0950-7051/$ see front matter 2011 Elsevier B.V. A doi:10.1016/j.knosys.2011.11.005 ⇑ Corresponding author. Address: Faculty of Econom Oviedo, Avda. Del Cristo s/n, 33006 Oviedo, Spain. Te E-mail address: [email protected] (J. de Andrés). In this paper we address the bankruptcy prediction problem and outline a procedure to improve the performance of standard classifiers. Our proposal replaces t...

Of the methods used to build bankruptcy prediction models in the last twenty years, neural networks are among the most challenging. Despite the characteristics of neural networks, most of the research done until now has not taken them into consideration for building financial failure models, nor for selecting the variables to be included in the models. The aim of our research is to establish th...

One of the most significant threats to the economy of a nation is the bankruptcy of its banks. This study evaluates the susceptibility of Nigerian banks to failure with a view to identifying ratios and financial data that are sensitive to solvency of the bank. Further, a predictive model is generated to guide all stakeholders in the industry. Thirty quoted banks that had published Annual Report...

This paper analyses the ability of some structural models to predict corporate bankruptcy. The study extends the existing empirical work on default risk in three ways. First, it estimates the expected default probabilities and computes default correlations using a copula function for a sample of bankrupt in the US. Second, it extracts common or latent factors that drive companies’ default corre...