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

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Author Info

  • 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.

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Bibliographic Info

Paper provided by Sveriges Riksbank (Central Bank of Sweden) in its series Working Paper Series with number 256.

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Length: 51 pages
Date of creation: 01 Nov 2011
Date of revision:
Handle: RePEc:hhs:rbnkwp:0256

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Postal: Sveriges Riksbank, SE-103 37 Stockholm, Sweden
Phone: 08 - 787 00 00
Fax: 08-21 05 31
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Web page: http://www.riksbank.com/
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Keywords: bankruptcy risk model; micro-data; logistic spline regression; …nancial ratios;

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References

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  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, 08.
  2. Shumway, Tyler, 2001. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model," The Journal of Business, University of Chicago Press, vol. 74(1), pages 101-24, January.
  3. 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, 09.
  4. McFadden, Daniel, 1974. "The measurement of urban travel demand," Journal of Public Economics, Elsevier, vol. 3(4), pages 303-328, November.
  5. Darrel Duffie & Leandro Saita & Ke Wang, 2005. "Multi-Period Corporate Default Prediction With Stochastic Covariates," CARF F-Series CARF-F-047, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
  6. 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, 08.
  7. 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.
  8. 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 449-70, May.
  9. Smith, M. & Kohn, R., . "Nonparametric Regression using Bayesian Variable Selection," Statistics Working Paper _009, Australian Graduate School of Management.
  10. Tim Opler & Lee Pinkowitz & Rene Stulz & Rohan Williamson, 1997. "The Determinants and Implications of Corporate Cash Holdings," NBER Working Papers 6234, National Bureau of Economic Research, Inc.
  11. 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.
  12. 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.
  13. Altman, Edward I, 1971. "Railroad Bankruptcy Propensity," Journal of Finance, American Finance Association, vol. 26(2), pages 333-45, May.
  14. 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.
  15. 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.
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Cited by:
  1. 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).
  2. Villani, Mattias & Kohn, Robert & Nott, David J., 2012. "Generalized smooth finite mixtures," Journal of Econometrics, Elsevier, vol. 171(2), pages 121-133.

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