In the last three decades forecasting bankruptcy of enterprises has been an important and difficult problem, used as an impulse for many research projects (Ribeiro et al. 2012). At present many methods of bankruptcy prediction are available. In view of the specific character of economic activity in individual sectors, specialised methods adapted to a given branch of industry are being used incr...

The prediction of bankruptcy is of significant importance with the present-day increase of bankrupt companies. In the practical applications, the cost of misclassification is worthy of consideration in the modeling in order to make accurate and desirable decisions. An effective prediction system requires the integration of the cost preference into the construction and optimization of prediction...

Keywords: Definition of financial distress Sampling methods Featuring methods Review Financial distress prediction Corporate failure prediction Case-based reasoning Ensemble Group decision-making Support vector machine Hybrid modeling Neural network Decision tree Logistic regression Multiple discriminant analysis a b s t r a c t As a hot topic, financial distress prediction (FDP), or called as ...

Bankruptcy prediction has been a topic of active research for business and corporate organizations since past decades. It is an effective tool to help financial institutions and relevant people to make the right decision in investments, especially in the current competitive environment. The tool provides auditors and managers a chance to identify the problems early.

Ability to predict corporate bankruptcy as one of the areas of risk management has various social and individual aspects. Timely warning of bankruptcy risk makes managers and investors able to do preventative measures. These measures consist of changing operational policy, financial restructuring and even optional treatment which by reducing potential losses, improve social and individual resou...

Predicting the failure of a company is a difficult problem traditionally performed by accounting experts using heuristic rules extracted from experience. In this work we apply HLVQ, a new algorithm to train neural networks, to this problem and compared its results with G-Prop, a neural network optimized with evolutionary algorithms. We show that HLVQ is an efficient alternative for the bankrupt...

Using financial ratio data from 2006 and 2007, this study uses a three-fold cross validation scheme to compare the classification and prediction of bankrupt firms by robust logistic regression with the Bianco and Yohai (BY) estimator versus maximum likelihood (ML) logistic regression. With both the 2006 and 2007 data, BY robust logistic regression improves both the classification of bankrupt fi...

This research starts from the work by Madonna and Cestari (2015) that aimed at assessing the usability of three bankruptcy prediction models applied in contexts other than the ones of their elaboration, in order to evaluate their generalizability and the possibility to apply them in wide-scale investigations. We took the cue from that study to assess the usability of four bankruptcy prediction ...