Estudo e análise estatística no mercado de ações brasileiro

The objective of this paper is to verify and analyze the existence in Brazil of stylized facts observed in financial time series: volatility clustering, probability distributions with fat tails, the presence of long run memory in absolute return time series, absence of linear return autocorrelation, gain/loss asymmetry, aggregative gaussianity, slow absolute return autocorrelation decay, trading volume/volatility correlation and leverage effect. We analyzed intraday prices for 10 stocks traded at the BM&FBovespa, responsible for 52.1% of the Ibovespa portfolio on Sept. 01, 2009. The data analysis confirms the stylized facts, whose behavior is consistent with what is observed in international markets.

Previsão de demanda para peças de reposição de alto giro: aplicação de método descritivo simples comparado com o modelo suavização exponencial

O estudo de métodos de previsão de demandas é um conceito bastante popular, mas nem sempre seus resultados são facilmente aplicáveis nas organizações por várias limitações. O propósito deste artigo é apresentar um método simples e descritivo para a previsão de demanda para peças de reposição de alto giro e comparar os resultados com o modelo de suavização exponencial. Foi utilizado para isto, dados reais de consumo de uma empresa de geração de energia em dois anos com a mesma condição de contorno, e estabeleceu-se o ano de 2012 com a série de aplicação dos métodos e a série de 2013 com a série de validação dos resultados e em todas as amostras tomadas observou-se um menor erro quadrático RMSE, a favor do método descritivo simplificado. Todas as quatro séries analisadas se caracterizam pela alta dispersão dos dados, e não possuem tendências e sazonalidades.

Análise matemática e estatística da produtividade de lavouras cafeeiras agroquímica e orgânica na região da alta paulista

Studies with organic systems have shown the feasibility and ecological and social sustainability of these agroecosystems, unlike the systems agrochemicals (conventional) production. Some studies have concluded that for the model agrochemical exists less interaction between the flow of internal energy, basically the crop receives all inputs to production with no increase in "energy quality" within the system, while in the organic model of production has increased interaction between different resources in the system. The current economic and ecological crisis, exposed no sustainability of the production pattern of industrialized agriculture developed in a way, showing the dependence of developed countries on imports of agricultural commodities produced in the third world, among there coffee. Given these facts, developed a survey to identify problems in the Alta Paulista region, west of São Paulo State, in relation to coffee production systems. Actually, the fundamental problem, according to the research, farmers in this region, is to choose a viable production system correctly (environmental, social and economic); agrochemical or organic. The objectives of this study were to analyze the yield of production systems and agro-chemical and organic coffee in the period from 2003 to 2007, in 30 producing properties, located in this region, in order to point the production system to produce the highest yield. According to the methodology of CONAB, data collected were recorded on spreadsheets to be used as variables in statistical analysis models and mathematics. We performed a descriptive analysis of productivity data and were used for statistical analysis tests for parametric and nonparametric analysis of variance. The mathematical analyses of the curves were prepared with Origin for Windows 6.0 software, which uses numerical methods to fit the data supplied to a function of variable parameters. Unlike conventional systems of production, the organic system showed greater viability of the production model. Furthermore, with the quantitative modeling proposal, it is possible to perform the evaluation of these types of investments, providing more security to the farmer at the time of decision.

Análise estatística de parâmetros elétricos em usinas sucroalcoleiras do centro-oeste paulista

The industry of sugar cane has become an important contributor to the generation of electricity in Brazil. Currently there are 434 sugar and ethanol plants operating in the country, 23% of the total export electricity to the National Integrated System (SIN), the state of São Paulo has 182 plants and 30% of them export energy to the SIN. The objective of this study is to compare parameters of electrical efficiency in the sugar and alcohol industry. For the study, three plants localized in the midwest region of Sao Paulo state with great potential for production and exporting bioenergy were chosen. Five energy analyzers LANDYS + GYR SAGA were used for measure the electrical parameters. The variables studied were energy consumption (C) and power factor (PF). For the statistical analysis it was adopteda randomized block design in a factorial 3 5composed of three companies and five sectors of energy consumption,in which: reception(1), milling (2), boiler (3), supporting activities / juice treatment (4), and distillation (5), totaling 15 treatments. Each group comprised 192 repetitions (48 hours 4 measurements per hour). It was concluded that there is no interest for the plans to fix the FP and reach a value 0.92, which is considered the ideal power factor.This,because the plants generate their own energy and are not penalized. Regarding the energy consumed, all sectors had significant differences. When comparingsector to sector, the plant called USB showed no significant differences in sectors 1 and 3, and the plant USC, in sectors 1 and 4. Considering the production units of this sector and selling power this type of evaluation is essential to perform this analysis, since the analyzed sectors are most important in the production of sugar and ethanol, and analyze and monitor these parameters, use and consumption energy can provide a greater supply of energy to be commercialized.

Modelos agrometeorológicos para previsão da produtividade e qualidade de bebida natural do cafeeiro

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modelos de previsão de ocorrência de adultos de diatraea saccharalis (Fabricius, 1794) (Lepidoptera: Crambidae) em cana-de-açúcar (Saccharum spp.)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A prática como componente curricular via Projeto Integrado de Prática Educativa (PIPE) no ensino de estatística na Universidade: implementação e implicações na Formação Inicial do Professor de Matemática

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Matemática e estatística aplicadas a gestão da qualidadade nos cursos de Engenharia de Produção no Brasil: um contraponto entre a formação e o mercado de trabalho

Pós-graduação em Educação Matemática - IGCE

Desenvolvimento de modelo auto-regressivo para previsão em pronto-atendimento

The 1988 constitution makes an life is a supreme good when increased health as the fundamental condition requiring that all ill patient has the right to be treated in a public hospital (CF, art. 196). In this sense, the goal of this work is to generate a weekly forecast of hospital care by means of an advanced prediction model. It is expected that the model of self-regressivas seasonal moving averages SARIMA generate reliable and adherent to issue forecasts analyzed, thus enabling better resource allocation and more efficient hospital management

Previsão de demanda de veículos automotores através do modelo de regressão linear múltipla

This study aimed to model a equation for the demand of automobiles and light commercial vehicles, based on the data from February 2007 to July 2014, through a multiple regression analysis. The literature review consists of an information collection of the history of automotive industry, and it has contributed to the understanding of the current crisis that affects this market, which consequence was a large reduction in sales. The model developed was evaluated by a residual analysis and also was used an adhesion test - F test - with a significance level of 5%. In addition, a coefficient of determination (R2) of 0.8159 was determined, indicating that 81.59% of the demand for automobiles and light commercial vehicles can be explained by the regression variables: interest rate, unemployment rate, broad consumer price index (CPI), gross domestic product (GDP) and tax on industrialized products (IPI). Finally, other ten samples, from August 2014 to May 2015, were tested in the model in order to validate its forecasting quality. Finally, a Monte Carlo Simulation was run in order to obtain a distribution of probabilities of future demands. It was observed that the actual demand in the period after the sample was in the range that was most likely to occur, and that the GDP and the CPI are the variable that have the greatest influence on the developed model

Métodos de previsão auto-regressivo aplicado a uma série de volume de produção de caminhões

The national truck fleet has expanded strongly in recent decades. However, due to fluctuations in the demand that the market is exposed, it needed up making more effective strategic decisions of automakers. These decisions are made after an evaluation of guaranteed sales forecasts. This work aims to generate an annual forecast of truck production by Box and Jenkins methodology. They used annual data for referring forecast modeling from the year 1957 to 2014, which were obtained by the National Association of Motor Vehicle Manufacturers (Anfavea). The model used was Autoregressive Integrated Moving Average (ARIMA) and can choose the best model for the series under study, and the ARIMA (2,1,3) as representative for conducting truck production forecast

Modelagem auto-regressiva na previsão de demanda dos produtos de uma empresa do setor químico

Considering the high competitiveness in the industrial chemical sector, demand forecast is a relevant factor for decision-making. There is a need for tools capable of assisting in the analysis and definition of the forecast. In that sense, the objective is to generate the chemical industry forecast using an advanced forecasting model and thus verify the accuracy of the method. Because it is time series with seasonality, the model of seasonal autoregressive integrated moving average - SARIMA generated reliable forecasts and acceding to the problem analyzed, thus enabling, through validation with real data improvements in the management and decision making of supply chain

Previsão da capacidade de carga de estacas escavadas em solo arenoso da região de Araquari-SC

In Geotechnical engineering the foundation projects depend on the bearing capacity and the acceptable displacements. One of the possible ways to predict the bearing capacity of foundations is through semi-empirical statistical methods which correlate in-situ tests (SPT and CPT). The piles breaking loads are defined by the interpretation of the load x head displacement curve and the experimental data acquired through the load test. In this work it is studied the behavior of bored piles executed in the Araquari/SC region, comparing the bearing capacity values predicted by the methods DECOURT & QUARESMA MODIFICADO (1996), AOKI & VELLOSO MODIFICADO MONTEIRO (2000), MILITITISKY E ALVES (1985), DECOURT & QUARESMA (1978), MÉTODO DE AOKI & VELLOSO (1975) e PHILOPANNAT (1986), with the results of the load test, evaluating their differences and discussing parameters that have direct effects on the prediction