No description available.

A mensuração do risco de um investimento é uma das mais importantes etapas para a tomada de decisão de um investidor. Em virtude disto, este trabalho comparou três métodos de estimação (tradicional, através da analise univariada dos retornos do portfólio; cópulas estáticas e cópulas dinâmicas) de duas medidas de risco: Value at Risk (VaR) e Expected Shortfall (ES). Tais medidas foram estimadas para o portfólio composto pelos índices BOVESPA e S&P500 no período de janeiro de 1998 a maio de 2012. Para as modelagens univariadas, incluindo as marginais das cópulas, foram comparados os modelos GARCH e EGARCH. Para cada modelo univariado, utilizamos as cópulas Normal, t-Student, Gumbel rotacionada e Joe-Clayton simetrizada, com isso totalizando 36 modelos comparados. Nas comparações do VaR e ES foram utilizados, respectivamente, o teste de Chritoffersen e o teste de Mcneil e Frey. Os principais resultados encontrados foram a superioridade de modelos que supõem erros com distribuição t-Student, assim como a identificação de mudança no comportamento dos parâmetros dinâmicos nos períodos de crise. / Measuring the risk of an investment is one of the most important steps in an investor's decision-making. With this in light, this study compared three estimation methods (traditional; by univariate analysis of portfolio returns; dynamic copulas and static copulas), of two risk measurements: Value at Risk (VaR) and Expected Shortfall (ES). Such estimated measures are performed for a portfolio composed by the BOVESPA and S&P500 indexes, ranging from January 1998 to May 2012. For univariate modelling (including copulas marginals), the GARCH and EGARCH models were compared,. Regarding copulas, we use Normal, t-Student, rotated Gumbel and symmetric Joe-Clayton, leading to a total of 36 models being compared. For the comparison of VaR and ES were used, respectively, the Christoffersen test, and the Mcneil and Frey test. The main results found were the superiority of models assuming the t-Student distributed errors, as well as the identification of a change in the behaviour of dynamic parameters in periods of crisis.

A mensuração do risco de um investimento é uma das mais importantes etapas para a tomada de decisão de um investidor. Em virtude disto, este trabalho comparou três métodos de estimação (tradicional, através da analise univariada dos retornos do portfólio; cópulas estáticas e cópulas dinâmicas) de duas medidas de risco: Value at Risk (VaR) e Expected Shortfall (ES). Tais medidas foram estimadas para o portfólio composto pelos índices BOVESPA e S&P500 no período de janeiro de 1998 a maio de 2012. Para as modelagens univariadas, incluindo as marginais das cópulas, foram comparados os modelos GARCH e EGARCH. Para cada modelo univariado, utilizamos as cópulas Normal, t-Student, Gumbel rotacionada e Joe-Clayton simetrizada, com isso totalizando 36 modelos comparados. Nas comparações do VaR e ES foram utilizados, respectivamente, o teste de Chritoffersen e o teste de Mcneil e Frey. Os principais resultados encontrados foram a superioridade de modelos que supõem erros com distribuição t-Student, assim como a identificação de mudança no comportamento dos parâmetros dinâmicos nos períodos de crise. / Measuring the risk of an investment is one of the most important steps in an investor's decision-making. With this in light, this study compared three estimation methods (traditional; by univariate analysis of portfolio returns; dynamic copulas and static copulas), of two risk measurements: Value at Risk (VaR) and Expected Shortfall (ES). Such estimated measures are performed for a portfolio composed by the BOVESPA and S&P500 indexes, ranging from January 1998 to May 2012. For univariate modelling (including copulas marginals), the GARCH and EGARCH models were compared,. Regarding copulas, we use Normal, t-Student, rotated Gumbel and symmetric Joe-Clayton, leading to a total of 36 models being compared. For the comparison of VaR and ES were used, respectively, the Christoffersen test, and the Mcneil and Frey test. The main results found were the superiority of models assuming the t-Student distributed errors, as well as the identification of a change in the behaviour of dynamic parameters in periods of crisis.

A mensuração do risco de um investimento é uma das mais importantes etapas para a tomada de decisão de um investidor. Em virtude disto, este trabalho comparou três métodos de estimação (tradicional, através da analise univariada dos retornos do portfólio; cópulas estáticas e cópulas dinâmicas) de duas medidas de risco: Value at Risk (VaR) e Expected Shortfall (ES). Tais medidas foram estimadas para o portfólio composto pelos índices BOVESPA e S&P500 no período de janeiro de 1998 a maio de 2012. Para as modelagens univariadas, incluindo as marginais das cópulas, foram comparados os modelos GARCH e EGARCH. Para cada modelo univariado, utilizamos as cópulas Normal, t-Student, Gumbel rotacionada e Joe-Clayton simetrizada, com isso totalizando 36 modelos comparados. Nas comparações do VaR e ES foram utilizados, respectivamente, o teste de Chritoffersen e o teste de Mcneil e Frey. Os principais resultados encontrados foram a superioridade de modelos que supõem erros com distribuição t-Student, assim como a identificação de mudança no comportamento dos parâmetros dinâmicos nos períodos de crise. / Measuring the risk of an investment is one of the most important steps in an investor's decision-making. With this in light, this study compared three estimation methods (traditional; by univariate analysis of portfolio returns; dynamic copulas and static copulas), of two risk measurements: Value at Risk (VaR) and Expected Shortfall (ES). Such estimated measures are performed for a portfolio composed by the BOVESPA and S&P500 indexes, ranging from January 1998 to May 2012. For univariate modelling (including copulas marginals), the GARCH and EGARCH models were compared,. Regarding copulas, we use Normal, t-Student, rotated Gumbel and symmetric Joe-Clayton, leading to a total of 36 models being compared. For the comparison of VaR and ES were used, respectively, the Christoffersen test, and the Mcneil and Frey test. The main results found were the superiority of models assuming the t-Student distributed errors, as well as the identification of a change in the behaviour of dynamic parameters in periods of crisis.

No description available.

published_or_final_version / abstract / Physics / Doctoral / Doctor of Philosophy

The focus of my research has been computationally efficient means of computing measures of risk for portfolios of nonlinear financial instruments when the risk factors might be possibly non-Gaussian. In particular, the measures of risk chosen have been Value-at-Risk (VaR) and conditional Value-at-Risk (CVaR). I have studied the problem of computation of risk in two types of financial portfolios with nonlinear instruments which depend on possibly non-Gaussian risk factors: 1. Portfolios of European stock options when the stock return distribution may not be Gaussian; 2. Portfolios of sovereign bonds (which are nonlinear in the underlying risk factor, i.e. the short rate) when the risk factor may or may not be Gaussian. Addressing both these problems need a wide array of mathematical tools both from the field of applied statistics (Delta-Gamma-Normal models, characteristic function inversion, probability conserving transformation) and systems theory (Vasicek stochastic differential equation model, Kalman filter). A new heuristic is proposed for addressing the first problem, while an empirical study is presented to support the use of filter-based models for addressing the second problem. In addition to presenting a discussion of these underlying mathematical tools, the dissertation also presents comprehensive numerical experiments in both cases, with simulated as well as real financial market data. Backtesting is used to confirm the validity of the proposed methods.

This mixed methods study sought to examine student perceptions of the impact of an alternative intervention program (AIP), and provide a framework meant to inspire programs in other locations. Focusing on attendance, discipline, and academic achievement data, this study examined what factors motivate successful alternative education students to succeed upon their return to the comprehensive setting, and identify support factors that foster resiliency. Qualitative data were collected through three focus groups of students who were either new to the program, enrolled in the program for at least a nine-week period, and students who successfully completed a nine-week placement. Six adult students who completed the program and received a high school diploma were in-depth interview participants. Quantitative data were collected using student records. Results indicated differences in the students’ perception of grades earned and the actual grades received. Students were able to maintain their attendance, grades, and discipline during the alternative program enrollment, but scored lower in English and Mathematics after leaving the program than they did prior to attending the program. The fast pace and rigor of a standards-based curriculum in a comprehensive setting proved challenging for students in need of a caring, nurturing environment that offered individualized instruction. Students overwhelmingly attribute their success in the alternative program to a caring staff, and flexible scheduling within a structured environment. This study revealed the need for a more structured process to transition students from the alternative to comprehensive settings. Students could literally be in the alternative setting today and in the comprehensive setting tomorrow, with very little support or guidance. This led to repeated disciplinary offenses and for some students, their return to the alternative setting.

The study surveyed a sample of K-12 teachers who had used assistive technology (AT) in the classroom to determine answers to five research questions. These were, (1) why the teachers adopted AT, (2) their attitudes and perceptions about its value, (3) challenges they have experienced in adopting AT, (4) whether they have discontinued or decreased use of AT, and, if so, (5) the factors that led to this result. The study used both quantitative and qualitative methods. For the quantitative aspect, an online survey instrument was developed to answer five research questions. Participants were teachers who had used AT in the classroom and came from 19 Georgia school districts whose superintendents granted permission for them to participate and whose assistant technology coordinators agreed to inform teachers in their districts' schools of the study. A total of 174 teachers completed the online survey. Of these, 52 agreed to be interviewed by telephone by the researcher, and 10 of those were randomly selected to be interviewed. Telephone interviews were audio recorded with the interviewee's permission, then transcribed by the researcher. Analysis of quantitative results included factor analysis of replies to Likert-scaled items, compilation of frequency of responses, and determination of means for Likert items. For interview responses, qualitative methods were used to determine any themes in participants' replies. It was found that (1) the most prevalent reason teachers initially used AT is that they perceived that the technology has value for their students, (2) the teachers had a mostly positive attitude toward the value of AT, (3) most of the teachers reported needing more training in AT, (4) almost half felt that time constraints affected their use of AT, (5) about one-third of online responders and 9 of 10 interviewees agreed that technical problems affected their use of AT, and (6) less than half of online participants perceived that they had adequate AT support. It was also found that most of the teachers had neither decreased nor discontinued use of AT during the 2008-2009 school year. Reasons cited by those who had decreased or discontinued use included time constraints, technical problems, lack of training, and lack of support.

La Rue House is a collection of short fictional stories set in and around a homeless shelter for adolescents.