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

Published online by Cambridge University Press:  23 January 2015

Paolo Giordani
Affiliation:, Research Division, Sveriges Riksbank, Stockholm, SE-103 37, Sweden
Tor Jacobson
Affiliation:, Research Division, Sveriges Riksbank, Stockholm, SE-103 37, Sweden
Erik von Schedvin
Affiliation:, Research Division, Sveriges Riksbank, Stockholm, SE-103 37, Sweden
Mattias Villani
Affiliation:, Division of Statistics, Linköping University, Linköping, 581 83, Sweden.


We demonstrate improvements in predictive power when introducing spline functions to take account of highly nonlinear relationships between firm failure and leverage, earnings, and liquidity in a logistic bankruptcy model. Our results show that modeling excessive nonlinearities yields substantially improved bankruptcy predictions, on the order of 70%–90%, compared with a standard logistic model. The spline model provides several important and surprising insights into nonmonotonic bankruptcy relationships. We find that low-leveraged as well as highly profitable firms are riskier than those given by a standard model, possibly a manifestation of credit rationing and excess cash-flow volatility.

Research Articles
Copyright © Michael G. Foster School of Business, University of Washington 2015 

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