Endogenous Prediction of Bankruptcy using a Support Vector Machine

Jorge Zazueta, Andrea Chavez Heredia and Jorge Zazueta-Hernández

No ehpt7, SocArXiv from Center for Open Science

Abstract: We build a global bankruptcy prediction model using a support vector machine trained only on firms' endogenous information in the form of financial ratios. The model is tested not only on entirely random unseen data but on samples taken from specific global regions and industries to test for prediction bias, achieving satisfactory prediction performance in all cases. While support vector machines are not easily interpretable, we explore variable importance and find it consistent with economic intuition.

Date: 2021-05-06
New Economics Papers: this item is included in nep-big and nep-cmp
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:ehpt7

DOI: 10.31219/osf.io/ehpt7

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