This study attempts to show how a Kohonen map can be used to improve the temporal stability of the accuracy of a financial failure model. Most models lose a significant part of their ability to generalize when data used for estimation and prediction purposes are collected over different time...

The aim of this study is to show how a Kohonen map can be used to increase the forecasting horizon of a financial failure model. Indeed, most prediction models fail to forecast accurately the occurrence of failure beyond one year, and their accuracy tends to fall as the prediction horizon...

We evaluate the prediction accuracy of models designed using different classification methods depending on the technique used to select variables, and we study the relationship between the structure of the models and their ability to correctly predict financial failure. We show that a neural...

This study examines a method of analyzing the dynamics of financial failure. Using a large amount of data and a Kohonen map, we show how to depict company trajectories of behavior and movement to terminal failure We also show how to analyze these trajectories to describe and understand the...

This paper is a critical review of the variable selection methods used to build empirical bankruptcy prediction models. Recent decades have seen many papers on modeling techniques, but very few about the variable selection methods that should be used jointly or about their fit. This issue is of...

The aim of this article is to analyze the various aspects of dividend policy. Emphasizing tax issues, theoretical frameworks of informational asymmetry of corporate governance and life cycles, we show that a static vision of dividends has been gradually replaced by a dynamic vision....

Over the last four decades, bankruptcy prediction has given rise to an extensive body of literature, the aim of which was to assess the conditions under which forecasting models perform effectively. Of all the parameters that may influence model accuracy, one has rarely been discussed: the...

Of the methods used to build bankruptcy prediction models in the last twenty years, neural networks are among the most challenging. Despite the characteristics of neural networks, most of the research done until now has not taken them into consideration for building financial failure models, nor...