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

Volatilidade dos retornos e governança: um estudo de eventos da crise do subprime

The financial crisis that occurred between the years 2007 and 2008, known as the subprime crisis, has highlighted the governance of companies in Brazil and worldwide. To monitor the financial risk, quantitative tools of risk management were created in the 1990s, after several financial disasters. The market turmoil has also led companies to invest in the development and use of information, which are applied as tools to support process control and decision making. Numerous empirical studies on informational efficiency of the market have been made inside and outside Brazil, revealing whether the prices reflect the information available instantly. The creation of different levels of corporate governance on BOVESPA, in 2000, made the firms had greater impairment in relation to its shareholders with greater transparency in their information. The purpose of this study is to analyze how the subprime financial crisis has affected, between January 2007 and December 2009, the volatility of stock returns in the BM&BOVESPA of companies with greater liquidity at different levels of corporate governance. From studies of time series and through the studies of events, econometric tests were performed by the EVIEWS, and through the results obtained it became evident that the adoption of good practices of corporate governance affect the volatility of returns of companies

Análise de volatilidade, integração de preços e previsibilidade para o mercado brasileiro de camarão

The present paper has the purpose of investigate the dynamics of the volatility structure in the shrimp prices in the Brazilian fish market. Therefore, a description of the initial aspects of the shrimp price series was made. From this information, statistics tests were made and selected univariate models to be price predictors. Then, it was verified the existence of relationship of long-term equilibrium between the Brazilian and American imported shrimp and if, confirmed the relationship, whether or not there is a causal link between these assets, considering that the two countries had presented trade relations over the years. It is presented as an exploratory research of applied nature with quantitative approach. The database was collected through direct contact with the Companhia de Entrepostos e Armazéns Gerais de São Paulo (CEAGESP) and on the official website of American import, National Marine Fisheries Service - National Oceanic and Atmospheric Administration (NMFS- NOAA). The results showed that the great variability in the active price is directly related with the gain and loss of the market agents. The price series presents a strong seasonal and biannual effect. The average structure of price of shrimp in the last 12 years was R$ 11.58 and external factors besides the production and marketing (U.S. antidumping, floods and pathologies) strongly affected the prices. Among the tested models for predicting prices of shrimp, four were selected, which through the prediction methodologies of one step forward of horizon 12, proved to be statistically more robust. It was found that there is weak evidence of long-term equilibrium between the Brazilian and American shrimp, where equivalently, was not found a causal link between them. We concluded that the dynamic pricing of commodity shrimp is strongly influenced by external productive factors and that these phenomena cause seasonal effects in the prices. There is no relationship of long-term stability between the Brazilian and American shrimp prices, but it is known that Brazil imports USA production inputs, which somehow shows some dependence productive. To the market agents, the risk of interferences of the external prices cointegrated to Brazilian is practically inexistent. Through statistical modeling is possible to minimize the risk and uncertainty embedded in the fish market, thus, the sales and marketing strategies for the Brazilian shrimp can be consolidated and widespread

Eficiência e razão de hedge: uma análise dos mercados futuro brasileiros de boi, café, etanol, milho e soja

This research aims to investigate the Hedge Efficiency and Optimal Hedge Ratio for the future market of cattle, coffee, ethanol, corn and soybean. This paper uses the Optimal Hedge Ratio and Hedge Effectiveness through multivariate GARCH models with error correction, attempting to the possible phenomenon of Optimal Hedge Ratio differential during the crop and intercrop period. The Optimal Hedge Ratio must be bigger in the intercrop period due to the uncertainty related to a possible supply shock (LAZZARINI, 2010). Among the future contracts studied in this research, the coffee, ethanol and soybean contracts were not object of this phenomenon investigation, yet. Furthermore, the corn and ethanol contracts were not object of researches which deal with Dynamic Hedging Strategy. This paper distinguishes itself for including the GARCH model with error correction, which it was never considered when the possible Optimal Hedge Ratio differential during the crop and intercrop period were investigated. The commodities quotation were used as future price in the market future of BM&FBOVESPA and as spot market, the CEPEA index, in the period from May 2010 to June 2013 to cattle, coffee, ethanol and corn, and to August 2012 to soybean, with daily frequency. Similar results were achieved for all the commodities. There is a long term relationship among the spot market and future market, bicausality and the spot market and future market of cattle, coffee, ethanol and corn, and unicausality of the future price of soybean on spot price. The Optimal Hedge Ratio was estimated from three different strategies: linear regression by MQO, BEKK-GARCH diagonal model, and BEKK-GARCH diagonal with intercrop dummy. The MQO regression model, pointed out the Hedge inefficiency, taking into consideration that the Optimal Hedge presented was too low. The second model represents the strategy of dynamic hedge, which collected time variations in the Optimal Hedge. The last Hedge strategy did not detect Optimal Hedge Ratio differential between the crop and intercrop period, therefore, unlikely what they expected, the investor do not need increase his/her investment in the future market during the intercrop

Análise da estrutura e transporte do zooplâncton no estuário do Rio Caravelas (Bahia-Brasil) através do uso do zooscan

Spatial-temporal dynamics of zooplankton in the Caravelas river estuary (Bahia, Brazil). The survey was conducted in order to describe the zooplankton community of the estuary Caravelas (Bahia, Brazil), to quantify and relate the patterns of horizontal and vertical transport with the type of tide (neap and spring) and tidal phase (flood and ebb). Zooplankton samples were collected with the aid of a suction pump (300L), filtered in plankton nets (300μm) and fixed in saline formalin 4%. Samples were collected at a fixed point (A1), near the mouth of the estuary, with samples taken at neap tides and spring tides during the dry and rainy seasons. Samples were collected for 13 hours, at intervals of 1 hour in 3 depths: surface, middle and bottom. Simultaneous collection of biological, we measured the current velocity, temperature and salinity of the water through CTD. In the laboratory, samples were selected for analysis in estereomicroscope, with 25 groups identified, with Copepoda getting the highest number of species. The 168 samples obtained from temporal samples were subsampled and processed on equipment ZooScan, with the aid of software ZooProcess at the end were generated 458.997 vingnettes. 8 taxa were identified automatically, with 16 classified as a semi-automatic. The group Copepoda, despite the limited taxonomic refinement ZooScan, obtained 2 genera and 1 species identified automatically. Among the seasons dry and wet groups Brachyura (zoea), Chaetognatha, and the Calanoid copepods (others), Temora spp., Oithona spp. and Euterpina acutifrons were those who had higher frequency of occurrence, appearing in more than 70% of the samples. Copepoda group showed the largest percentage of relative abundance in both seasons. There was no seasonal variation of total zooplankton, with an average density of 7826±4219 org.m-3 in the dry season, and 7959±3675 org.m-3 in the rainy season, neither between the types and phases of the tides, but seasonal differences were significant recorded for the main zooplankton groups. Vertical stratification was seen for the major zooplankton groups (Brachyura, Chaetognatha, Calanoida (other), Oithona spp, Temora spp. e Euterpina acutifrons). The scale of this stratification varied with the type (square or tide) and tidal phase (flood or ebb). The instantaneous transport was more influenced by current velocity, with higher values observed in spring tides to the total zooplankton, however, there was a variation of this pattern depending on the zooplankton group. According to the data import and export of total zooplankton, the outflow of organisms of the estuary was higher than the input. The results suggest that the estuary of Caravelas may influence the dynamics of organic matter to the adjacent coast, with possible consequences in National Marine Park of Abrolhos