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Improving bankruptcy prediction in micro-entities by using nonlinear effects and non-financial variables

Opened Access Improving bankruptcy prediction in micro-entities by using nonlinear effects and non-financial variables
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Autor: Blanco Oliver, Antonio Jesús
Irimia Diéguez, Ana Isabel
Oliver Alfonso, María Dolores
Wilson, Nicholas
Departamento: Universidad de Sevilla. Departamento de Economía Financiera y Dirección de Operaciones
Fecha: 2015
Publicado en: Finance a úvěr: Czech Journal of Economics and Finance, 65 (2), 144-166.
Tipo de documento: Artículo
Resumen: The use of non-parametric methodologies, the introduction of non-financial variables, and the development of models geared towards the homogeneous characteristics of corporate sub-populations have recently experienced a surge of interest in the bankruptcy literature. However, no research on default prediction has yet focused on micro-entities (MEs), despite such firms’ importance in the global economy. This paper builds the first bankruptcy model especially designed for MEs by using a wide set of accounts from 1999 to 2008 and applying artificial neural networks (ANNs). Our findings show that ANNs outperform the traditional logistic regression (LR) models. In addition, we also report that, thanks to the introduction of non-financial predictors related to age, the delay in filing accounts, legal action by creditors to recover unpaid debts, and the ownership features of the company, the improvement with respect to the use of solely financial information is 3.6%, which is even...
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Cita: Blanco Oliver, A.J., Irimia Diéguez, A.I., Oliver Alfonso, M.D. y Wilson, N. (2015). Improving bankruptcy prediction in micro-entities by using nonlinear effects and non-financial variables. Finance a úvěr: Czech Journal of Economics and Finance, 65 (2), 144-166.
Tamaño: 389.2Kb
Formato: PDF

URI: https://hdl.handle.net/11441/80856

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