¿Bancos con Problemas? Un Sistema de Alerta Temprana para la Prevención de Crisis Bancarias

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Publicado 18-09-2018
Ana Fernández Sainz Felipe Llaugel

Resumen

Las autoridades reguladoras y supervisoras de los sistemas financieros han probado diversos métodos para intentar encontrar un procedimiento eficaz en la elaboración de un sistema de alerta temprana de las crisis bancarias. Los Modelos de Regresión Logística han sido usados aunque han mostrado algunas debilidades, por lo que se necesitan nuevos y mejores métodos. La crisis bancaria ocurrida en la República Dominicana entre los años 2002 y 2004 se ha usado para comparar la eficacia de la Regresión Logística frente al uso del método Support Vector Machines (SVM) para la detección de crisis bancarias. En el análisis se usan 30 indicadores financieros para determinar cuáles de ellos son los más apropiados en la construcción de un modelo capaz de distinguir un banco en problemas de uno solvente. En este contexto, el método de SVM generó mejores resultados que la Regresión Logística en la detección de los bancos con problemas y se contradicen las afirmaciones de otros estudios que plantean la poca efectividad de los indicadores financieros para detectar crisis bancarias en economías emergentes.

Cómo citar

Fernández Sainz, A., & Llaugel, F. (2018). ¿Bancos con Problemas? Un Sistema de Alerta Temprana para la Prevención de Crisis Bancarias. Cuadernos De Gestión, 11(2), 149–168. https://doi.org/10.5295/cdg.100239af
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Keywords

crisis bancarias, regresión logística, support vector machines

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