Um modelo de previsão de solvência utilizando regressão logística

João Alberto Minussi, Cláudio Damacena and Walter Lee Ness

RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration), 2002, vol. 6, issue 3, 109-128

Abstract: The process of entry of foreign banks in the Brazilian financial system, together with the achievement of monetary stability, are requiring changes in the profile of action of Brazilian banks, especially in the area of credit. In this sense, this article represents an important contribution in testing a new technique (logistic regression) in evaluating credit risk. The statistical technique used shows itself more robust than other methods that have been used in previous studies of this nature. Additionally, characteristics of the sample used (size, profile, and source) differentiate this study from others. 323 clients from the industrial sector of a financial institution were used. Through the application of the statistical technique known as logistic regression, an econometric model of solvency prediction was developed that includes five variables. The precision of the model was relatively high, in that 94.85% of the sample was classified correctly. The validation of the model was performed by the method known as cross-validation, dividing the original sample in two: one part for constructing the model and the other for validating the model.

Date: 2002
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Persistent link: https://EconPapers.repec.org/RePEc:abg:anprac:v:6:y:2002:i:3:184

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