Fiche du document
2012
- handle: 10670/1.hpj0ng
- 1886-516X
Ce document est lié à :
http://www.redalyc.org/revista.oa
Revista de Métodos Cuantitativos para la Economía y la Empresa
Mots-clés
Economía y Finanzas neural networks Level of default financial institutions Extreme Learning MachineSujets proches
Learning process Scholarship LearningCiter ce document
Teresa Montero-Romero et al., « Extreme Learning Machine to Analyze the Level of Default in Spanish Deposit Institutions », Revista de Métodos Cuantitativos para la Economía y la Empresa, ID : 10670/1.hpj0ng
Métriques
Partage / Export
Résumé
"The level of default in financial institutions is a key piece of information in the activity of these organizations and reveals their level of risk. This in turn explains the growing attention given to variables of this kind, during the crisis of these last years. This paper presents a method to estimate the default rate using the non-linear model defined by standard Multilayer Perceptron (MLP) neural networks trained with a novel methodology called Extreme Learning Machine (ELM). The experimental results are promising, and show a good performance when comparing the MLP model trained with the Leverberg-Marquard algorithm."