IDEAS home Printed from https://ideas.repec.org/p/hhs/rbnkwp/0256.html
   My bibliography  Save this paper

Taking the Twists into Account: Predicting Firm Bankruptcy Risk with Splines of Financial Ratios

Author

Listed:
  • Giordani, Paolo

    () (Research Department, Central Bank of Sweden)

  • Jacobson, Tor

    () (Research Department, Central Bank of Sweden)

  • von Schedvin , Erik

    () (CentER - Tilburg University, EBC, and Sveriges Riksbank)

  • Villani, Mattias

    () (Division of Statistics, Department of Computer and Information Science, Linköping University)

Abstract

We demonstrate improvements in predictive power when introducing spline functions to take account of highly non-linear relationships between firm failure and earnings, leverage, and liquidity in a logistic bankruptcy model. Our results show that modeling excessive non-linearities yields substantially improved bankruptcy predictions, on the order of 70 to 90 percent, compared with a standard logistic model. The spline model provides several important and surprising insights into non-monotonic bankruptcy relationships. We find that low-leveraged and highly profitable firms are riskier than given by a standard model. These features are remarkably stable over time, suggesting that they are of a structural nature.

Suggested Citation

  • Giordani, Paolo & Jacobson, Tor & von Schedvin , Erik & Villani, Mattias, 2011. "Taking the Twists into Account: Predicting Firm Bankruptcy Risk with Splines of Financial Ratios," Working Paper Series 256, Sveriges Riksbank (Central Bank of Sweden).
  • Handle: RePEc:hhs:rbnkwp:0256
    as

    Download full text from publisher

    File URL: http://www.riksbank.com/upload/Dokument_riksbank/Kat_publicerat/WorkingPapers/2011/wp256.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Tor Jacobson & Jesper Lindé & Kasper Roszbach, 2013. "Firm Default And Aggregate Fluctuations," Journal of the European Economic Association, European Economic Association, vol. 11(4), pages 945-972, August.
    2. Duffie, Darrell & Saita, Leandro & Wang, Ke, 2007. "Multi-period corporate default prediction with stochastic covariates," Journal of Financial Economics, Elsevier, vol. 83(3), pages 635-665, March.
    3. Altman, Edward I, 1971. "Railroad Bankruptcy Propensity," Journal of Finance, American Finance Association, vol. 26(2), pages 333-345, May.
    4. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    5. Rada Dakovic & Claudia Czado & Daniel Berg, 2010. "Bankruptcy prediction in Norway: a comparison study," Applied Economics Letters, Taylor & Francis Journals, vol. 17(17), pages 1739-1746.
    6. Lang, Larry & Poulsen, Annette & Stulz, Rene, 1995. "Asset sales, firm performance, and the agency costs of managerial discretion," Journal of Financial Economics, Elsevier, vol. 37(1), pages 3-37, January.
    7. Altman, Edward I., 1984. "The success of business failure prediction models : An international survey," Journal of Banking & Finance, Elsevier, vol. 8(2), pages 171-198, June.
    8. Smith, Michael & Kohn, Robert, 1996. "Nonparametric regression using Bayesian variable selection," Journal of Econometrics, Elsevier, vol. 75(2), pages 317-343, December.
    9. Opler, Tim & Pinkowitz, Lee & Stulz, Rene & Williamson, Rohan, 1999. "The determinants and implications of corporate cash holdings," Journal of Financial Economics, Elsevier, vol. 52(1), pages 3-46, April.
    10. Heitor Almeida & Murillo Campello & Michael S. Weisbach, 2004. "The Cash Flow Sensitivity of Cash," Journal of Finance, American Finance Association, vol. 59(4), pages 1777-1804, August.
    11. repec:bla:joares:v:4:y:1966:i::p:71-111 is not listed on IDEAS
    12. Jacobson, Tor & Linde, Jesper & Roszbach, Kasper, 2005. "Exploring interactions between real activity and the financial stance," Journal of Financial Stability, Elsevier, vol. 1(3), pages 308-341, April.
    13. 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.
    14. 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.
    15. repec:bla:joares:v:18:y:1980:i:1:p:109-131 is not listed on IDEAS
    16. Sreedhar T. Bharath & Tyler Shumway, 2008. "Forecasting Default with the Merton Distance to Default Model," Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1339-1369, May.
    17. McFadden, Daniel, 1974. "The measurement of urban travel demand," Journal of Public Economics, Elsevier, vol. 3(4), pages 303-328, November.
    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. Villani, Mattias & Kohn, Robert & Nott, David J., 2012. "Generalized smooth finite mixtures," Journal of Econometrics, Elsevier, vol. 171(2), pages 121-133.
    2. Koresh Galil & Neta Gilat, 2018. "Predicting Default More Accurately: To Proxy Or Not To Proxy For Default," Working Papers 1801, Ben-Gurion University of the Negev, Department of Economics.
    3. Quiroz, Matias & Villani, Mattias & Kohn, Robert, 2015. "Speeding Up Mcmc By Efficient Data Subsampling," Working Paper Series 297, Sveriges Riksbank (Central Bank of Sweden).
    4. Kohn, Robert & Quiroz, Matias & Tran, Minh-Ngoc & Villani, Mattias, 2016. "Speeding up MCMC by Efficient Data Subsampling," Working Papers 2123/16205, University of Sydney Business School, Discipline of Business Analytics.
    5. Quiroz, Matias & Villani, Mattias, 2013. "Dynamic mixture-of-experts models for longitudinal and discrete-time survival data," Working Paper Series 268, Sveriges Riksbank (Central Bank of Sweden).
    6. Péter Bauer & Marianna Endrész, 2016. "Modelling Bankruptcy Using Hungarian Firm-Level Data," MNB Occasional Papers 2016/122, Magyar Nemzeti Bank (Central Bank of Hungary).
    7. Amberg, Niklas & Jacobson, Tor & von Schedvin, Erik & Townsend, Robert, 2016. "Curbing Shocks to Corporate Liquidity: The Role of Trade Credit," Working Paper Series 320, Sveriges Riksbank (Central Bank of Sweden).
    8. Feng Li & Mattias Villani, 2013. "Efficient Bayesian Multivariate Surface Regression," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(4), pages 706-723, December.

    More about this item

    Keywords

    bankruptcy risk model; micro-data; logistic spline regression; …nancial ratios;

    JEL classification:

    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • G38 - Financial Economics - - Corporate Finance and Governance - - - Government Policy and Regulation

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:hhs:rbnkwp:0256. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Lena Löfgren). General contact details of provider: http://edirc.repec.org/data/rbgovse.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.