Add to ORKGIn view of the failure of many high profile firms, bankruptcy prediction has become a topic of high interest. In this paper we have briefly reviewed the various techniques for the financial distress prediction. These techniques consist of statistical techniques like logit and probit models, multiple discriminant analysis, multivariate CUSUM methods etc. and artificial intelligence (AI) techniques like Artificial Neural Network techniques. We have used some of these techniques to over 1000 US companies which consisted of a mixture of surviving and failed firms. We have developed a hybrid model for predicting financial distress
A growing number of predicting corporate failure models has emerged since 60s. Economic and social c...
This paper provides empirical evidence on the prediction of non-financial companies’ failure. We dev...
AbstractIn this paper, we compare some traditional statistical methods for predicting financial dist...
As a prerequisite for an informed decision, a company’s financial results are undoubtedly one of the...
One of the most important topics discussed in the area of financial management is investors’ ability...
Financial distress is a condition where a company has difficulty paying off its financial obligation...
International audienceThe use of neural networks in finance began by the end of the 1980s and by the...
The ability to predict financial failure forms an essential topic in financial research. The various...
Financial distress prediction is a key challenge every financing provider faces when determining bor...
International audienceFinancial distress prediction is a central issue in empirical finance that has...
This paper looks at the ability of a relatively new technique, hybrid ANN’s, to predict corporate di...
Corporate bankruptcy and financial distress prediction is a topic of interest for a variety of stake...
In this study we will build a fully automatic workflow of machine learning technique quickly adaptab...
The main question which will be raised in this thesis is - whether we can predict future financial d...
A growing number of predicting corporate failure models has emerged since 60s. Economic and social c...
A growing number of predicting corporate failure models has emerged since 60s. Economic and social c...
This paper provides empirical evidence on the prediction of non-financial companies’ failure. We dev...
AbstractIn this paper, we compare some traditional statistical methods for predicting financial dist...
As a prerequisite for an informed decision, a company’s financial results are undoubtedly one of the...
One of the most important topics discussed in the area of financial management is investors’ ability...
Financial distress is a condition where a company has difficulty paying off its financial obligation...
International audienceThe use of neural networks in finance began by the end of the 1980s and by the...
The ability to predict financial failure forms an essential topic in financial research. The various...
Financial distress prediction is a key challenge every financing provider faces when determining bor...
International audienceFinancial distress prediction is a central issue in empirical finance that has...
This paper looks at the ability of a relatively new technique, hybrid ANN’s, to predict corporate di...
Corporate bankruptcy and financial distress prediction is a topic of interest for a variety of stake...
In this study we will build a fully automatic workflow of machine learning technique quickly adaptab...
The main question which will be raised in this thesis is - whether we can predict future financial d...
A growing number of predicting corporate failure models has emerged since 60s. Economic and social c...
A growing number of predicting corporate failure models has emerged since 60s. Economic and social c...
This paper provides empirical evidence on the prediction of non-financial companies’ failure. We dev...
AbstractIn this paper, we compare some traditional statistical methods for predicting financial dist...