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 descentralização das políticas de desenvolvimento rural: uma análise da experiência do Rio Grande do Norte

MATOS FILHO, João. A descentralização das Políticas de desenvolvimento rural - uma análise da experiência do Rio Grande do Norte. 2002. 259f. Tese (Doutorado em Ciências Econômicas)– Instituto de Economia da Universidade Estadual de Campinas, Campinas, 2002.

Análise do comportamento e crescimento do camarão branco Litopenaeus vannamei (Boone, 1931) em diferentes substratos inconsolidados

The aim of this study was to test the sediment preference of L. vannamei shrimp. It was observed shrimp visit frequency, swimming and burying behaviour at different sediment compositions for 24h. Juvenile (0.93 ± 0.29g) and sub-adult shrimps (10.0 ± 1.18g) were obtained from the aquaculture station at Universidade Federal Rural do Semi-Árido UFERSA, and held in a plastic tank (water volume 500 L) supplied with aerated water and kept at constant temperature, pH, and salinity. Shrimp was fed by commercial shrimp dry food. The experimental substrates were composed by A: medium sand + thick sand + very thick sand + gravel; B: very fine sand + fine sand; and C: silt + clay. Thus, six different substrate combinations were tested: A, B, C, A+B, A+C, B+C. To test preference, it was used a cylindrical tank (40 l) divided into six differently substrate compartments. A single shrimp was introduced each tank and the frequency at which this shrimp visited each compartment was recorded over a 24h study period. It was tested 54 shrimp (18 sub-adult males, 18 subadult females and 18 juveniles). For each trial, sediment and water were changed to avoid pheromones and residues influence. Shrimp were weighted and sub-adults were divided by sex: males present petasma and females present thelycum. Data were collected on the experimental day at 19:30; 20:30; 00:30; 1:30; 05:30; 06:30; 13:30 and 14:30 h. At each time point, shrimp were observed for 20-min periods, in which we noted down which compartment the shrimp was occupying at 2-min intervals. Thus, for each period we had eleven observations (88 observations per day). For observations at night, it was used dim red light that did not affect shrimp behaviour. At each 20-min period, it was observed visit frequency in each substrate, if shrimp was burred or not or if it was swimming. There was not significant difference between light and dark burry activity for females. Swimming activity was significantly higher at night, mainly at 00:30 and 01:30 h. All L. vannamei shrimp showed preference for sediment B. This animal presents cyclic activity, spends the day light period buried and swims at night