Multi-criteria decision analysis (MCDA) is a valuable resource within operations research
and management science. Various MCDA methods have been developed over the years …

For financial institutions, the ability to predict or forecast business failures is crucial, as
incorrect decisions can have direct financial consequences. Bankruptcy prediction and …

This study introduces deep learning models for corporate bankruptcy forecasting using
textual disclosures. Although textual data are common, it is rarely considered in the financial …

This study investigates stock market indices prediction that is an interesting and important
research in the areas of investment and applications, as it can get more profits and returns at …

Nowadays, many current real financial applications have nonlinear and uncertain behaviors
which change across the time. Therefore, the need to solve highly nonlinear, time variant …

We set out in this study to review a vast amount of recent literature on machine learning (ML)
approaches to predicting financial distress (FD), including supervised, unsupervised and …

Ratio type financial indicators are the most popular explanatory variables in bankruptcy
prediction models. These measures often exhibit heavily skewed distribution because of the …

Bibliometric analysis is an effective method to carry out quantitative study of academic output
to address the research trends on a given area of investigation through analysing existing …

Credit classification is an important component of critical financial decision making tasks
such as credit scoring and bankruptcy prediction. Credit classification methods are usually …

The objectives of this paper are firstly, to provide an optimal hotel bankruptcy prediction
approach to minimize the empirical risk of misclassification and secondly, to investigate the …