Logo PUC-Rio Logo Maxwell
ETDs @PUC-Rio
Título: A NEURAL MODEL FOR PREDICTION OF BANKRUPTCY IN THE FINANCIAL SYSTEM
Autor: GUSTAVO ADOLFO SORENSEN CABRERA
Colaborador(es): CARLOS EDUARDO PEDREIRA - Orientador
Catalogação: 17/NOV/2005 Língua(s): PORTUGUESE - BRAZIL
Tipo: TEXT Subtipo: THESIS
Notas: [pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio.
[en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio.
Referência(s): [pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=7493&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=7493&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.7493
Resumo:
This dissertation investigates the use of Neural Networks, especially the model known as Self-Organizing Feature Maps (S.O.F.M.), as regards the prediction of bankruptcy in the financial system. Quarterly financial ratios of 32 Banks and 53 Financial Institutions in Paraguay within the period December 96 - December 97 were utilized for the development of this work. The qualification system, Known as CAULA (Capital, Assets, Utilities, Liquidity and Management), used by the Superintendence of Banks of the Central Bank of Paraguay, was chosen as a comparative model with respect to the Neural Network model.
Descrição: Arquivo:   
COVER, ACKNOWLEDGEMENTS, RESUMO, ABSTRACT AND SUMMARY PDF      
CHAPTER 1 AND CHAPTER 2 PDF      
CHAPTER 3 PDF      
CHAPTER 4 PDF      
PDF