Over the last four decades, bankruptcy prediction has given rise to an extensive body of literature, the aim of which …

Of the methods used to build bankruptcy prediction models in the last twenty years, neural networks are among the most …

During the last three decades various models have been proposed by the literature to predict the risk of bankruptcy and …

In this paper, we estimate coefficients of bankruptcy forecasting models, such as logistic and neural network models …, in terms of discriminatory power, information content and economic impact while we forecast bankruptcy one year ahead …, two years ahead but also financial distress, which is a situation that precedes firm bankruptcy. Using US public firms …

-parametric models for bankruptcy prediction. More specifically, we compute the unobservable parameters such as, asset value and asset …, Campbell et al. (2008). There, financial and market data are the inputs, and the output is the probability of bankruptcy … bankruptcy …

variables consistently predict bankruptcy for firms of different dimensions, over different periods and in different industries …

Bankruptcy is a menacing situation, which the investors, businesses, and the economy are afraid of, due to its adverse … effects. Prediction of bankruptcy can help the investors and businesses in formulating their strategies in order to improve … network in our brain. So this study focuses on using the different variables of ROA, ROE to predict the bankruptcy of …

Quite a few in-depth articles were found in the above-mentioned domain. Bankruptcy is one of the most critical factors … which most of companies don't want to face. To predict the Bankruptcy of Banks, there have been several attempts made, some … Artificial Neural Network model, can be used to predict bankruptcy. Looking at the current scenario of the public sector banks …