Financial distress prediction is always important for financial institutions in order for them to assess the financial health of enterprises and individuals. Bankruptcy prediction and credit scoring are two important issues in financial distress prediction where various statistical and machine learning techniques have been employed to develop financial prediction models. Since there are no gene...

-Signs of a potential business bankruptcy are evident well before actual bankruptcy occurs. For managers, creditors, and all other concerned parties this lag allows time to take remedial action. Therefore, building models, which signal approaching financial failure, have been an important part of corporate finance literature, in order to help management refocus their energy, revaluate their cor...

bankruptcy is an event with strong impacts on management, shareholders, employees, creditors, customers and other stakeholders, so as bankruptcy challenges the country both socially and economically. therefore, correct prediction of bankruptcy is of high importance in the financial world. this research intends to investigate financial crisis prediction power using models based on neural network...

0950-7051/$ see front matter 2011 Elsevier B.V. A doi:10.1016/j.knosys.2011.06.008 ⇑ Corresponding author at: Key Laboratory of Knowledge Engineering of Ministry of Education, 130012, China. E-mail addresses: [email protected], liudayou19420 Bankruptcy prediction is one of the most important issues in financial decision-making. Constructing effective corporate bankruptcy prediction models in tim...

The problem of bankruptcy forecasting is one of the most actively studied nowadays, posing the task of building effective classifiers as well as the task of dealing with dataset imbalance. In this paper, we apply different combinations of modern learning algorithms (MDA, LR, CRT, and ANNs) in order to try to identify the most effective approach to bankruptcy prediction for Russian manufacturing...

Many static neural networks have been studied extensively in financial classification problems. However, dynamic time series predictive classification using neural networks with memory, such as the Gamma Memory neural network (GMNN), may prove more accurate. In this study we compare the predictive accuracy of the GMNN to the Multilayer Perceptron neural network and the statistical approaches of...

Bankruptcy prediction has been an important decision-making process for nancial analysts. One of the most common approaches for the bankruptcy prediction problem is the Discrim-inant Analysis. Also, the k-Nearest Neighbor classiier is very successful in such domains. This paper proposes a Feature Projection based classiication algorithm, and explores its applicability to the problem of predicti...

Due to the economic significance of bankruptcy prediction of companies for financial institutions, investors and governments, many quantitative methods have been used to develop effective prediction models. Support vector machines (SVM), a powerful classification method, has been used for this task, however, the performance of SVM is sensitive to model form, parameters setting and features sele...

this study predicts corporate bankruptcy five years before its occurrence using financial ratios introduced in altman’s z-score model and current ratio. three estimation methods namely; liner probability, logit and probit models have chosen for model estimation. the sample contains 134 companies in tehran stock exchange during 2003. the precision of prediction of the estimated models for the ma...

Business failures can cause financial damages to investors, creditors, or even society. For this reason bankruptcy prediction is one of the most challenging tasks in the field of financial decisionmaking. Business failure prediction has been an active research area since the 60s. The work of Beaver (1966) who performed univariate analysis of financial ratios and the work of Altman (1968) who em...