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

A influência do processo de terceirização de tecnologia da informação na utilização dos modelos de contratação de serviços: um estudo de casos múltiplos

The change in the economic world and the emergence of Internet as a tool for communication and integration among the markets have forced organizations to adopt a different structure, process-oriented with a focus on information management. Thus, information technology has gained prominence in the organizational context, increasing its complexity and range of services provided by this function. Moreover, outsourcing has become an important model for flexible corporate structure, helping organizations to achieve better results when carrying out their activities and processes and be more competitive. To make the IT outsourcing, it is necessary to follow certain steps that range from strategic assessment to the management of outsourced service. Such steps can influence the form of contracting services, varying the types of service providers and contractors. Thus, the study aimed to identify how this IT outsourcing process influences the use of models for contracting services. For this, a study was conducted in multiple cases study involving two companies in Rio Grande do Norte State, specifically the health sector. Data collection was carried out with the CIOs of the companies surveyed through semi-structured interviews. According to the results obtained, it was found that the outsourcing process more structured influences the use of a more advanced contracting model. However, there are features found in these steps carrying more clearly this influence, as the goals pursued by outsourcing, the criteria used in selecting the supplier, a contract negotiation, how to transition services and the use of methods management, but can vary depending on the level of maturity in the relationship of the companies examined. Moreover, it was found that the use of contracting model may also influence how it is developed the IT outsourcing process, requiring or not its more formalized and organization