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Predicting issuer credit ratings using a semiparametric method

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  • Hwang, Ruey-Ching
  • Chung, Huimin
  • Chu, C.K.

Abstract

This paper proposes a prediction method based on an ordered semiparametric probit model for credit risk forecast. The proposed prediction model is constructed by replacing the linear regression function in the usual ordered probit model with a semiparametric function, thus it allows for more flexible choice of regression function. The unknown parameters in the proposed prediction model are estimated by maximizing a local (weighted) log-likelihood function, and the resulting estimators are analyzed through their asymptotic biases and variances. A real data example for predicting issuer credit ratings is used to illustrate the proposed prediction method. The empirical result confirms that the new model compares favorably with the usual ordered probit model.

Suggested Citation

  • Hwang, Ruey-Ching & Chung, Huimin & Chu, C.K., 2010. "Predicting issuer credit ratings using a semiparametric method," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 120-137, January.
    • Handle: RePEc:eee:empfin:v:17:y:2010:i:1:p:120-137
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    1. Ederington, Louis H, 1985. "Classification Models and Bond Ratings," The Financial Review, Eastern Finance Association, vol. 20(4), pages 237-262, November.
    2. repec:bla:jfinan:v:53:y:1998:i:4:p:1389-1413 is not listed on IDEAS
    3. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    4. Gentry, James A & Whitford, David T & Newbold, Paul, 1988. "Predicting Industrial Bond Ratings with a Probit Model and Funds Flow Components," The Financial Review, Eastern Finance Association, vol. 23(3), pages 269-286, August.
    5. Ruey-Ching Hwang & K. F. Cheng & Jack C. Lee, 2007. "A semiparametric method for predicting bankruptcy," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(5), pages 317-342.
    6. Marshall E. Blume & Felix Lim & A. Craig MacKinlay, "undated". "The Declining Credit Quality of US Corporate Debt: Myth or Reality?," Rodney L. White Center for Financial Research Working Papers 03-98, Wharton School Rodney L. White Center for Financial Research.
    7. West, Rr, 1970. "Alternative Approach To Predicting Corporate Bond Ratings," Journal of Accounting Research, Wiley Blackwell, vol. 8(1), pages 118-125.
    8. Sudheer Chava & Catalina Stefanescu & Stuart Turnbull, 2011. "Modeling the Loss Distribution," Management Science, INFORMS, vol. 57(7), pages 1267-1287, July.
    9. Sudheer Chava & Robert A. Jarrow, 2008. "Bankruptcy Prediction with Industry Effects," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 21, pages 517-549, World Scientific Publishing Co. Pte. Ltd..
    10. repec:fth:pennfi:67 is not listed on IDEAS
    11. Marshall E. Blume & Felix Lim & A. Craig MacKinlay, "undated". "The Declining Credit Quality of US Corporate Debt: Myth or Reality?," Rodney L. White Center for Financial Research Working Papers 3-98, Wharton School Rodney L. White Center for Financial Research.
    12. Feng, D. & Gourieroux, C. & Jasiak, J., 2008. "The ordered qualitative model for credit rating transitions," Journal of Empirical Finance, Elsevier, vol. 15(1), pages 111-130, January.
    13. Poon, Winnie P. H., 2003. "Are unsolicited credit ratings biased downward?," Journal of Banking & Finance, Elsevier, vol. 27(4), pages 593-614, April.
    14. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    15. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    16. Guttler, Andre & Wahrenburg, Mark, 2007. "The adjustment of credit ratings in advance of defaults," Journal of Banking & Finance, Elsevier, vol. 31(3), pages 751-767, March.
    17. 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.
    18. 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.
    19. 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.
    20. Kaplan, Robert S & Urwitz, Gabriel, 1979. "Statistical Models of Bond Ratings: A Methodological Inquiry," The Journal of Business, University of Chicago Press, vol. 52(2), pages 231-261, April.
    21. Shumway, Tyler, 2001. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model," The Journal of Business, University of Chicago Press, vol. 74(1), pages 101-124, January.
    22. Sreedhar T. Bharath & Tyler Shumway, 2008. "Forecasting Default with the Merton Distance to Default Model," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1339-1369, May.
    23. Horrigan, Jo, 1966. "Determination Of Long-Term Credit Standing With Financial Ratios," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 44-62.
    24. Stefanescu, Catalina & Tunaru, Radu & Turnbull, Stuart, 2009. "The credit rating process and estimation of transition probabilities: A Bayesian approach," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 216-234, March.
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    Cited by:

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    3. Mustafa Pamuk & Matthias Schumann, 2023. "Opening a New Era with Machine Learning in Financial Services? Forecasting Corporate Credit Ratings Based on Annual Financial Statements," IJFS, MDPI, vol. 11(3), pages 1-20, July.
    4. Cheng Few Lee, 2020. "Financial econometrics, mathematics, statistics, and financial technology: an overall view," Review of Quantitative Finance and Accounting, Springer, vol. 54(4), pages 1529-1578, May.
    5. Golbayani, Parisa & Florescu, Ionuţ & Chatterjee, Rupak, 2020. "A comparative study of forecasting corporate credit ratings using neural networks, support vector machines, and decision trees," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    6. Shi, Baofeng & Chi, Guotai & Li, Weiping, 2020. "Exploring the mismatch between credit ratings and loss-given-default: A credit risk approach," Economic Modelling, Elsevier, vol. 85(C), pages 420-428.
    7. Ruey-Ching Hwang & Huimin Chung & C. K. Chu, 2016. "A Two-Stage Probit Model for Predicting Recovery Rates," Journal of Financial Services Research, Springer;Western Finance Association, vol. 50(3), pages 311-339, December.
    8. Ruey-Ching Hwang & Chih-Kang Chu & Kaizhi Yu, 2021. "Predicting the Loss Given Default Distribution with the Zero-Inflated Censored Beta-Mixture Regression that Allows Probability Masses and Bimodality," Journal of Financial Services Research, Springer;Western Finance Association, vol. 59(3), pages 143-172, June.
    9. Nazário Augusto de Oliveira & Leonardo Fernando Cruz Basso, 2024. "The Impact of Value Creation (Tobin’s Q), Total Shareholder Return (TSR), and Survival (Altman’s Z) on Credit Ratings," IJFS, MDPI, vol. 12(2), pages 1-17, May.
    10. Balios, Dimitris & Thomadakis, Stavros & Tsipouri, Lena, 2016. "Credit rating model development: An ordered analysis based on accounting data," Research in International Business and Finance, Elsevier, vol. 38(C), pages 122-136.
    11. Ruey-Ching Hwang & Chih-Kang Chu, 2013. "Forecasting forward defaults: a simple hazard model with competing risks," Quantitative Finance, Taylor & Francis Journals, vol. 14(8), pages 1467-1477, August.
    12. Jaspreet Kaur & Madhu Vij & Ajay Kumar Chauhan, 2023. "Signals influencing corporate credit ratings—a systematic literature review," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 50(1), pages 91-114, March.
    13. Parisa Golbayani & Ionuc{t} Florescu & Rupak Chatterjee, 2020. "A comparative study of forecasting Corporate Credit Ratings using Neural Networks, Support Vector Machines, and Decision Trees," Papers 2007.06617, arXiv.org.
    14. Sermpinis, Georgios & Tsoukas, Serafeim & Zhang, Ping, 2018. "Modelling market implied ratings using LASSO variable selection techniques," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 19-35.
    15. Afef Feki Krichene & Walid Khoufi, 2016. "On the Nonlinearity of the Financial Ratios-Credit Ratings Relationship," Applied Finance and Accounting, Redfame publishing, vol. 2(2), pages 65-70, August.
    16. Lin, Yi-Chen & Hwang, Ruey-Ching & Deng, Wen-Shuenn, 2015. "Heterogeneity in the relationship between subjective well-being and its determinants over the life cycle: A varying-coefficient ordered probit approach," Economic Modelling, Elsevier, vol. 49(C), pages 372-386.
    17. Doumpos, Michael & Niklis, Dimitrios & Zopounidis, Constantin & Andriosopoulos, Kostas, 2015. "Combining accounting data and a structural model for predicting credit ratings: Empirical evidence from European listed firms," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 599-607.
    18. Hirk, Rainer & Vana, Laura & Hornik, Kurt, 2022. "A corporate credit rating model with autoregressive errors," Journal of Empirical Finance, Elsevier, vol. 69(C), pages 224-240.
    19. Doumpos, Michalis & Figueira, José Rui, 2019. "A multicriteria outranking approach for modeling corporate credit ratings: An application of the Electre Tri-nC method," Omega, Elsevier, vol. 82(C), pages 166-180.

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