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.

Desenvolvimento de barra alimentícia adicionada de café: estudo de marketing

The consumption of snack bars is based especially on the demand for practical and nutritious food. Coffee is highlighted for being appreciated and consumed worldwide, presenting elevated antioxidant activity, in addition to peculiar sensorial attributes. Therefore, it has great potential for use in many formulations. However, the success in the acceptance of a new product also derives from adequate marketing strategies. In this context, the present study aimed at evaluating the feasibility of introducing to the market a snack bar added with coffee, by means of sensorial acceptance and purchase intent of the consumers, in addition to identifying the best concept and the possible market segments. This work was a qualitative, by means of a focus group (content analysis), and quantitative research, by means of sensorial analysis and structures questionnaires (descriptive – frequency distribution, arithmetic mean, crosstabs and t test – and multivariate – cluster and discriminate analysis - statistical techniques). With the results, we showed that the main aspects considered by the consumers regarding the snack bar added with coffee. According to the qualitative evaluation, the consumer prefers packaging with matte colors ranging in the tones related to the coffee grain. The analysis of the quantitative data allows us to infer that the evaluations of the product regarding overall impression, purchase intent, preference and expectation before and after consuming the product are better for packaging containing the information “special coffee flavor – 100% arabic”. Regarding market segment, it was possible to conclude that, of the three extracted groups, the group of “healthy and conscious consumers” was the segment with higher potential for exploitation regarding purchase and consumption of the snack bar added with coffee.