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A multivariate study of spanish bond ratings

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  • Mar Molinero, C.
  • Apellaniz Gomez, P.
  • Serrano Cinca, C.

Abstract

In this paper we analyse the ratings given in 1993 to the main Spanish banks, both private and governmental. We use 24 financial ratios obtained from the balance and the profit and loss accounts. Multidimensional scaling (MDS), a multivariate technique which is intuitive and robust to the data, forms the basis of the study. This is complemented with other multivariate statistical techniques such as cluster analysis, property fitting (ProFit) and discriminant analysis. The results identify the financial information that has been used by the rating agency. They also confirm the conjecture that other factors, such as the public or private character of the institution, have also been taken into account by the rating agents.

Suggested Citation

  • Mar Molinero, C. & Apellaniz Gomez, P. & Serrano Cinca, C., 1996. "A multivariate study of spanish bond ratings," Omega, Elsevier, vol. 24(4), pages 451-462, August.
    • Handle: RePEc:eee:jomega:v:24:y:1996:i:4:p:451-462
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    References listed on IDEAS

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    1. West, Rr, 1970. "Alternative Approach To Predicting Corporate Bond Ratings," Journal of Accounting Research, Wiley Blackwell, vol. 8(1), pages 118-125.
    2. Frances Provan & Lester, 1993. "Spss: Version 5 for Windows," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 42(4), pages 686-690, December.
    3. Pogue, Thomas F. & Soldofsky, Robert M., 1969. "What's in a Bond Rating*," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 4(2), pages 201-228, June.
    4. Pinches, George E & Mingo, Kent A, 1973. "A Multivariate Analysis of Industrial Bond Ratings," Journal of Finance, American Finance Association, vol. 28(1), pages 1-18, March.
    5. Cecilio Mar-Molinero & Carlos Serrano-Cinca, 2001. "Bank failure: a multidimensional scaling approach," The European Journal of Finance, Taylor & Francis Journals, vol. 7(2), pages 165-183.
    6. J. Kruskal, 1964. "Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis," Psychometrika, Springer;The Psychometric Society, vol. 29(1), pages 1-27, March.
    7. Pinches, George E & Mingo, Kent A, 1975. "The Role of Subordination and Industrial Bond Ratings," Journal of Finance, American Finance Association, vol. 30(1), pages 201-206, March.
    8. Horrigan, Jo, 1966. "Determination Of Long-Term Credit Standing With Financial Ratios," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 44-62.
    9. Ang, James S & Patel, Kiritkumar A, 1975. "Bond Rating Methods: Comparison and Validation," Journal of Finance, American Finance Association, vol. 30(2), pages 631-640, May.
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    Cited by:

    1. Malcolm J. Beynon, 2005. "Optimizing object classification under ambiguity/ignorance: application to the credit rating problem," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 13(2), pages 113-130, June.
    2. Sun, Yue & Chai, Nana & Dong, Yizhe & Shi, Baofeng, 2022. "Assessing and predicting small industrial enterprises’ credit ratings: A fuzzy decision-making approach," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1158-1172.
    3. C Mar-Molinero & J Mingers, 2007. "An evaluation of the limitations of, and alternatives to, the Co-Plot methodology," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(7), pages 874-886, July.
    4. Patrycja Chodnicka-Jaworska, 2018. "Banks credit ratings – is the size of the credit rating agency important?," Faculty of Management Working Paper Series 32018, University of Warsaw, Faculty of Management.
    5. Bego�a Guti�rrez Nieto & Carlos Serrano Cinca, 2006. "Factors explaining the rating of Microfinance Institutions," Documentos de Trabajo dt2006-03, Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza.

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