Risco de crédito: uma abordagem utilizando análise discriminante, regressão logística e redes neurais artificiais

Considering the relevance of researches concerning credit risk, model diversity and the existent indicators, this thesis aimed at verifying if the Fleuriet Model contributes in discriminating Brazilian open capital companies in the analysis of credit concession. We specifically intended to i) identify the economic-financial indicators used in credit risk models; ii) identify which economic-financial indicators best discriminate companies in the analysis of credit concession; iii) assess which techniques used (discriminant analysis, logistic regression and neural networks) present the best accuracy to predict company bankruptcy. To do this, the theoretical background approached the concepts of financial analysis, which introduced themes relative to the company evaluation process; considerations on credit, risk and analysis; Fleuriet Model and its indicators, and, finally, presented the techniques for credit analysis based on discriminant analysis, logistic regression and artificial neural networks. Methodologically, the research was defined as quantitative, regarding its nature, and explanatory, regarding its type. It was developed using data derived from bibliographic and document analysis. The financial demonstrations were collected by means of the Economática ® and the BM$FBOVESPA website. The sample was comprised of 121 companies, being those 70 solvents and 51 insolvents from various sectors. In the analyses, we used 22 indicators of the Traditional Model and 13 of the Fleuriet Model, totalizing 35 indicators. The economic-financial indicators which were a part of, at least, one of the three final models were: X1 (Working Capital over Assets), X3 (NCG over Assets), X4 (NCG over Net Revenue), X8 (Type of Financial Structure), X9 (Net Thermometer), X16 (Net Equity divided by the total demandable), X17 (Asset Turnover), X20 (Net Equity Profitability), X25 (Net Margin), X28 (Debt Composition) and X31 (Net Equity over Asset). The final models presented setting values of: 90.9% (discriminant analysis); 90.9% (logistic regression) and 97.8% (neural networks). The modeling in neural networks presented higher accuracy, which was confirmed by the ROC curve. In conclusion, the indicators of the Fleuriet Model presented relevant results for the research of credit risk, especially if modeled by neural networks.

Nanocompósitos com atividade antioxidante de amido de milho/isolado proteico de soro de leite/ óleo essencial de alecrim obtidos por extrusão termoplástica

In order to improve the quality and safety of food, the active packaging emerges as a new technology based on the release of composites beneficial to food products. Thus, biodegradable films incorporated with active substances have the function of acting as a barrier to external elements, protecting the product and increasing its shelf life. They are formulated from proteins, polysaccharides, lipids or from the combination of these compounds. However, there is a need to improve the performance properties of these packages. Nanotechnologies, then, emerges with the study of many nanoparticles as additives to modify the performance of biodegradable polymers. With this, we aimed at developing and active antioxidant film of corn starch blenders and whey protein isolate with rosemary essential oil or microcapsules of rosemary essential oil reinforced with sodium montmorillonite (MMTNa + ) nanoparticles by extrusion. The films were developed and characterized in a first stage for the selection of the best polymeric blender using the following analyses: water vapor permeability (WVP), machanical properties; optical, thermogravimetry (TG), differential scanning calorimetry (DSC), x-ray diffraction (XRD) and scanning electron microscopy (SEM). In the second stage, montmorillonite clay nanoparticles and rosemary essential oil were added as reinforcement to evaluate its antioxidant effect. In a third stage, we studied the addition of microcapsules of rosemary essential oil (MR) as a form of protecting the active agent and its antioxidant potential in the films. The results indicate that the development of p olymeric blender with 30% of corn starch substitution is the most indicated for future work. The addition of rosemary essential oil or microcapsule of rosemary essential oil allowed for the obtaining of nanocomposites with antioxidant potential for application in food packages.