The failure prediction models: a comparative study
by Nesrine Ayadi
International Journal of Accounting and Finance (IJAF), Vol. 9, No. 2/3/4, 2019

Abstract: The objective of this paper is to explain and predict the companies' failure risk of claiming a credit in order to improve the decision-making process. Our tests are conducted on a sample of 513 French companies and use the methodologies of principal component analysis, Fisher's linear discriminant analysis; and logistic regression. All have been implemented using carefully selected economic and financial ratios. The empirical results show that the turnover in logarithm, financial independence, the by-employee turnover and the turnover growth rate are the most important explanatory variables with a ranking success that exceeds 70%. This finding is consistent across all tested models and specifications.

Online publication date: Mon, 20-Apr-2020

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