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Modelos de alerta temprana para pronosticar crisis bancarias: desde la extracción de señales a las redes neuronales

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Author Info
Christian A. Johnson () (Universidad Adolfo Ibañez)

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Abstract

This paper reviews alternative methodologies and models to design sys-tems to help in the early detection of banking distress (EWS). The pro-posed methodologies are aimed to the early identification of financial distress for countries without an important recent history of banking failure. This paper presents traditional models often used to predict currency crisis, and more advanced approaches, such as non linear neural networks models.

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Publisher Info
Article provided by Ilades-Georgetown University, Economics Department in its journal Revista de Analisis Economico.

Volume (Year): 20 (2005)
Issue (Month): 1 (June)
Pages: 95-121
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Handle: RePEc:ila:anaeco:v:20:y:2005:i:1:p:95-121

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Related research
Keywords: E44; G21; C23; C25; C45;

Find related papers by JEL classification:
E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Mortgages
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data
C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models
C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics

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