Prediction of firms’ financial distress using adaboost algorithm and comparing its accuracy to artificial neural networks.

• Autores: Mahmoud Hemmatfar, Seyed Alimorad Hosseinipak
• Localización: QUID: Investigación, Ciencia y Tecnología, ISSN-e 2462-9006, ISSN 1692-343X, Nº. Extra 1, 2017, págs. 2151-2158
• Idioma: inglés
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• Resumen

  • One of the most important topics discussed in the area of financial management is investors’ ability to tell favourable investment opportunities from unfavourable ones. One way to help investors is to present firm’s financial distress prediction models. So far, different techniques have been used to design firm’s financial distress prediction models. Recent studies in the field of financial distress prediction have focused on creation and application of artificial intelligence and machine learning methods, AdaBoost algorithm and artificial neural networks are used in the present study as a comparative model to Companies’ financial distress prediction. 660 samples were selected from 112 financially distressed companies and 548 non-financially distressed over a 6-year period from 2007 to 2012 have been selected.Research Findings suggest that in Companies’ financial distress prediction, the model based on AdaBoost algorithm has a higher overall accuracy than the model based on artificial neural network.