Abstract
Differential evolution was used for the automatic selection of financial ratios for the prediction of business insolvency. A sample of companies from the Galician economy is used to predict the insolvency of a company a year in advance. The genetic population encodes possible sets or combinations of financial ratios, and the quality of each encoded solution is determined by the classification accuracy provided by a KNN classifier that uses the selected encoded ratios. Finally, the selected and relevant ratios are used with a more robust classifier, a classical multilayer perceptron, which provides greater sensitivity in the prediction results.
This study was funded by the Xunta de Galicia and the European Union, with grants CITIC (ED431G 2019/01), GPC ED431B 2019/03, and by the Spanish Ministry of Science and Innovation (project PID2020-116201GB-I00).
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Santos, J., Sestayo, Ó., Beade, Á., Rodríguez, M. (2022). Automatic Selection of Financial Ratios by Means of Differential Evolution and for Predicting Business Insolvency. In: Ferrández Vicente, J.M., Álvarez-Sánchez, J.R., de la Paz López, F., Adeli, H. (eds) Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence. IWINAC 2022. Lecture Notes in Computer Science, vol 13259. Springer, Cham. https://doi.org/10.1007/978-3-031-06527-9_53
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