ARTIFICIAL NEURAL NETWORKS AND BANKRUPTCY FORECASTING : A STATE OF THE ART - HAL-SHS - Sciences de l'Homme et de la Société
Article Dans Une Revue Neural Computing and Applications Année : 2006

ARTIFICIAL NEURAL NETWORKS AND BANKRUPTCY FORECASTING : A STATE OF THE ART

Muriel Perez

Résumé

The use of neural networks in finance began by the end of the 1980s and by the beginning of the 1990s, it developed specific applications related to forecasting on the failure of companies. In order to highlight the evolution of this research stream, we have retained and analysed 30 studies in which the authors use neural networks to solve companies' classification problems (healthy and failing firms). This review of all these works gives us the opportunity to stress upon future trends in bankruptcy forecasting research

Dates et versions

halshs-00522129 , version 1 (29-09-2010)

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Citer

Muriel Perez. ARTIFICIAL NEURAL NETWORKS AND BANKRUPTCY FORECASTING : A STATE OF THE ART. Neural Computing and Applications, 2006, pp.154-163. ⟨10.1007/s00521-005-0022-x⟩. ⟨halshs-00522129⟩
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