Failure. Empirical Research in Accounting: Selected Studies. 4(3). 71–111.
Altman, E .(1968) .Financial ratios, discriminant analysis and the prediction of corporate bankruptcy, The Journal of Finance 23(4). 589 – 609.
Altman, E. e Katz, S. (1976). Statistical Bond Rating Classification Using Financial and Accounting data, in Michael Schiff e George Sorter (eds.), Proceedings of the Conference on Topícal Research in Accounting. (New York: New York University School of Business), 205-239
Ohlson, J. A. (1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research, Vol. 18, pp. 109-131
Adams, M, Burton, B., & Hardwick, P. (2003). The determinants of credit ratings in the United Kingdom insurance industry. Journal of Business Finance & Accounting, 30(3/4), 539-572.
Akdemie, Ali and Karsl, Durdu (2012). An assessment of strategic importance of credit rating agencies for companies and organizations. Social and Behavioral Sciences, 58 , 1628 – 1639.
Blume, Marshall E; Lim, Felix and Mackinlay, A. Craig (1998). The declining credit quality of US corporate debt: Myth or reality?. Journal of Finance .53(4), 1389 – 1413
Becker, B., and Milbourn, T. (2011). How did Increased Competition Affect Credit Ratings? Journal of Financial Economics.101. 493-514
Guo, Xuesong; Zhu, Zhengwei and Shi, Jia (2012). A Corporate Credit Rating Model Using Support Vector Domain Combined with Fuzzy Clustering Algorithm, Mathematical Problemsin Engineering 10.1155, 1-20.
Kaplan, R., G. Urwitz (1979). Statistical models of bond ratings: A methodological inquiry, Journal of Business. 52, 231 – 261
Ederington, L. (1985). classification models and bond ratings, The Financial Review . 20(4). 237-261
Kamstra, Mark; Kennedy, Peter and Suan, Teck-Kin (2001). Combining bond rating forecasts using logit. The Financial Review. 37. 75-96
Gray, Stephen; Mirkovic, Alexsander and Ragunathan, Vanitha (2006). The Determinants of Credit Ratings: Australian Evidence. Australian Journal of Management. (31). 333-354
Xiaolu, Hu; and et al (2019). Information asymmetry and credit rating: A quasi-natural experiment from China. Journal of Banking & Finance. 106 (1), 132-152.
Blomkvist, M., Löflund, A., & Vyas, H. (2020). Credit ratings and firm life-cycle. Economics letters, (5), [101598]. https://doi.org/10.1016/j.frl.2020.101598.
Kladakis, George; Chen, Lei and Sotirios K. Bellos (2021). Bank Asset and Informational Quality. Journal of International Financial Markets, Institutions and Money, (69) 39.
Aktas, Nihat; Petmezas, Dimitris and Henri. Servaes (2021). Credit ratings and acquisitions. Journal of Corporate Finance, (69) 2.
Fitch Ratings (2014). Definitions of Ratings and Other Forms of Opinion. 1-59. www.fitchratings.com
IOSCO (International Organisation of Securities Commissions).(2008). Report on the role of credit rating agencies structured finance markets to the IOSCO, May.
Moody`s Rating Service (2015). Rating Symbols and Defiitions. www.moodys. Com
Moody’s Investor Service (2004), Special Report: Annual Default Study Addendum,: Global Corporate Rating Transition Rates, www.moodys.com
Standard & Poor’s (2001). Rating Methodology: Evaluating the Issuer. Corporate Rating Criteria. (New York: Standard & Poor’s)
Standard & Poor’s (2008). Corporate Rating Criteria. www.corporatecriteria. standardandpoors.com
Standard & Poor’s (2013). Corporate Rating Criteria. Regulation body of knowledge.org
Standard & Poor’s Ratings Services. (2011). Guide to credit rating essentials: what are credit ratings and how do they work? Retrieved from http://img.en25.com
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