In this paper the performance of classical approaches and GARCH family models are evaluated and compared in estimation one-step-ahead VaR. The classical VaR methodology includes historical simulation (HS), RiskMetrics, and unconditional approaches. The classical VaR methods, the four univariate and two multivariate GARCH models with the Student’s t and the normal error distributions have been applied to 5 stock indices and 4 portfolios to determine the best VaR method. We used four evaluation tests to assess the quality of VaR forecasts: -                     Violation ratio -                     Kupiec’s test -                     Christoffersen’s test -                     Joint test The results point out that GARCH-based models produce far more accurate forecasts for both individual and portfolio VaR. RiskMetrics gives reliable VaR predictions but it is still substantially inferior to GARCH models. The choice of an optimal GARCH model depends on the individual asset, and the best model can be different based on different empirical data.

This paper deals with the applications of symbolic computation of Mathematica 7.0 (Wolfram, 2008) in distribution theory. The purpose of this study is twofold. Firstly, we will implement some functions to extend Mathematica capabilities to handle symbolic computations of the characteristic function for linear combination of independent univariate random variables. These functions utilizes pattern-matching codes that enhance Mathematica's ability to simplify expressions involving the product and summation of algebraic terms. Secondly, characteristic function can be classified into commonly used distributions, including six discrete distributions and seven continuous distributions, via the pattern-matching feature of Mathematica. Finally, several examples will be presented. The examples include calculating limit of characteristic function of linear combinations of independent random variables, and applications of coded functions and illustrate the central limit theorem, the law of large numbers and properties of some distributions.

Most of the time series are constructed by some kind of aggregation and temporal aggregation that can be defined as aggregation over consecutive time periods. Temporal aggregation takes an important role in time series analysis since the choice of time unit clearly influences the type of model and forecast results. A totally different time series model can be fitted on the same variable over different time periods. In this thesis, the effect of temporal aggregation on univariate time series models is studied by considering modeling and forecasting procedure via a simulation study and an application based on a southern oscillation data set. Simulation study shows how the model, mean square forecast error and estimated parameters change when temporally aggregated data is used for different orders of aggregation and sample sizes. Furthermore, the effect of temporal aggregation is also demonstrated through southern oscillation data set for different orders of aggregation. It is observed that the effect of temporal aggregation should be taken into account for data analysis since temporal aggregation can give rise to misleading results and inferences.

In Part 1 of this paper, we adapt Turnbull¡¦s algorithm to estimate the distribution function of univariate interval-censored and truncated failure time data. We also propose four non-parametric tests to test whether two groups of the data come from the same distribution. The powers of proposed test statistics are compared by simulation under different distributions. The proposed tests are then used to analyze an AIDS study. In Part 2, for bivariate interval-censored data, we propose some models of how to generate the data and several methods to measure the correlation between the two variates. We also propose several nonparametric tests to determine whether the two variates are mutually independent or whether they have the same distribution. We demonstrate the performance of these tests by simulation and give an application to AIDS study¡]ACTG 181¡^.

Background: Skin cancer is one of the most preventable forms of cancer yet for certain types of skin cancers, it can be fatal if it goes untreated. While ultraviolet radiation is the main cause of skin cancer, there are several other risk factors, including sunburn history, smoking, environmental pollutants, family history, personal history, and skin color. Practicing sun protection behaviors and receiving regular skin cancer screenings can prevent the cancer from ever developing. This study examines the demographic and socioeconomic status risk factors for skin cancer. Methods: The Health Information National Trends Survey data was used from 2005. Using this secondary dataset, chi-square analysis was performed to determine the prevalence of skin cancer within the demographic categories of age and race/ethnicity as well as socioeconomic status indicators educational attainment, annual household income, employment status, and marital status. Univariate and multivariate analyses were performed to determine the correlations of the variables with skin cancer. A p-value of 0.05 and a 95% confidence interval were maintained throughout the analyses to determine any statistical significance. Results: Of the 3,804 respondents who answered the question related to cancer diagnosis, 226 indicated they had a positive skin cancer diagnosis, which was 5.94% of the total sample. Skin cancer and increased age were consistently associated (χ2 (2) = 171.5, p<.001). The skin cancer peak prevalence was for all those respondents aged 65 and older. Higher educational attainment and higher annual household income were associated with greater likelihood of skin cancer. Conclusions: This study revealed that skin cancer is significantly associated with increased age, higher educational attainment, and higher annual household income. Implementing consistent screening practices and targeted behavioral interventions are important areas for health focus in the future.

O presente estudo tem como objetivo identificar os papéis na compra de interruptores de luz por clientes finais e identificar as influências desses papéis e como ocorrem. O método utilizado foi dividido em duas fases, a primeira com abordagem qualitativa e a segunda com abordagem quantitativa. Inicialmente foram feitas entrevistas em profundidade com consumidores e profissionais da área, com o objetivo de identificar quais os tipos de papéis que ocorrem durante a compra de interruptores e identificar os influenciadores. O segundo passo foi uma survey, sendo entrevistadas 1.013 pessoas divididas nas cinco regiões do país, Região Centro Oeste, Nordeste, Sul, Norte e Sudeste. Foram identificados cinco papéis de compra e sete influenciadores desse processo. Os resultados da pesquisa quantitativa foram analisados com análises univariadas e multivariadas. As análises indicam que os compradores adquirem interruptores para outros usuários, mas a grande maioria deles adquirem o produto para uso próprio e são responsáveis pela compra e pelo pagamento do produto. Os resultados também indicam que as pessoas próximas são os maiores influenciadores. Espera-se que com os resultados obtidos esse trabalho possa contribuir para executivos e empresas do setor elétrico na tomada de decisões. / The present paper has the objective to identify which are the final consumers purchase roles of light switches and identify the influences about this roles and how it occurs. The analysis method was dividing in two steps, the first with a qualitative approach and the second with a quantitative approach. First of all, had been made depth interviews with consumers and professionals from the area, with the objective to identify the influencers. After that, a survey has been made, 1.013 people were interviewed and divided at five regions of the country, Midwest region, Northeast, South, North and Southeast. Were identified five purchase roles and seven influencers of this process. The quantitative research results were analyzed with univariate and multivariate analysis. The analysis indicate that the buyers also buy the light switches for other users, but the majority buy the product for own use and is responsible for the purchase and the product payment. The results also indicate that, in general, close people are the major influencers. With the obtained results throw crossing and the performed analyses, the expectations with this paper is contribute with executives and companies of the area on theirs decision-making.

O presente estudo tem como objetivo identificar os papéis na compra de interruptores de luz por clientes finais e identificar as influências desses papéis e como ocorrem. O método utilizado foi dividido em duas fases, a primeira com abordagem qualitativa e a segunda com abordagem quantitativa. Inicialmente foram feitas entrevistas em profundidade com consumidores e profissionais da área, com o objetivo de identificar quais os tipos de papéis que ocorrem durante a compra de interruptores e identificar os influenciadores. O segundo passo foi uma survey, sendo entrevistadas 1.013 pessoas divididas nas cinco regiões do país, Região Centro Oeste, Nordeste, Sul, Norte e Sudeste. Foram identificados cinco papéis de compra e sete influenciadores desse processo. Os resultados da pesquisa quantitativa foram analisados com análises univariadas e multivariadas. As análises indicam que os compradores adquirem interruptores para outros usuários, mas a grande maioria deles adquirem o produto para uso próprio e são responsáveis pela compra e pelo pagamento do produto. Os resultados também indicam que as pessoas próximas são os maiores influenciadores. Espera-se que com os resultados obtidos esse trabalho possa contribuir para executivos e empresas do setor elétrico na tomada de decisões. / The present paper has the objective to identify which are the final consumers purchase roles of light switches and identify the influences about this roles and how it occurs. The analysis method was dividing in two steps, the first with a qualitative approach and the second with a quantitative approach. First of all, had been made depth interviews with consumers and professionals from the area, with the objective to identify the influencers. After that, a survey has been made, 1.013 people were interviewed and divided at five regions of the country, Midwest region, Northeast, South, North and Southeast. Were identified five purchase roles and seven influencers of this process. The quantitative research results were analyzed with univariate and multivariate analysis. The analysis indicate that the buyers also buy the light switches for other users, but the majority buy the product for own use and is responsible for the purchase and the product payment. The results also indicate that, in general, close people are the major influencers. With the obtained results throw crossing and the performed analyses, the expectations with this paper is contribute with executives and companies of the area on theirs decision-making.

Submitted by (ana.araujo@ufrpe.br) on 2016-05-18T16:23:27Z No. of bitstreams: 1 Adalberto Gomes de Araujo.pdf: 1912427 bytes, checksum: f5afb060ed8c40727f32cece528acc33 (MD5) / Made available in DSpace on 2016-05-18T16:23:27Z (GMT). No. of bitstreams: 1 Adalberto Gomes de Araujo.pdf: 1912427 bytes, checksum: f5afb060ed8c40727f32cece528acc33 (MD5) Previous issue date: 2005-06-15 / The objective of this work was to use multivariate and univariate statistical methods, in the selection of independent variables, in mathematical models, in the construction of volume tables for Leucaena leucocephala, looking for reduction in time and costs, without loss of precision. The data came from an experiment carried out at the Experimental Station of the Institute of Agriculture Research (IPA), Caruaru-PE. It was used 201 trees of leucena that had their volumes (dependent variable) measured by the method of Smalian, and 20 variables independent measured in the same trees. For the selection of the independent variables the following methods were used: Principal Components, Cluster Analysis, Maximum and Minimum R2, Stepwise, Forward, Backward and Criterion of Akaike. In the general, the univariate and multivariate methods used in the selection of independent variables for volume models, showed similar responses, even though they had different structures in relation to the independent variables, since the number of those variables is high. Besides the applied statistical tests, the researcher'sjudgment about the relevance of the selected independent variables in the final equations has a great importance, mainly, in the reduction of costs and sampling errors. / O objetivo deste trabalho foi utilizar métodos estatísticos univariados e multivariados na seleção de variáveis independentes, em modelos matemáticos, para a construção de tabelas de volumes para Leucaena leucocephala, visando reduzir tempo e custos sem perda de precisão. Os dados foram provenientes de um experimento conduzido na Estação Experimental da Empresa Pernambucana de Pesquisa Agropecuária (IPA), Caruaru-PE. Foram utilizadas 201 árvores de leucena, que tiveram seus volumes cubados pelo método de Smalian, e 20 variáveis independentes medidas nas mesmas árvores. Para a seleção das variáveis independentes foram utilizados os seguintes métodos: Componentes Principais, Análise de Agrupamento, R2 Máximo e Mínimo, Stepwise, Forward, Backward e Critério de Akaike. No geral, os métodos univariados e multivariados empregados no descarte de variáveis independentes para modelos volumétricos, conduzem a respostas semelhantes, mesmo que possuam estruturas diferentes em relação às variáveis independentes, desde que o número dessas variáveis seja elevado. Além dos testes estatísticos aplicados, o julgamento do pesquisador sobre a relevância das variáveis selecionadas nas equações resultantes, é de grande importância, principalmente, na redução de custos e do erro de amostragem

This thesis consists of three studies which cover topics in the trading volume-market return volatility linkage, stock market return-aggregate mutual fund flow relationship as well as market return volatility-aggregate mutual fund flow interaction. Chapter 2 investigates the issue of volume-volatility linkage in the US market for the period 1990-2012 (S&P 500) and 1992-2012 (Dow Jones). We construct four sub-samples depending on three different structural points (the Asian Financial Crisis, the Dot-Com Bubble and the 2007 Financial Crisis). By employing univariate and bivariate GARCH processes, we find positive (negative) bidirectional linkages between these two aforementioned variables in various cases of the estimation, while a mixed one is observed in the remainder of these cases. Chapter 3 examines the issue of temporal ordering of the range-based stock market return (S&P 500 index) and aggregate mutual fund flow in the U.S. market for the period 1998-2012. We construct nine sub-samples represented by three fundamental cases of the whole data set. In addition, we take into consideration three essential indicators when splitting the whole data set, which are the 2000 Dot-Com Bubble, the 2007 Financial Crisis as well as the 2009 European Sovereign Debt Crisis. We examine the dynamics of the return-flow interaction by employing bivariate VAR model with various specifications of GARCH approach. Our principal findings display a bidirectional mixed feedback between stock market return and aggregate mutual fund flow for the majority of the sub-samples obtained. Nevertheless, we provide limited evidence of a positive bi-directional causality between return and flow. Chapter 4 investigates the dynamic relation between S&P 500 return volatility and U.S. aggregate mutual fund flow for the period spanning between 1998 and 2012. We assess the dynamics of the volatility-flow linkage by employing a bivariate VAR model with the GARCH approach which allows for long memory in the mean and the variance equations. In addition to the sub-samples obtained in chapter 3, we generate two measurements of volatility. Our baseline results indicate a variety of bidirectional mixed causalities between market return volatility and aggregate mutual fund flow in several sub-samples. In addition, we observe a negative/positive bi-directional relationship between volatility and flow in the rest of the sub-periods. Summarizing, a range of our findings are in line with the empirical underpinnings that most likely predict a significant linkage between the aforementioned variables. Finally, most of the bidirectional effects are found to be quite robust to the dynamics of the various GARCH processes employed in this thesis.

The paper analyses the degree of output persistence in GDP in order to empirically discriminate between the Solow growth model, the perfect competition endogenous growth model, the imperfect competition endogenous growth model, and the subcase of a multiple equilibria model of endogenous growth for the case of Austria. We find that a temporary shock in the growth rate of output induces a permanent and larger effect on the level of GDP. This leads us to refute the Solow growth model and the perfect competition model. We find strong empirical support for the imperfect competition growth model, but cannot fully rule out the possibility of multiple equilibria growth rates. / Series: Department of Economics Working Paper Series