Is credit rating reserved territory for credit rating agencies? A MULTIMOORA approach for European firms and countries
Abstract
Credit Rating Agencies rate firms and countries by internal experts but with a final qualitative judgment by their management acting as decision makers. These ratings on their turn influence the countries credit rating and ipso facto of their enterprises. The work of the CRA is in fact double: credit rating of firms and other organizations at one side and countries on the other. Considering the credit rating of firms, the CRA made significant mistakes during the Recession 2007−2009 and their judgment is too much American oriented, in any way from a European point of view. Consequently, in Europe many efforts were made to come to a new agency, but all efforts failed. It could be different for the rating of countries. Is a more scientific approach, eventually on a quantitative and structural basis, not possible? Therefore, MULTIMOORA, a quantitative method, is suggested. The study was made for all countries of the European Continent. Based on data available in 2013 and on their extrapolation, the results are quite comparable to the results of Standard & Poor’s Credit Rating System of the moment. As the classifications of Moody’s and Fitch are very similar to those of Standard & Poor’s the outcome would be similar for these other Credit Rating Agencies.
Keyword : credit rating agencies, multi-objective optimization, ratio system, reference point method, full multiplicative form, MULTIMOORA
How to Cite
Brauers, W. K. M., & Lepkova, N. (2019). Is credit rating reserved territory for credit rating agencies? A MULTIMOORA approach for European firms and countries. Technological and Economic Development of Economy, 25(6), 1259-1281. https://doi.org/10.3846/tede.2019.10722
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Brauers, W. K. M. (2018). Location theory and multi-criteria decision making:an application of the MOORA method. Contemporary Economics, 12(3), 241-252.
Brauers, W. K. M., Baležentis, A., & Baležentis, T. (2012). European Union Member States preparing for Europe 2020. An application of the MULTIMOORA method. Technological and Economic Development of Economy, 18(4), 567-587.
Brauers, W. K. M., Baležentis, A., & Baležentis, T. (2018). Analysis, a possible solution for the standard error in sampling? Journal of Modern Technology & Engineering, 3(1), 1-14.
Brauers, W. K. M., & Zavadskas, E. K. (2013). Multi-objective evaluation of the European Union member states. As opposed to Credit Rating Agencies opinions? Transformations in Business & Economics, 12, 2(29), 102-124.
Brauers, W. K. M., & Zavadskas, E. K. (2011). MULTIMOORA optimization used to decide on a bank loan to buy property. Technological and Economic Development of Economy, 179(1), 174-188. https://doi.org/10.3846/13928619.2011.560632
Brauers, W. K. M., & Zavadskas, E. K. (2010a). Project management by MULTIMOORA as an instrument for transition economies. Technological and Economic Development of Economy, 16(1), 5-24. https://doi.org/10.3846/tede.2010.01
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Brauers, W. K. M., & Zavadskas, E. K. (2006). The MOORA method and its application to privatization in a transition economy. Control and Cybernetics, 35(2), 443-469.
Brauers, W. K. M., Zavadskas, E. K., & Lepkova, N. (2017). The future of facilities management in Lithuania. Romanian Journal of Economic Forecasting, 20(1), 98-115.
Chakraborty, S. (2011). Applications of the MOORA method for decision making in manufacturing environment. International Journal Advanced Manufacturing Technology, 54, 1155-1166. https://doi.org/10.1007/s00170-010-2972-0
Clark, R. (2010). World-system mobility and economic growth 1981-2000. Social Forces, 88(3), 11231151. https://doi.org/10.1353/sof.0.0295
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Dahooie, J. H., Zavadskas, E. K., Firoozfar, H. R., Vanaki, A. S., Mohammadi, N., & Brauers, W. K. M. (2019). An improved fuzzy MULTIMOORA approach for multi-criteria decision making based on objective weighting method (CCSD) and its application to technological forecasting method selection. Engineering Applications of Artificial Intelligence, 79, 114-128. https://doi.org/10.1016/j.engappai.2018.12.008
Despontin, M., Moscarola, J., & Spronk, J. (1983). A user-oriented listing of multiple criteria decision methods. Revue Belge de Statistique, d’Informatique et de Recherche Operationnelle, 23(4), 3-110.
Money Expert. Deutsche Bank. (2011). Retrieved from https://www.deutschebank.be/nl/ratings.html
Doumpos, M., & Figueira, J. R. (2019). A multicriteria outranking approach for modeling corporate credit ratings: an application of the Electre Tri-nC method. Omega, 82, 166-180. https://doi.org/10.1016/j.omega.2018.01.003
Driss, H., Massoud, N., & Roberts, G. S. (2016). Are credit rating agencies still relevant? Evidence on certification from Moody’s credit watches. Journal of Corporate Finance (in press). https://doi.org/10.1016/j.jcorpfin.2016.08.003
European Commission. (2016). Study on the state of the credit rating market (Final report). Retrieved from https://ec.europa.eu/info/system/files/state-of-credit-rating-market-study-01012016_en.pdf
ESMA. (2011). Retrieved from https://www.esma.europa.eu/about-esma
Gagnon, J. E. (2011). The Global Outlook for Government Debt over the next 25 years: implications for the Economy and Public Policy (Vol. 34). Peterson Institute for International Economics, Washington D.C.
Gordon, T. J., Enzer, S., & Rochberg, R. (1970). An experiment in simulation gaming for social policy studies. Technological Forecasting, 1(3), 241-261. https://doi.org/10.1016/0099-3964(70)90027-X
Hafezalkotob, A., & Hafezalkotob, A. (2017). Interval MULTIMOORA method with target values of attributes based on interval distance and preference degree: biomaterials selection. Journal of Industrial Engineering International, 13(2), 181-198. https://doi.org/10.1007/s40092-016-0176-4
Hafezalkotob, A., Hafezalkotob, A., Liao, H., & Herrera, F. (2019). An overview of MULTIMOORA for multi-criteria decision-making: theory, developments, applications, and challenges. Information Fusion, 51, 145-177. https://doi.org/10.1016/j.inffus.2018.12.002
Heredia, F. M. (2012, April 7). De Tijd (Flemish financial news paper, pp. 8-9). Brussels.
Herkenhoff, L., & Fogli, J. (2013). Applied Statistics for Business and Management using Microsoft Excel. New York: Springer. https://doi.org/10.1007/978-1-4614-8423-3
Hodge, N. (2017, October 24). EC takes on Ireland and Luxembourg over tax avoidance, Compliance Week. Boston. Retrieved from http://www.complianceweek.com/authors/neil-hodge
Human Development Report. (2018). Human Development Indices and Indicators, HDRO. United Nations Development Programme, United Nations.
Karlin, S., & Studden, W. J. (1966). Tchebycheff systems: with applications in analysis and statistics. New York: Interscience Publishers.
Karuppanna, P. N., & Sekar, K. (2016). Selection of best alternative in manufacturing and service sector using multigrade decision approach – a review. Computer Science and Information Technology, 57-74.
Kim, H. A. (2019). Are inflated domestic credit ratings relative to global ratings associated with peer firms’ investment decisions? Evidence from Korea. Japan and the World Economy, 51, 100956. https://doi.org/10.1016/j.japwor.2019.04.001
L’Ile Maurice. (1990). Nouvelles frontières. Jaguar/Editions, Paris.
Liu, H.-C., You, J.-X., Lu, C., & Chen, Y.-Z. (2015). Evaluating health-care waste treatment technologies using a hybrid multi-criteria decision making model. Renewable and Sustainable Energy Reviews, 41, 932-942. https://doi.org/10.1016/j.rser.2014.08.061
Luitel, P., Vanpée, R., & De Moor, L. (2016). Pernicious effects: how the credit rating agencies disadvantage emerging markets. Research in International Business and Finance, 38, 286-298. https://doi.org/10.1016/j.ribaf.2016.04.009
Maghsoodi, A. I., Abouhamzeh, G., Khalilzadeh, M., & Zavadskas, E. K. (2018). Ranking and selecting the best performance appraisal method using the MULTIMOORA approach integrated Shannon’s entropy. Frontiers of Business Research in China, 12(2), 1-21. https://doi.org/10.1186/s11782-017-0022-6
Marandola, G. (2016). InkLocal credit rating agencies: a new dataset. Research in International Business and Finance, 38, 83-103. https://doi.org/10.1016/j.ribaf.2016.03.006
Michel, A. (2014, November 5, 6). Le Luxembourg, plaque tournante de l’évasion fiscale. Le Monde, 5-11.
Ng, A., & Ariff, M. (2019, February 22). Does credit rating revision affect the price of a special class of common stock? Borsa Istanbul Review (in press). https://doi.org/10.1016/j.bir.2019.02.004
Obermayer, B. (2014, December 5). Day in fiscal paradise, chasing Letterbox Leads in Luxemburg. Süddeutsche Zeitung.
OECD. (2018). Economic Outlook, 103 database, Stat Link. Retrieved from https://stats.oecd.org/index.aspx?datasetcode=eo103_ltb
Park, G., & Lee, H.-Y. (2018). Opportunistic behaviors of credit rating agencies and bond issuers. Pacific-Basin Finance Journal, 47, 39-59. https://doi.org/10.1016/j.pacfin.2017.11.003
Regulating Credit Rating Agencies. (2013). Retrieved from https://ec.europa.eu/info/business-economy-euro/banking-and-finace/financialsupervision-and-risk-management/management-riskbanks-and-financial-institutions/regulating-credit-rating-agencies
Quirk, T. (2011). Excel 2010 for business statistics. New York: Springer. https://doi.org/10.1007/978-1-4419-9934-4
SEC, US Securities and Exchange Commission. (2016). Annual Report on nationally recognized statistical organizations, as required by section 6 of the Credit Rating Agency Reform Act of 2006.
Siksnelyte, I., Zavadskas, E. K., Bausys, R., & Streimikiene, D. (2019). Implementation of EU energy policy priorities in the Baltic Sea Region countries: sustainability assessment based on neutrosophic MULTIMOORA method. Energy Policy, 125, 90-102. https://doi.org/10.1016/j.enpol.2018.10.013
Sovereigns Ratings List. (2018). S&P, Moody’s, Fitch Ratings each for 2018. Retrieved from https://countryeconomy/com/ratings
TalhaYalta, A., & YaseminYalta, A. (2018). Are credit rating agencies regionally biased? Economic Systems, 42, 682-694. https://doi.org/10.1016/j.ecosys.2018.08.001
Tchebycheff, P. L. (1947). Complete collected works. Moscow-Leningrad.
Türe, H., Kocak, D., & Dogan, S. (2016). Country risk assessment with MULTIMOORA method (in Turkish). Gazi Universitesi iktisadi ve idari bilimler fakültesi dergisi, 18(3), 824-844.
White, L. J. (2010). The credit rating agencies. Journal of Economic Perspectives, 24(2), 211-226. https://doi.org/10.1257/jep.24.2.211
Zavadskas, E. K., Bausys, R., Juodagalviene, B., & Garnyte-Sapranaviciene, I. (2017). Model for residential house element and material selection by neutrosophic MULTIMOORA Method. Engineering Applications of Artificial Intelligence, 64, 315-324. https://doi.org/10.1016/j.engappai.2017.06.020
Zhou, W. Y., You, X. Y., Zhao, H., & Liu, H. C. (2018). Robot evaluation and selection using the hesitant fuzzy linguistic MULTIMOORA method. Journal of Testing and Evaluation, 47(2), 560-690. https://doi.org/10.1520/JTE20170094
Bertelsmann Stiftung. (2012). Blueprint for INCRA, an international non-profit credit rating agency. Retrieved from http://www.bfna.org
Berger, R. (2012, January 12). Corriere della Sera. In De Tijd (Flemish financial newspaper).
Binici, M., & Hutchison, M. (2018). Do credit rating agencies provide valuable information in market evaluation of sovereign default Risk? Journal of International Money and Finance, 85, 58-75. https://doi.org/10.1016/j.jimonfin.2018.04.001
Brauers, W. K. M. (1998). Internationaal Voetbalstadion te Antwerpen (Dutch for International Football Stadium in Antwerp). Consulting, Antwerp.
Brauers, W. K. M. (2018). Location theory and multi-criteria decision making:an application of the MOORA method. Contemporary Economics, 12(3), 241-252.
Brauers, W. K. M., Baležentis, A., & Baležentis, T. (2012). European Union Member States preparing for Europe 2020. An application of the MULTIMOORA method. Technological and Economic Development of Economy, 18(4), 567-587.
Brauers, W. K. M., Baležentis, A., & Baležentis, T. (2018). Analysis, a possible solution for the standard error in sampling? Journal of Modern Technology & Engineering, 3(1), 1-14.
Brauers, W. K. M., & Zavadskas, E. K. (2013). Multi-objective evaluation of the European Union member states. As opposed to Credit Rating Agencies opinions? Transformations in Business & Economics, 12, 2(29), 102-124.
Brauers, W. K. M., & Zavadskas, E. K. (2011). MULTIMOORA optimization used to decide on a bank loan to buy property. Technological and Economic Development of Economy, 179(1), 174-188. https://doi.org/10.3846/13928619.2011.560632
Brauers, W. K. M., & Zavadskas, E. K. (2010a). Project management by MULTIMOORA as an instrument for transition economies. Technological and Economic Development of Economy, 16(1), 5-24. https://doi.org/10.3846/tede.2010.01
Brauers, W. K. M., & Zavadskas, E. K. (2010b). Robustness in the MULTIMOORA model, the example of Tanzania. Transformations in Business & Economics, 9, 3(21), 67-83.
Brauers, W. K. M., & Zavadskas, E. K. (2006). The MOORA method and its application to privatization in a transition economy. Control and Cybernetics, 35(2), 443-469.
Brauers, W. K. M., Zavadskas, E. K., & Lepkova, N. (2017). The future of facilities management in Lithuania. Romanian Journal of Economic Forecasting, 20(1), 98-115.
Chakraborty, S. (2011). Applications of the MOORA method for decision making in manufacturing environment. International Journal Advanced Manufacturing Technology, 54, 1155-1166. https://doi.org/10.1007/s00170-010-2972-0
Clark, R. (2010). World-system mobility and economic growth 1981-2000. Social Forces, 88(3), 11231151. https://doi.org/10.1353/sof.0.0295
Credit Rating Agencies. (2009). Regulation (Ec)No1060-2009. Retrieved from https://ec.europa.eu/info/law/credit-rating-agencies-regulation-ec-no-1060-2009
Credendo. (2019, February 12). Retrieved from www.credendo.com
Dahooie, J. H., Zavadskas, E. K., Firoozfar, H. R., Vanaki, A. S., Mohammadi, N., & Brauers, W. K. M. (2019). An improved fuzzy MULTIMOORA approach for multi-criteria decision making based on objective weighting method (CCSD) and its application to technological forecasting method selection. Engineering Applications of Artificial Intelligence, 79, 114-128. https://doi.org/10.1016/j.engappai.2018.12.008
Despontin, M., Moscarola, J., & Spronk, J. (1983). A user-oriented listing of multiple criteria decision methods. Revue Belge de Statistique, d’Informatique et de Recherche Operationnelle, 23(4), 3-110.
Money Expert. Deutsche Bank. (2011). Retrieved from https://www.deutschebank.be/nl/ratings.html
Doumpos, M., & Figueira, J. R. (2019). A multicriteria outranking approach for modeling corporate credit ratings: an application of the Electre Tri-nC method. Omega, 82, 166-180. https://doi.org/10.1016/j.omega.2018.01.003
Driss, H., Massoud, N., & Roberts, G. S. (2016). Are credit rating agencies still relevant? Evidence on certification from Moody’s credit watches. Journal of Corporate Finance (in press). https://doi.org/10.1016/j.jcorpfin.2016.08.003
European Commission. (2016). Study on the state of the credit rating market (Final report). Retrieved from https://ec.europa.eu/info/system/files/state-of-credit-rating-market-study-01012016_en.pdf
ESMA. (2011). Retrieved from https://www.esma.europa.eu/about-esma
Gagnon, J. E. (2011). The Global Outlook for Government Debt over the next 25 years: implications for the Economy and Public Policy (Vol. 34). Peterson Institute for International Economics, Washington D.C.
Gordon, T. J., Enzer, S., & Rochberg, R. (1970). An experiment in simulation gaming for social policy studies. Technological Forecasting, 1(3), 241-261. https://doi.org/10.1016/0099-3964(70)90027-X
Hafezalkotob, A., & Hafezalkotob, A. (2017). Interval MULTIMOORA method with target values of attributes based on interval distance and preference degree: biomaterials selection. Journal of Industrial Engineering International, 13(2), 181-198. https://doi.org/10.1007/s40092-016-0176-4
Hafezalkotob, A., Hafezalkotob, A., Liao, H., & Herrera, F. (2019). An overview of MULTIMOORA for multi-criteria decision-making: theory, developments, applications, and challenges. Information Fusion, 51, 145-177. https://doi.org/10.1016/j.inffus.2018.12.002
Heredia, F. M. (2012, April 7). De Tijd (Flemish financial news paper, pp. 8-9). Brussels.
Herkenhoff, L., & Fogli, J. (2013). Applied Statistics for Business and Management using Microsoft Excel. New York: Springer. https://doi.org/10.1007/978-1-4614-8423-3
Hodge, N. (2017, October 24). EC takes on Ireland and Luxembourg over tax avoidance, Compliance Week. Boston. Retrieved from http://www.complianceweek.com/authors/neil-hodge
Human Development Report. (2018). Human Development Indices and Indicators, HDRO. United Nations Development Programme, United Nations.
Karlin, S., & Studden, W. J. (1966). Tchebycheff systems: with applications in analysis and statistics. New York: Interscience Publishers.
Karuppanna, P. N., & Sekar, K. (2016). Selection of best alternative in manufacturing and service sector using multigrade decision approach – a review. Computer Science and Information Technology, 57-74.
Kim, H. A. (2019). Are inflated domestic credit ratings relative to global ratings associated with peer firms’ investment decisions? Evidence from Korea. Japan and the World Economy, 51, 100956. https://doi.org/10.1016/j.japwor.2019.04.001
L’Ile Maurice. (1990). Nouvelles frontières. Jaguar/Editions, Paris.
Liu, H.-C., You, J.-X., Lu, C., & Chen, Y.-Z. (2015). Evaluating health-care waste treatment technologies using a hybrid multi-criteria decision making model. Renewable and Sustainable Energy Reviews, 41, 932-942. https://doi.org/10.1016/j.rser.2014.08.061
Luitel, P., Vanpée, R., & De Moor, L. (2016). Pernicious effects: how the credit rating agencies disadvantage emerging markets. Research in International Business and Finance, 38, 286-298. https://doi.org/10.1016/j.ribaf.2016.04.009
Maghsoodi, A. I., Abouhamzeh, G., Khalilzadeh, M., & Zavadskas, E. K. (2018). Ranking and selecting the best performance appraisal method using the MULTIMOORA approach integrated Shannon’s entropy. Frontiers of Business Research in China, 12(2), 1-21. https://doi.org/10.1186/s11782-017-0022-6
Marandola, G. (2016). InkLocal credit rating agencies: a new dataset. Research in International Business and Finance, 38, 83-103. https://doi.org/10.1016/j.ribaf.2016.03.006
Michel, A. (2014, November 5, 6). Le Luxembourg, plaque tournante de l’évasion fiscale. Le Monde, 5-11.
Ng, A., & Ariff, M. (2019, February 22). Does credit rating revision affect the price of a special class of common stock? Borsa Istanbul Review (in press). https://doi.org/10.1016/j.bir.2019.02.004
Obermayer, B. (2014, December 5). Day in fiscal paradise, chasing Letterbox Leads in Luxemburg. Süddeutsche Zeitung.
OECD. (2018). Economic Outlook, 103 database, Stat Link. Retrieved from https://stats.oecd.org/index.aspx?datasetcode=eo103_ltb
Park, G., & Lee, H.-Y. (2018). Opportunistic behaviors of credit rating agencies and bond issuers. Pacific-Basin Finance Journal, 47, 39-59. https://doi.org/10.1016/j.pacfin.2017.11.003
Regulating Credit Rating Agencies. (2013). Retrieved from https://ec.europa.eu/info/business-economy-euro/banking-and-finace/financialsupervision-and-risk-management/management-riskbanks-and-financial-institutions/regulating-credit-rating-agencies
Quirk, T. (2011). Excel 2010 for business statistics. New York: Springer. https://doi.org/10.1007/978-1-4419-9934-4
SEC, US Securities and Exchange Commission. (2016). Annual Report on nationally recognized statistical organizations, as required by section 6 of the Credit Rating Agency Reform Act of 2006.
Siksnelyte, I., Zavadskas, E. K., Bausys, R., & Streimikiene, D. (2019). Implementation of EU energy policy priorities in the Baltic Sea Region countries: sustainability assessment based on neutrosophic MULTIMOORA method. Energy Policy, 125, 90-102. https://doi.org/10.1016/j.enpol.2018.10.013
Sovereigns Ratings List. (2018). S&P, Moody’s, Fitch Ratings each for 2018. Retrieved from https://countryeconomy/com/ratings
TalhaYalta, A., & YaseminYalta, A. (2018). Are credit rating agencies regionally biased? Economic Systems, 42, 682-694. https://doi.org/10.1016/j.ecosys.2018.08.001
Tchebycheff, P. L. (1947). Complete collected works. Moscow-Leningrad.
Türe, H., Kocak, D., & Dogan, S. (2016). Country risk assessment with MULTIMOORA method (in Turkish). Gazi Universitesi iktisadi ve idari bilimler fakültesi dergisi, 18(3), 824-844.
White, L. J. (2010). The credit rating agencies. Journal of Economic Perspectives, 24(2), 211-226. https://doi.org/10.1257/jep.24.2.211
Zavadskas, E. K., Bausys, R., Juodagalviene, B., & Garnyte-Sapranaviciene, I. (2017). Model for residential house element and material selection by neutrosophic MULTIMOORA Method. Engineering Applications of Artificial Intelligence, 64, 315-324. https://doi.org/10.1016/j.engappai.2017.06.020
Zhou, W. Y., You, X. Y., Zhao, H., & Liu, H. C. (2018). Robot evaluation and selection using the hesitant fuzzy linguistic MULTIMOORA method. Journal of Testing and Evaluation, 47(2), 560-690. https://doi.org/10.1520/JTE20170094