The Default Risk of Firms Examined with Smooth Support Vector Machines
In the era of Basel II a powerful tool for bankruptcy prognosis is vital for banks. The tool must be precise but also easily adaptable to the bank's objections regarding the relation of false acceptances (Type I error) and false rejections (Type II error). We explore the suitabil- ity of Smooth Support Vector Machines (SSVM), and investigate how important factors such as selection of appropriate accounting ratios (predictors), length of training period and structure of the training sample in°uence the precision of prediction. Furthermore we show that oversampling can be employed to gear the tradeo® between error types. Finally, we illustrate graphically how di®erent variants of SSVM can be used jointly to support the decision task of loan o±cers.
|Date of creation:||Jan 2008|
|Contact details of provider:|| Postal: Spandauer Str. 1,10178 Berlin|
Web page: http://sfb649.wiwi.hu-berlin.de
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Shiyi Chen & Wolfgang Härdle & Rouslan Moro, 2006. "Estimation of Default Probabilities with Support Vector Machines," SFB 649 Discussion Papers SFB649DP2006-077, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Mella-Barral, Pierre & Perraudin, William, 1997.
" Strategic Debt Service,"
Journal of Finance,
American Finance Association, vol. 52(2), pages 531-556, June.
- Pierre Mella-Barral & William R M Perraudin, 1993. "Strategic Debt Service," CEPR Financial Markets Paper 0039, European Science Foundation Network in Financial Markets, c/o C.E.P.R, 77 Bastwick Street, London EC1V 3PZ..
- Altman, Edward I. & Marco, Giancarlo & Varetto, Franco, 1994. "Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience)," Journal of Banking & Finance, Elsevier, vol. 18(3), pages 505-529, May.
- 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.
- Merton, Robert C., 1973. "On the pricing of corporate debt: the risk structure of interest rates," Working papers 684-73., Massachusetts Institute of Technology (MIT), Sloan School of Management.
- Martin, Daniel, 1977. "Early warning of bank failure : A logit regression approach," Journal of Banking & Finance, Elsevier, vol. 1(3), pages 249-276, November.
- Leland, Hayne E & Toft, Klaus Bjerre, 1996. " Optimal Capital Structure, Endogenous Bankruptcy, and the Term Structure of Credit Spreads," Journal of Finance, American Finance Association, vol. 51(3), pages 987-1019, July.
- Hayne E. Leland and Klaus Bjerre Toft., 1995. "Optimal Capital Structure, Endogenous Bankruptcy, and the Term Structure of Credit Spreads," Research Program in Finance Working Papers RPF-259, University of California at Berkeley.
- repec:bla:joares:v:18:y:1980:i:1:p:109-131 is not listed on IDEAS
- Krahnen, Jan Pieter & Weber, Martin, 2001. "Generally accepted rating principles: A primer," Journal of Banking & Finance, Elsevier, vol. 25(1), pages 3-23, January.
- Krahnen, Jan Pieter & Weber, Martin, 2000. "Generally accepted rating principles: A primer," CFS Working Paper Series 2000/02, Center for Financial Studies (CFS).
- Härdle, Wolfgang Karl & Moro, Rouslan A. & Schäfer, Dorothea, 2007. "Estimating probabilities of default with support vector machines," Discussion Paper Series 2: Banking and Financial Studies 2007,18, Deutsche Bundesbank, Research Centre.
- Wolfgang Härdle & Rouslan Moro & Dorothea Schäfer, 2007. "Estimating Probabilities of Default With Support Vector Machines," SFB 649 Discussion Papers SFB649DP2007-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Huang, Chien-Ming & Lee, Yuh-Jye & Lin, Dennis K.J. & Huang, Su-Yun, 2007. "Model selection for support vector machines via uniform design," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 335-346, September. Full references (including those not matched with items on IDEAS)
When requesting a correction, please mention this item's handle: RePEc:hum:wpaper:sfb649dp2008-005. 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: (RDC-Team)
If references are entirely missing, you can add them using this form.