IDEAS home Printed from https://ideas.repec.org/a/eee/empfin/v17y2010i1p120-137.html
   My bibliography  Save this article

Predicting issuer credit ratings using a semiparametric method

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0927-5398(09)00058-9
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ederington, Louis H, 1985. "Classification Models and Bond Ratings," The Financial Review, Eastern Finance Association, vol. 20(4), pages 237-262, November.
    2. 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.
    3. 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.
    4. Sudheer Chava & Catalina Stefanescu & Stuart Turnbull, 2011. "Modeling the Loss Distribution," Management Science, INFORMS, vol. 57(7), pages 1267-1287, July.
    5. 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.
    6. Poon, Winnie P. H., 2003. "Are unsolicited credit ratings biased downward?," Journal of Banking & Finance, Elsevier, vol. 27(4), pages 593-614, April.
    7. 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.
    8. 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..
    9. repec:bla:jfinan:v:53:y:1998:i:4:p:1389-1413 is not listed on IDEAS
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    15. 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.
    16. repec:fth:pennfi:67 is not listed on IDEAS
    17. 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.
    18. 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.
    19. Horrigan, Jo, 1966. "Determination Of Long-Term Credit Standing With Financial Ratios," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 44-62.
    20. 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.
    21. 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.
    22. 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.
    23. West, Rr, 1970. "Alternative Approach To Predicting Corporate Bond Ratings," Journal of Accounting Research, Wiley Blackwell, vol. 8(1), pages 118-125.
    24. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ruey-Ching Hwang, 2013. "Forecasting credit ratings with the varying-coefficient model," Quantitative Finance, Taylor & Francis Journals, vol. 13(12), pages 1947-1965, December.
    2. 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.
    3. Arundina, Tika & Azmi Omar, Mohd. & Kartiwi, Mira, 2015. "The predictive accuracy of Sukuk ratings; Multinomial Logistic and Neural Network inferences," Pacific-Basin Finance Journal, Elsevier, vol. 34(C), pages 273-292.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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).
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ruey-Ching Hwang, 2013. "Forecasting credit ratings with the varying-coefficient model," Quantitative Finance, Taylor & Francis Journals, vol. 13(12), pages 1947-1965, December.
    2. Ruey‐Ching Hwang & K. F. Cheng & Cheng‐Few Lee, 2009. "On multiple‐class prediction of issuer credit ratings," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(5), pages 535-550, September.
    3. 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.
    4. Shen, Chung-Hua & Huang, Yu-Li & Hasan, Iftekhar, 2012. "Asymmetric benchmarking in bank credit rating," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(1), pages 171-193.
    5. Hwang, Ruey-Ching, 2012. "A varying-coefficient default model," International Journal of Forecasting, Elsevier, vol. 28(3), pages 675-688.
    6. Jens Hilscher & Mungo Wilson, 2017. "Credit Ratings and Credit Risk: Is One Measure Enough?," Management Science, INFORMS, vol. 63(10), pages 3414-3437, October.
    7. 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.
    8. Koresh Galil, 2005. "Ratings as Predictors of Default in the Long Term:an Empirical Investigation," Working Papers 0505, Ben-Gurion University of the Negev, Department of Economics.
    9. Manzoni, Katiuscia, 2004. "Modeling Eurobond credit ratings and forecasting downgrade probability," International Review of Financial Analysis, Elsevier, vol. 13(3), pages 277-300.
    10. Nidhi Aggarwal & Manish K. Singh & Susan Thomas, 2022. "Informational efficiency of credit ratings," Working Papers 14, xKDR.
    11. Marta Gómez-Puig & Simón Sosvilla-Rivero & Manish K. Singh, 2018. "“Incorporating creditors' seniority into contingent claim models:Application to peripheral euro area countries”," IREA Working Papers 201803, University of Barcelona, Research Institute of Applied Economics, revised Feb 2018.
    12. Van Laere, Elisabeth & Baesens, Bart, 2010. "The development of a simple and intuitive rating system under Solvency II," Insurance: Mathematics and Economics, Elsevier, vol. 46(3), pages 500-510, June.
    13. Ken Hung & Hui Wen Cheng & Shih-shen Chen & Ying-Chen Huang, 2013. "Factors that Affect Credit Rating: An Application of Ordered Probit Models," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 94-108, December.
    14. Singh, Manish K. & Gómez-Puig, Marta & Sosvilla-Rivero, Simón, 2015. "Bank risk behavior and connectedness in EMU countries," Journal of International Money and Finance, Elsevier, vol. 57(C), pages 161-184.
    15. Jens Hilscher & Mungo Wilson, 2011. "Credit ratings and credit risk," Working Papers 31, Brandeis University, Department of Economics and International Business School.
    16. Azmat, Saad & Skully, Michael & Brown, Kym, 2017. "The (little) difference that makes all the difference between Islamic and conventional bonds," Pacific-Basin Finance Journal, Elsevier, vol. 42(C), pages 46-59.
    17. Emilia Bonaccorsi di Patti & Alessio D’Ignazio & Marco Gallo & Giacinto Micucci, 2015. "The Role of Leverage in Firm Solvency: Evidence From Bank Loans," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 1(2), pages 253-286, July.
    18. Mizen, Paul & Tsoukas, Serafeim, 2012. "Forecasting US bond default ratings allowing for previous and initial state dependence in an ordered probit model," International Journal of Forecasting, Elsevier, vol. 28(1), pages 273-287.
    19. 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.
    20. Chen, Jie & Hill, Paula, 2013. "The impact of diverse measures of default risk on UK stock returns," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5118-5131.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:empfin:v:17:y:2010:i:1:p:120-137. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jempfin .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.