Indian Journal of Science and Technology
Year: 2019, Volume: 12, Issue: 24, Pages: 1-14
Isabel Cristina Alzate Rendón* and Antonio José Boada
Institución Universitaria CEIPA, Escuela de Administración, Grupo de Investigación IMCA, Sabaneta, Antioquia, Colombia; [email protected], [email protected]
*Author for correspondence
Isabel Cristina Alzate Rendón
Institución Universitaria CEIPA, Escuela de Administración, Grupo de Investigación IMCA, Sabaneta, Antioquia, Colombia. Email: [email protected]
Objectives: This article describes the use and advantages of the Logit Statistical Model to assess the risk levels of default of service sector companies. Methods/Statistical Analysis: With some level of certainty, it was developed a statistical model to measure the probability of default of some Venezuelan companies. This measure was performed between 2004 and 2007 (just before this country got immersed in the serious economic situation that is going through now). The implementation of the Logit Model permitted to put into practice a pattern of predictive modelling to foresee the risks of financial stress of a company hindering the payment of the credit obligations, originating the stimation of default or nondefault condition. This stimation was achieved taking into account the financial indicators, either theoretical variables or exogenous assessment variables (considered by the authors of this study)such as the commercial accounts receivable in correspondence with the total assets, the net inventory and the total current liabilities in correspondence with the total assets, of several Venezuelan companies that belong to the financial sector. Findings/Application: Finally, despite the volatility features of the markets of emerging countries, it must be highlighted that it is possible to come up with the design of statistical models that permit to figure out the prediction of capacity of payment through the use of audited accounting financial statements, which provide valuable information for strategically decision – making purposes of the organization.
Keywords: Companies Risk, Credit Risk Levels, Default Prediction, Emerging Markets, Logit Model, Volatility
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