Análise dos riscos sistemáticos e idiossincráticos, representados pelo CAPM, para portfólios de diferentes setores em condições econômicas distintas

Esse estudo busca analisar os impactos causados pelo Ciclo Monetário, o Ciclo Econômico, o Nível da Indústria e a Condição do Mercado de Ações nas variáveis do CAPM para portfólios de ações de diferentes setores da indústria no Brasil. O banco de dados utilizado compreende séries temporais mensais, do retorno de ações de 17 setores da economia, no período de Janeiro de 2008 à Dezembro de 2014. Foi observado que existem relações estatisticamente relevantes entre variáveis macroeconômicas e o excesso de retorno dos portfólios de ações analisados. Além disso, foi possível notar que essas relações tem efeitos distintos sobre os riscos sistemáticos e idiossincráticos dos portfólios. A maior parte dos resultados obtidos não se mostraram estatisticamente relevantes, o que sugere que existem outras variáveis explicativas que se relacionam com as variáveis dependentes de forma mais robusta, assim como já apontado pela literatura existente, no caso do Brasil. No entanto, foi possível observar que há efeitos indiretos das variáveis macroeconômicas sobre o retorno dos ativos através do canal de retorno do mercado.

Portfólios ponderados pelo risco : uma abordagem para a alocação de carteiras

Esse estudo busca analisar o desempenho de um portfólio de investimento constituído através da contribuição equânime do risco de seus ativos para o risco total do portfólio, ou seja, a chamada estratégia de risk parity, utilizando uma amostra composta de dados diários de cotações de fechamento de 27 ações pertencentes ao mercado brasileiro de ações entre janeiro de 2004 e dezembro de 2014. O estudo compara tal portfólio com outros três portfólios constituídos através de abordagens tradicionais: o portfólio baseado na estratégia por média-variância, o portfólio baseado na estratégia por mínima variância e o portfólio igualmente ponderado, também conhecido como portfólio ingênuo (naive). Ao mesmo tempo, o estudo analisa o desempenho do portfólio comparado a dois indicadores importantes do mercado de capitais brasileiro: o IBOVESPA e o CDI. Foram construídas séries temporais com rebalanceamento trimestral dos portfólios para o desenvolvimento do estudo, como efetuado em Maillard et al. (2010). Os resultados demonstram que o portfólio constituído através da contribuição equânime ao risco não apresentou desempenho superior quando comparado aos portfólios por média-variância e por mínima variância, em termos de retorno e risco. Por outro lado, quando comparado ao portfólio ingênuo, ao IBOVESPA e ao CDI, o desempenho obtido foi superior, tendo também apresentado resultados similares aos exibidos em Maillard et al. (2010). O estudo conclui que a construção de carteiras por risk parity é uma alternativa viável para a composição de carteiras que buscam estabilidade na alocação de risco e nos pesos dos ativos no longo prazo, diante de diferentes cenários macroeconômicos.

Indústria de máquinas agrícolas no Brasil: um modelo para estimação da demanda de tratores para o triênio 2016 – 2018

O objetivo desta dissertação foi estimar a demanda de tratores agrícolas para o mercado brasileiro no triênio 2016-2018, utilizando-se para isto de técnicas de econometria de séries temporais, neste caso, modelos univariados da classe ARIMA e SARIMA e ou multivariados SARIMAX. Justifica-se esta pesquisa quando se observa a indústria de máquinas agrícolas no Brasil, dados os ciclos econômicos e outros fatores exógenos aos fundamentos econômicos da demanda, onde esta enfrenta muitos desafios. Dentre estes, a estimação de demanda se destaca, pois exerce forte impacto, por exemplo, no planejamento e custo de produção de curto e médio prazo, níveis de inventários, na relação com fornecedores de materiais e de mão de obra local, e por consequência na geração de valor para o acionista. Durante a fase de revisão bibliográfica foram encontrados vários trabalhos científicos que abordam o agronegócio e suas diversas áreas de atuação, porém, não foram encontrados trabalhos científicos publicados no Brasil que abordassem a previsão da demanda de tratores agrícolas no Brasil, o que serviu de motivação para agregar conhecimento à academia e valor ao mercado através deste. Concluiu-se, após testes realizados com diversos modelos que estão dispostos no texto e apêndices, que o modelo univariado SARIMA (15,1,1) (1,1,1) cumpriu as premissas estabelecidas nos objetivos específicos para escolha do modelo que melhor se ajusta aos dados, e foi escolhido então, como o modelo para estimação da demanda de tratores agrícolas no Brasil. Os resultados desta pesquisa apontam para uma demanda de tratores agrícolas no Brasil oscilando entre 46.000 e 49.000 unidades ano entre os anos de 2016 e 2018.

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 agrupamentos dos dados de DFA oriundos de perfis elétricos de indução de poços de petróleo

The main objective of this study is to apply recently developed methods of physical-statistic to time series analysis, particularly in electrical induction s profiles of oil wells data, to study the petrophysical similarity of those wells in a spatial distribution. For this, we used the DFA method in order to know if we can or not use this technique to characterize spatially the fields. After obtain the DFA values for all wells, we applied clustering analysis. To do these tests we used the non-hierarchical method called K-means. Usually based on the Euclidean distance, the K-means consists in dividing the elements of a data matrix N in k groups, so that the similarities among elements belonging to different groups are the smallest possible. In order to test if a dataset generated by the K-means method or randomly generated datasets form spatial patterns, we created the parameter Ω (index of neighborhood). High values of Ω reveals more aggregated data and low values of Ω show scattered data or data without spatial correlation. Thus we concluded that data from the DFA of 54 wells are grouped and can be used to characterize spatial fields. Applying contour level technique we confirm the results obtained by the K-means, confirming that DFA is effective to perform spatial analysis

Análise de DFA e de agrupamento do perfil de densidade de poços de petróleo

In recent years, the DFA introduced by Peng, was established as an important tool capable of detecting long-range autocorrelation in time series with non-stationary. This technique has been successfully applied to various areas such as: Econophysics, Biophysics, Medicine, Physics and Climatology. In this study, we used the DFA technique to obtain the Hurst exponent (H) of the profile of electric density profile (RHOB) of 53 wells resulting from the Field School of Namorados. In this work we want to know if we can or not use H to spatially characterize the spatial data field. Two cases arise: In the first a set of H reflects the local geology, with wells that are geographically closer showing similar H, and then one can use H in geostatistical procedures. In the second case each well has its proper H and the information of the well are uncorrelated, the profiles show only random fluctuations in H that do not show any spatial structure. Cluster analysis is a method widely used in carrying out statistical analysis. In this work we use the non-hierarchy method of k-means. In order to verify whether a set of data generated by the k-means method shows spatial patterns, we create the parameter Ω (index of neighborhood). High Ω shows more aggregated data, low Ω indicates dispersed or data without spatial correlation. With help of this index and the method of Monte Carlo. Using Ω index we verify that random cluster data shows a distribution of Ω that is lower than actual cluster Ω. Thus we conclude that the data of H obtained in 53 wells are grouped and can be used to characterize space patterns. The analysis of curves level confirmed the results of the k-means

Modelagem estocástica do índice de radiação ultravioleta na costa leste do nordeste do Brasil

The increase in ultraviolet radiation (UV) at surface, the high incidence of non-melanoma skin cancer (NMSC) in coast of Northeast of Brazil (NEB) and reduction of total ozone were the motivation for the present study. The overall objective was to identify and understand the variability of UV or Index Ultraviolet Radiation (UV Index) in the capitals of the east coast of the NEB and adjust stochastic models to time series of UV index aiming make predictions (interpolations) and forecasts / projections (extrapolations) followed by trend analysis. The methodology consisted of applying multivariate analysis (principal component analysis and cluster analysis), Predictive Mean Matching method for filling gaps in the data, autoregressive distributed lag (ADL) and Mann-Kendal. The modeling via the ADL consisted of parameter estimation, diagnostics, residuals analysis and evaluation of the quality of the predictions and forecasts via mean squared error and Pearson correlation coefficient. The research results indicated that the annual variability of UV in the capital of Rio Grande do Norte (Natal) has a feature in the months of September and October that consisting of a stabilization / reduction of UV index because of the greater annual concentration total ozone. The increased amount of aerosol during this period contributes in lesser intensity for this event. The increased amount of aerosol during this period contributes in lesser intensity for this event. The application of cluster analysis on the east coast of the NEB showed that this event also occurs in the capitals of Paraiba (João Pessoa) and Pernambuco (Recife). Extreme events of UV in NEB were analyzed from the city of Natal and were associated with absence of cloud cover and levels below the annual average of total ozone and did not occurring in the entire region because of the uneven spatial distribution of these variables. The ADL (4, 1) model, adjusted with data of the UV index and total ozone to period 2001-2012 made a the projection / extrapolation for the next 30 years (2013-2043) indicating in end of that period an increase to the UV index of one unit (approximately), case total ozone maintain the downward trend observed in study period

Dunas costeiras de Jenipabu: Status de conservação e diretrizes para restauração da vegetação

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Crescimento econômico e restrição externa: evidências empíricas na economia brasileira (1991-2010)

This study aims to investigate the influence of the balance of payments constrained on economic growth in Brazil from 1991 to 2010. With this order, are shown some of the Keynesian balance of payments constrained growth models, inspired by Thirlwall (1979) and Kaldor (1970), which are supported by important points in common, such as adherence to the principle of effective demand. Given that within this theoretical perspective, there is no consensus about the best model to explain the growth rate allowed by the balance of payments constraint, the results are presented by the representative of the empirical literature that addresses the topic, which are necessary for understand the Brazilian case. From the estimation of the income elasticity of imports (0.85) via autoregressive vectors with error correction (VEC), it was calculated five growth rates of income, as predicted by the models of Thirlwall (1979), Thirlwall and Hussain (1982), Moreno-Brid (1998, 2003) and Lourenço et al. (2011) and compared with the actual growth rate. The empirical analysis has shown that: it can not reject the presence of external constraint in the Brazilian economy, there is a strong similarity in growth rates provided by different modeling suggest that growth with external constraint. In addition, when using data in quarterly for the period after 1990 there are no factors that could cause instability in the parameters of the import function (income elasticity and price elasticity of imports) within the period, which indicates that the structural break widely associated with the year 1994 was not confirmed by this study

Propagação de danos no modelo de ising em redes de bravais e em fractais

In this work we have studied, by Monte Carlo computer simulation, several properties that characterize the damage spreading in the Ising model, defined in Bravais lattices (the square and the triangular lattices) and in the Sierpinski Gasket. First, we investigated the antiferromagnetic model in the triangular lattice with uniform magnetic field, by Glauber dynamics; The chaotic-frozen critical frontier that we obtained coincides , within error bars, with the paramegnetic-ferromagnetic frontier of the static transition. Using heat-bath dynamics, we have studied the ferromagnetic model in the Sierpinski Gasket: We have shown that there are two times that characterize the relaxation of the damage: One of them satisfy the generalized scaling theory proposed by Henley (critical exponent z~A/T for low temperatures). On the other hand, the other time does not obey any of the known scaling theories. Finally, we have used methods of time series analysis to study in Glauber dynamics, the damage in the ferromagnetic Ising model on a square lattice. We have obtained a Hurst exponent with value 0.5 in high temperatures and that grows to 1, close to the temperature TD, that separates the chaotic and the frozen phases

Em busca de um novo indicador Espectroscópico do período de rotação das Estrelas do tipo solar

The study of sunspots consistently contributed to a better understanding of magnetic phenomena of the Sun, as its activity. It was found with the dynamics of sunspots that the Sun has a rotation period of twenty-seven days around your axis. With the help of Project Sun-As-A-Star that solar spectra obtained for more than thirty years we observed oscillations of both the depth of the spectral line and its equivalent width, and analysis of the return information about the characteristics of solar magnetism. It also aims to find patterns of solar magnetic activity cycle and the average period of rotation of the Sun will indicate the spectral lines that are sensitive to magnetic activity and which are not. Sensitive lines how Ti II 5381.0 Å stands as the best indicator of the solar rotation period and also shows different periods of rotation cycles of minimum and maximum magnetic activity. It is the first time we observe clearly distinct rotation periods in the different cycles. The analysis also shows that Ca II 8542.1 Å and HI 6562.0 Å indicate the cycle of magnetic activity of eleven years. Some spectral lines no indicated connection with solar activity, this result can help us search for programs planets using spectroscopic models. Data analysis was performed using the Lomb-Scargle method that makes the time series analysis for unequally spaced data. Observe different rotation periods in the cycles of magnetic activity accounts for a discussion has been debated for many decades. We verified that spectroscopy can also specify the period of stellar rotation, thus being able to generalize the method to other stars

Rotação diferencial em estrelas do tipo solar

Stellar differential rotation is an important key to understand hydromagnetic stellar dynamos, instabilities, and transport processes in stellar interiors as well as for a better treatment of tides in close binary and star-planet systems. The space-borne high-precision photometry with MOST, CoRoT, and Kepler has provided large and homogeneous datasets. This allows, for the first time, the study of differential rotation statistically robust samples covering almost all stages of stellar evolution. In this sense, we introduce a method to measure a lower limit to the amplitude of surface differential rotation from high-precision evenly sampled photometric time series such as those obtained by space-borne telescopes. It is designed for application to main-sequence late-type stars whose optical flux modulation is dominated by starspots. An autocorrelation of the time series is used to select stars that allow an accurate determination of spot rotation periods. A simple two-spot model is applied together with a Bayesian Information Criterion to preliminarily select intervals of the time series showing evidence of differential rotation with starspots of almost constant area. Finally, the significance of the differential rotation detection and a measurement of its amplitude and uncertainty are obtained by an a posteriori Bayesian analysis based on a Monte Carlo Markov Chain (hereafter MCMC) approach. We apply our method to the Sun and eight other stars for which previous spot modelling has been performed to compare our results with previous ones. The selected stars are of spectral type F, G and K. Among the main results of this work, We find that autocorrelation is a simple method for selecting stars with a coherent rotational signal that is a prerequisite to a successful measurement of differential rotation through spot modelling. For a proper MCMC analysis, it is necessary to take into account the strong correlations among different parameters that exists in spot modelling. For the planethosting star Kepler-30, we derive a lower limit to the relative amplitude of the differential rotation. We confirm that the Sun as a star in the optical passband is not suitable for a measurement of the differential rotation owing to the rapid evolution of its photospheric active regions. In general, our method performs well in comparison with more sophisticated procedures used until now in the study of stellar differential rotation

DFA e análise de agrupamento aplicadas a perfis de porosidade neutrônico em poços de petróleo

Peng was the first to work with the Technical DFA (Detrended Fluctuation Analysis), a tool capable of detecting auto-long-range correlation in time series with non-stationary. In this study, the technique of DFA is used to obtain the Hurst exponent (H) profile of the electric neutron porosity of the 52 oil wells in Namorado Field, located in the Campos Basin -Brazil. The purpose is to know if the Hurst exponent can be used to characterize spatial distribution of wells. Thus, we verify that the wells that have close values of H are spatially close together. In this work we used the method of hierarchical clustering and non-hierarchical clustering method (the k-mean method). Then compare the two methods to see which of the two provides the best result. From this, was the parameter � (index neighborhood) which checks whether a data set generated by the k- average method, or at random, so in fact spatial patterns. High values of � indicate that the data are aggregated, while low values of � indicate that the data are scattered (no spatial correlation). Using the Monte Carlo method showed that combined data show a random distribution of � below the empirical value. So the empirical evidence of H obtained from 52 wells are grouped geographically. By passing the data of standard curves with the results obtained by the k-mean, confirming that it is effective to correlate well in spatial distribution

Estudo de Fractalidade e Evolução Dinâmica de Sistemas Complexos

In this work, the study of some complex systems is done with use of two distinct procedures. In the first part, we have studied the usage of Wavelet transform on analysis and characterization of (multi)fractal time series. We have test the reliability of Wavelet Transform Modulus Maxima method (WTMM) in respect to the multifractal formalism, trough the calculation of the singularity spectrum of time series whose fractality is well known a priori. Next, we have use the Wavelet Transform Modulus Maxima method to study the fractality of lungs crackles sounds, a biological time series. Since the crackles sounds are due to the opening of a pulmonary airway bronchi, bronchioles and alveoli which was initially closed, we can get information on the phenomenon of the airway opening cascade of the whole lung. Once this phenomenon is associated with the pulmonar tree architecture, which displays fractal geometry, the analysis and fractal characterization of this noise may provide us with important parameters for comparison between healthy lungs and those affected by disorders that affect the geometry of the tree lung, such as the obstructive and parenchymal degenerative diseases, which occurs, for example, in pulmonary emphysema. In the second part, we study a site percolation model for square lattices, where the percolating cluster grows governed by a control rule, corresponding to a method of automatic search. In this model of percolation, which have characteristics of self-organized criticality, the method does not use the automated search on Leaths algorithm. It uses the following control rule: pt+1 = pt + k(Rc − Rt), where p is the probability of percolation, k is a kinetic parameter where 0 < k < 1 and R is the fraction of percolating finite square lattices with side L, LxL. This rule provides a time series corresponding to the dynamical evolution of the system, in particular the likelihood of percolation p. We proceed an analysis of scaling of the signal obtained in this way. The model used here enables the study of the automatic search method used for site percolation in square lattices, evaluating the dynamics of their parameters when the system goes to the critical point. It shows that the scaling of , the time elapsed until the system reaches the critical point, and tcor, the time required for the system loses its correlations, are both inversely proportional to k, the kinetic parameter of the control rule. We verify yet that the system has two different time scales after: one in which the system shows noise of type 1 f , indicating to be strongly correlated. Another in which it shows white noise, indicating that the correlation is lost. For large intervals of time the dynamics of the system shows ergodicity

Temporal dynamics of stomatal conductance of plants under water deficit: can homeostasis be improved by more complex dynamics?

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)