A decision tree approach for predicting insolvency of SMEs: an empirical research in Spain
This paper addresses the problem of insolvency prediction in Spanish SMEs from a binary classification perspective. From a dataset containing more than 325 dependent variables of different natures (including demographic and economic-financial) and 17562 SMEs, a decision tree has been fitted that wit...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universidad de La Laguna (ULL) |
| Repositorio: | RIULL. Repositorio Institucional de la Universidad de La Laguna |
| OAI Identifier: | oai:riull.ull.es:915/41286 |
| Acceso en línea: | http://riull.ull.es/xmlui/handle/915/41286 |
| Access Level: | acceso abierto |
| Palabra clave: | Insolvency decision tree SME binary classification Pareto optimality model selection bankruptcy |
| Sumario: | This paper addresses the problem of insolvency prediction in Spanish SMEs from a binary classification perspective. From a dataset containing more than 325 dependent variables of different natures (including demographic and economic-financial) and 17562 SMEs, a decision tree has been fitted that with a 0.93 accuracy predicts the state of a company and allows it to identify the most relevant variables in such prediction. The results obtained indicate that, in general, insolvency can be predicted from very few financial variables and with an anticipation of more than 10 years before the insolvency event. As a result, it is possible to provide early warnings to SMEs based on the indicators identified. |
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