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

Dramaturgia do aqui e agora: presença, recepção e sentido no corpo do ator

The actor is an actor during all the phases of creation and development of his character. (S) He goes beyond the moment of interpreting. In this sense, in her (his) daily life, the actor may use her (his) potential to extract from reality the necessary elements for the work of creation. This is a theoretical research which focus on the concept of presence in the actor s work, stretching the concept beyond the scene, encompassing different components such as the body, the word, the silence, the technique and the acting as the actor s stance in regards to his own reality. The objective of such stance is to integrate him (her) self in the environment, balancing his (hers) inner life with the outside life flow. To reach this objective, the research drew theoretical resources from the concept of presence in the actor s work according to BROOK, BARBA, GROTOWSKI and MNOUCHKINE and the studies on reception theory in ISER, 1996; GUMBRECHT, 2010. Thus, the dialogue between reader and actor high lights both as receivers in this work. A practical description of a street theater Kamchàtka show, featured by the Kamchàtka Company is used as an example of the research on the presence. The elements localized in this show are: play, listening, word, silence, meaning, relationship with here and now and the effects of the said presence