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Prediction of Corporate Credit Ratings with Machine Learning: Simple Interpretative Models

Author

Listed:
  • Koresh Galil

    (BGU)

  • Ami Hauptman

    (Computer Science Department of Sapir College)

  • Rosit Levy Rosenboim

    (Applied Economics Department of Sapir College)

Abstract

No abstract is available for this item.

Suggested Citation

  • Koresh Galil & Ami Hauptman & Rosit Levy Rosenboim, 2023. "Prediction of Corporate Credit Ratings with Machine Learning: Simple Interpretative Models," Working Papers 2308, Ben-Gurion University of the Negev, Department of Economics.
    • Handle: RePEc:bgu:wpaper:2308
    as

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    File URL: http://in.bgu.ac.il/en/humsos/Econ/Workingpapers/2308.pdf
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    References listed on IDEAS

    as
    1. 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.
    2. repec:bla:jfinan:v:53:y:1998:i:4:p:1389-1413 is not listed on IDEAS
    3. Jens Hilscher & Mungo Wilson, 2017. "Credit Ratings and Credit Risk: Is One Measure Enough?," Management Science, INFORMS, vol. 63(10), pages 3414-3437, October.
    4. 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.
    5. Engin Tas & Ayca Hatice Atli, 2022. "A comparison of SVR and NARX in financial time series forecasting," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 12(3), pages 303-320.
    6. repec:fth:pennfi:67 is not listed on IDEAS
    7. 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.
    8. Ramin P. Baghai & Henri Servaes & Ane Tamayo, 2014. "Have Rating Agencies Become More Conservative? Implications for Capital Structure and Debt Pricing," Journal of Finance, American Finance Association, vol. 69(5), pages 1961-2005, October.
    9. 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.
    10. 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).
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Corporate Ratings; Machine Learning; Classification and Regression Tree; Support Vector Regression; CART; SVR; Size;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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