Taking the Twists into Account: Predicting Firm Bankruptcy Risk with Splines of Financial Ratios
Paolo Giordani (),
Tor Jacobson (),
Erik von Schedvin () and
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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)
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
New Economics Papers: this item is included in nep-bec
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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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