Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

Tecnologia social para autogestão : um estudo em empreendedorismo econômico solidário da cadeia produtiva da cajucultura no Rio Grande do Norte

The theme of this dissertation is social technology for self-management: a study in economic enterprise supportive of Rio Grande do Norte. The research aimed to obtain evidence that the reapplication of technology management, basic economic-financial and pricing, as production costs, has the potential to contribute to the self-management of APABV. The social technology and self-management are theoretical frameworks used and where workers are central figures in both the generation and replication of technologies that are compatible with their realities, as in the conduct and management approach adopted by them in their venture, they are makers decisions. To achieve the proposed objective was accomplished participatory research, which was used in addition to document analysis, participatory methodologies such as the construction of the DRP, group interview, experience in the production environment and family of entrepreneurs APABV. This research allowed the management technologies such as spreadsheets controls basic economic and financial costs, when socialized and understood by workers has the potential informational and become part of their daily decision-making process of the project, making up social technology

Imagens do terceiro setor: um estudo com pais e responsáveis financeiros das organizações educacionais

The present report is the result of an applied research in the educational entities of the third sector, aiming to demonstrate whether the financial influences the perception of users on the image of those entities. For both used the prospect of integrative marketing relationship adapting to and developing a set of indicators which bore the measurement of images from the model of Machado et al (2005) and Kotler and Fox (1994). The sample included a total of 187 parents and financial responsibility in 03 (three) institutions of education in Natal / RN. These data were processed by multivariate statistical analysis, factor analysis, linear regression, analysis of cluster and discriminant analysis. The factor analysis also identified 6 images perceived by users of services. Next were the relationships of cause and effect between the financial and images formed. In discriminant analysis, was identified two distinct groups of parents and guardians with financial perceptions similar and well defined. The result of the work shows that the differential level of financial participation of parents and guardians not influence the formation of the images formed from educational institutions of the third sector