Bankruptcy prediction models based on multinorm analysis: An alternative to accounting ratios

Abstract

0950-7051/$ see front matter 2011 Elsevier B.V. A doi:10.1016/j.knosys.2011.11.005 ⇑ Corresponding author. Address: Faculty of Econom Oviedo, Avda. Del Cristo s/n, 33006 Oviedo, Spain. Te E-mail address: jdandres@uniovi.es (J. de Andrés). In this paper we address the bankruptcy prediction problem and outline a procedure to improve the performance of standard classifiers. Our proposal replaces traditional indicators (accounting ratios) with the output of a so-called multinorm analysis. The deviations of each firm from a battery of industry norms (computed by nonparametric quantile regression) are used as input variables for the classifiers. The approach is applied to predict bankruptcy of firms, and tested on a representative data set of Spanish firms. Results indicate that the approach may provide significant improvements in predictive accuracy, both in linear and nonlinear classifiers. 2011 Elsevier B.V. All rights reserved.

DOI: 10.1016/j.knosys.2011.11.005
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@article{Andrs2012BankruptcyPM, title={Bankruptcy prediction models based on multinorm analysis: An alternative to accounting ratios}, author={Javier de Andr{\'e}s and Manuel Landajo and Pedro Lorca}, journal={Knowl.-Based Syst.}, year={2012}, volume={30}, pages={67-77} }