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

Paolo Giordani (), Tor Jacobson (), Erik von Schedvin () and Mattias Villani
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Tor Jacobson: Research Department, Central Bank of Sweden, Postal: Sveriges Riksbank, SE-103 37 Stockholm, Sweden

No 256, Working Paper Series from Sveriges Riksbank (Central Bank of Sweden)

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.

Keywords: bankruptcy risk model; micro-data; logistic spline regression; …nancial ratios (search for similar items in EconPapers)
JEL-codes: C41 G21 G33 G38 (search for similar items in EconPapers)
Pages: 51 pages
Date: 2011-11-01
New Economics Papers: this item is included in nep-bec
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

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Journal Article: Taking the Twists into Account: Predicting Firm Bankruptcy Risk with Splines of Financial Ratios (2014)
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