Options listing and the volatility of the underling asset: a study on the derivative market function

There are basic misunderstandings on derivative markets. Some professionals believe that they are a kind of casinos and have no utility for the investors. This work looks at the effects of options introduction in the Brazilian market, seeking for another benefit for this introduction: changes in the stocks risk leveI. Our results are the same found in the US and other markets: the options introduction reduces the stocks volatility. We also found that there is a slight indication that the volatility becames more stochastic with this alternative.

A SARIMA forecasting model to predict the number of cases of dengue in Campinas, State of São Paulo, Brazil

INTRODUCTION: Forecasting dengue cases in a population by using time-series models can provide useful information that can be used to facilitate the planning of public health interventions. The objective of this article was to develop a forecasting model for dengue incidence in Campinas, southeast Brazil, considering the Box-Jenkins modeling approach. METHODS: The forecasting model for dengue incidence was performed with R software using the seasonal autoregressive integrated moving average (SARIMA) model. We fitted a model based on the reported monthly incidence of dengue from 1998 to 2008, and we validated the model using the data collected between January and December of 2009. RESULTS: SARIMA (2,1,2) (1,1,1)12 was the model with the best fit for data. This model indicated that the number of dengue cases in a given month can be estimated by the number of dengue cases occurring one, two and twelve months prior. The predicted values for 2009 are relatively close to the observed values. CONCLUSIONS: The results of this article indicate that SARIMA models are useful tools for monitoring dengue incidence. We also observe that the SARIMA model is capable of representing with relative precision the number of cases in a next year.

The feasibility of forecasting influenza epidemics in Cuba

A large influenza epidemic took place in Havana during the winter of 1988. The epidemiologic surveillance unit of the Pedro Kouri Institute of Tropical Medicine detected the begining of the epidemic wave. The Rvachev-Baroyan mathematical model of the geographic spread of an epidemic was used to forecast this epidemic under routine conditions of the public health system. The expected number of individuals who would attend outpatient services, because of influenza-like illness, was calculated and communicated to the health authorities within enough time to permit the introduction of available control measures. The approximate date of the epidemic peak, the daily expected number of individuals attending medical services, and the approximate time of the end of the epidemic wave were estimated. The prediction error was 12%. The model was sufficienty accurate to warrant its use as a pratical forecasting tool in the Cuban public health system.

The three phases of the ensemble forecasting of niche models: geographic range and shifts in climatically suitable areas of Utetheisa ornatrix (Lepidoptera, Arctiidae)

Species' geographic ranges are usually considered as basic units in macroecology and biogeography, yet it is still difficult to measure them accurately for many reasons. About 20 years ago, researchers started using local data on species' occurrences to estimate broad scale ranges, thereby establishing the niche modeling approach. However, there are still many problems in model evaluation and application, and one of the solutions is to find a consensus solution among models derived from different mathematical and statistical models for niche modeling, climatic projections and variable combination, all of which are sources of uncertainty during niche modeling. In this paper, we discuss this approach of ensemble forecasting and propose that it can be divided into three phases with increasing levels of complexity. Phase I is the simple combination of maps to achieve a consensual and hopefully conservative solution. In Phase II, differences among the maps used are described by multivariate analyses, and Phase III consists of the quantitative evaluation of the relative magnitude of uncertainties from different sources and their mapping. To illustrate these developments, we analyzed the occurrence data of the tiger moth, Utetheisa ornatrix (Lepidoptera, Arctiidae), a Neotropical moth species, and modeled its geographic range in current and future climates.

Time-series forecasting of pollutant concentration levels using particle swarm optimization and artificial neural networks

This study evaluates the application of an intelligent hybrid system for time-series forecasting of atmospheric pollutant concentration levels. The proposed method consists of an artificial neural network combined with a particle swarm optimization algorithm. The method not only searches relevant time lags for the correct characterization of the time series, but also determines the best neural network architecture. An experimental analysis is performed using four real time series and the results are shown in terms of six performance measures. The experimental results demonstrate that the proposed methodology achieves a fair prediction of the presented pollutant time series by using compact networks.

Volatility of Different Formulations of Clomazone Herbicide

Volatilization represents an important process in the displacement of pesticides for the environment. The physicochemical properties of the clomazone molecule indicate its relative volatility. Therefore, this study was carried out to assess the volatilization of different clomazone herbicide formulations using bioindicator species. To that end, airtight glass boxes were used with the presence of different clomazone formulations and plant species. The formulations used were Gamit 360 CS(r), Gamit 500 EC(r) and Gamit Star(r). The plant species assessed were maize, sorghum and rice. With the results obtained it is possible to conclude that, among the formulations, Gamit 360 CS(r) has caused less phytotoxicity to the bioindicator species in comparison to the formulations of Gamit 500 EC(r) and Gamit Star(r) formulations. In general, The Gamit 500 EC(r) and Gamit Star(r) have not differed in the phytotoxicity potential for the bioindicator species.

Effects of overvaluation and exchange rate volatility over industrial investment: empirical evidence and economic policy proposals for Brazil

The present article aims to analyze the recent behavior of real exchange rate in Brazil and its effects over investment per worker in Brazilian manufacturing and extractive industry. Preliminary estimates presented in the article shows an over-valuation of 48% of real exchange rate in Brazil. The reaction between the level (and volatility) of real exchange rate and investment (per worker) in Brazil is analyzed by means of a panel data econometric model for 30 sectors of Brazilian manufacturing and extractive industry. The empirical results show that the level and volatility of real exchange rate has a strong effect over investment per worker in Brazilian industry. Finally, we conclude the article presenting a proposal for a new macroeconomic regime that aims to produce an acceleration of economic growth of Brazilian economy and, by that, a catching-up process with developed countries.

MÉTODOS COLABORATIVOS NA GESTÃO DE CADEIAS DE SUPRIMENTOS: DESAFIOS DE IMPLEMENTAÇÃO

RESUMOO tema gestão colaborativa vem sendo abordado como forma de gerar vantagem competitiva. Iniciativas colaborativas em cadeias de suprimentos (CS) proporcionaram o surgimento de métodos e práticas que corroboram a ideia de que a competitividade não se dá mais entre empresas isoladas, e sim entre cadeias. Na literatura, além de métodos colaborativos para a gestão da cadeia de suprimentos (GCS), é possível encontrar iniciativas para projeto, configuração, otimização, entre outras. Porém, observa-se baixa adesão de métodos colaborativos para a GCS, assim como dificuldades de implementação. O objetivo do artigo é investigar os métodos colaborativos referentes à coordenação de CS e analisar suas características e dificuldades de implementação. Uma revisão sistemática apontou o Collaborative Planning, Forecasting and Replenishment (CPFR) como o método colaborativo mais abordado e, posteriormente, um estudo de caso identificou dificuldades na implementação que colaboraram com o que foi pesquisado na literatura.

Smoking, consumption of alcohol and sedentary life style in population grouping and their relationships with lipemic disorders

The study, part of the project "Atherosclerotic cardiovascular diseases, lipemic disorders, hypertension, obesity and diabetis mellitus in a population of the metropolitan area of the southeastern region of Brazil", had the following objectives: a) the characterization and distribution among typical human socio-economic groupings, of the prevalence of some particular habits which constitute aspects of life-style-the use of tobacco, the use of alcohol and sedentary activity; b) the establishment of the interrelation between the above-mentioned habits and some lipemic disorders. The prevalence of the habits cited behaved in the following manner: the use of tobacco predominated among men, distributed uniformly throughout the social strata; among the women the average percentage of smokers was 18,9%, a significant difference occurring among the highest socio-economic class, where the average was of 40.2%. The sedentary style of life presented high prevalence, among both men and women with exception of the women of the highest socio-economic level and of the skilled working class. The use of alcohol, as one would expect, is a habit basically practised by the men, without any statistically significant differences between classes. For the purpose of establishing associations between these risk fictors and lipemic conditions four situations were chosen, of the following characteristics: 1- total cholesterol > or = 220 mg/dl and triglycerides > or = 150 mg/dl; 2- HDL cholesterol <35 mg/dl for men and <45 mg/dl for women and triglycerides levels > or = 150 mg/dl; 3- HDL cholesterol <35 mg/dl for men and <45 mg/dl for women and triglycerides levels <150 mg/dl; 4- total cholesterol 220 mg/dl with triglycerides levels <150 mg/dl. Six models of multiple (backward) regression were established, with seven independent variables- age, sex, use of tobacco, consumption of alcohol, light physical activity, hypertension and obesity. Significant associations (P<0,05) were revealed with hypercholesterolemia, accompanied by triglyceride levels > or = 150 mg/dl, and the following independent variables: age, use of tobacco and the interactions between obesity and smoking, age and sedentary lifestyle, sex and obesity (R2=22%); the standardized B coefficient showed that the variables with the greatest weight in the forecasting of the variation in the levels of cholesterol were smoking and the interaction between obesity and smoking. The hypercholesterolemia accompanied by triglycerides levels <150 mg/dl showed a positive association between total cholesterol and sex and the interactions obesity/smoking and sex/obesity. As regards HDL cholesterol accompanied by triglyceride/ levels > or = 150 mg/dl was inversely associated with obesity and the interaction smoking/ age and directly with age (R=31%). The standardized B coeffients, indicated that the variables obesity and the interactions smoking/age possessed a weight three times greater than age alone in accounting for the variation in the serum levels of HDL cholesterol. When accompanied by triglycerides <150 mg/dl there was no association between and the independent variables and the set of them presented R equal to 22%. The sum of top, in the population stutied in this project, the component habits of life-style (smoking, alcohol consumption and sedentary activity) which constitute risk factors which determine morbidity from atherosclerotic cardiovascular diseases are be found distributed through all the typical social groupings of this particular form of social organization. On the other hand, the seven independent variables used in the multiple regression models for the explanation of the lipemic conditions considered presented multiple determination coefficients which varied, approximately, between 20% and 30%. Thus it is important that in the genetic epidemiology the study of the morbidities in question be emphasized.