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

Conhecimento, sociabilidade e lazer em jogos online : uma etnografia na "Lan House do Paulo" em São Gonçalo do Amarante-RN

In a highly dynamic society such as we live, have access to the virtual world is an increasingly common practice, is aiming to study, work or to search leisure through chat rooms, sites and games, being incorporated by the most varied groups that end up appropriating these new possibilities of interaction, shaping them in order to adapt them to their needs / wants. The specific purposes pursued through the use of tools available over the Internet can vary considerably when one takes into account specific user groups, which makes the topic quite relevant to problematization, especially when we take into account access through lan houses. This research seeks to study the networks of knowledge, sociability and leisure formed by young people who frequented the "Lan house do Paulo" in São Gonçalo do Amarante - RN based on the use of the online role-playing-game World of Warcraft, which makes possible the interaction of several users through an avatar resident in a virtual world, theoretically questioning the importance of this type of platform for the development and maintenance of social interactions among its users

Comunidades tradicionais em áreas protegidas: convergências e lacunas da Política Urbana e Ambiental na Reserva de Desenvolvimento Sustentável Estadual Ponta do Tubarão/RN

This work presents a reflection on possibilities and boundaries of consolidation and expansion of human settlements characterized as traditional communities that are located within protected areas, using as study reference the State Sustainable Development Reserve Ponta do Tubarão, at Rio Grande do Norte state. The main topics highlight the conflict between the right to housing and the prevalence of fundamental rights of traditional populations, opposed to the diffuse right to environment, according to the regulatory framework of the Brazilian Urban and Environmental Policies. At the same time that these settlements, historically built, are substantiated by the principles of recognition of rights to traditional populations, they are in a condition of complexity to the resolution of conflicts in its urban dimension and lead to an impairment of natural sites. This work questions how the instruments of land use and occupation are defined and relate to environmental planning, especially considering that the settlements are located in Permanent Preservation Areas (APP). It aims to further the discussion of the urban dimension in settlements, characterizing its formation and growth process, to identify the gaps and convergences between the Urban and Environmental Policy, under the foundations of a socio-environmental approach. The results spotlights the conflicts between occupation and natural areas, inferring that the definition of Urban Policies instruments and its integration with Environmental Policies instruments account for essential and priority actions to the achievement to the rights to a sustainable city, as determined in the Cities Statute and environmental protection goals, defined for the Conservation Units