The face of America's schools is changing. An increasingly diverse and challenging population of students blends assorted ethnic backgrounds, varied approaches to learning, and different socio-economic backgrounds into one student body. Faced with the realities of environmental and educational stressors, some students may find the educational milieu difficult. One particular group of students who may fit this category are those placed at-risk of school failure. The No Child Left Behind Act of 2001, the latest government reform in education to affect our nation's schools, created additional pressures on educators and students alike. In this climate of increased testing and accountability, educators must be trained to work with today's students. Staff development is one method of assisting educators to become knowledgeable about the needs of students placed at-risk of school failure in the current reform era. Guiding issues for this study were the nature of staff development with regard to students placed at-risk of school failure in an era of educational reform as viewed through staff development. Guiding questions were how many staff development courses were aimed at meeting the needs of students placed at-risk of school failure and how much of this training was done relative to content-based staff development. Staff development offices were chosen because they are the conduits through which school district employees often gain substantial knowledge and training, and because of their importance in the field of training and professional development. The method used in this study was a content analysis of staff development course documents from the 100 largest school districts in the United States. The intent of this quantitative content analysis was to explore how school district staff development offices approach the task of educating their employees to work with a complex, diverse school population, often seen as at-risk of school failure. This study was important to the field of educational leadership because it provided essential and useful information, both for educators working with an increasingly diverse student population, especially students at-risk of school failure, and for district leaders whose task it is to provide staff development for those who teach our children. Quantitative analyses of the staff development course documents showed no relationship between school district size and number of courses with coded words; the total number of courses a school district offered was, however, a predictor for the total number of targeted courses. All but one of the school districts sampled had at least one course with a coded word. A qualitative analysis of the coding of the categories and indicators revealed that the coded words were applied broadly to the themes and patterns that emerged. School district staff development offices continue to play a positive role in the training of educators striving to meet the needs of a diverse student body in the 21st century. / Ed. D.

This was a case study analysis of the Opportunity School, an alternative public education program in Danville,Virginia that serves students who are considered academically at-risk, grades six through twelve. A case study analysis of the Opportunity School was implemented to provide specific information regarding the overall effectiveness of the program. In addition, the analysis attempted to: reflect on the worthiness of the program since its inception in 1993; assess the program's strengths and weakness; ascertain students' level of satifaction; address areas that needed further expansion and suggest recommendations, based on indicators of effectiveness cited in the literature. The case study analysis, which was qualitative and quantitative was the methodology implemented in this research. The case records included, focus group sessions, interviews, student questionnaire, typology--using Kellmayer's indicators, and analysis of students' records. The sample population for this study was students who participated in the Opportunity School's program in 1996-97. Sixteen students participated in three focus groups and 41 students responded to a questionnaire designed to determine their satisfaction with the Opportunity School. In addition, school records of 153 students who participated in the program for a least one year between 1993-1997 were analyzed using: paired t-Tests, correlation coefficients, standard deviations, means and cross tabulations. Analysis of student data revealed the Opportunity School's program may have contributed to the positive change in students' academics performance and disciplinary behavior. Other factors that may have contributed to this change are maturation of students and repetitiveness of the Literacy Passport tests, which was used as a barometer to gauge academic performance. Collectively the Opportunity School's program has provided at-risk students with a second chance to continue their education. However, to more effectively serve students, there are areas that should be strengthen and expanded. Some of these areas included: use and integration of technology in the classroom, more variety in curriculum courses, adding a vocational education component, flexibility around the time of day students attend school and a comprehensive counseling program. The Opportunity School in Danville, Virginia should continue serving students who are considered at-risk of dropping out of school. Students in the school perceived the program as meeting their needs, and were very satisfied with the program and the school's staff. However, if alternative program for at-risk students are to have have real benefits, merely labeling them alternative will obviously not do. A program design must incorporate quantitative attributes. To further assess the effectiveness of alternative education programs for at-risk populations more longitudinal studies are needed. / Ed. D.

This study examines a collaborative creation and application of an evaluation process for a teen shelter. An independent researcher collaborated with the key administrators of a teen shelter to create an agency-specific evaluation process that gathered both quantitative and qualitative data from three separate participant groups: teen clients of the shelter, their parents, and the staff who work at the shelter. Results of the creation process indicate that collaborating with key administrators is imperative when developing agency-specific evaluations with the goal of program improvement. Application results indicate that the clients and staff at this particular shelter felt the program was very helpful. Responses included participants' ideas as to what was helpful and what aspects of the program made the experience beneficial. Participants offered positive feedback about the effective aspects of the program, as well as suggestions for improving some weaker aspects of the program. Shelter administrators were pleased with the evaluation process and results and were enthusiastic about applying the results toward program improvement. / Master of Science

The widespread effects of student failure and dropout have social, judicial, and economic implications. This study addressed factors that can affect students academic identification, an element that can influence dropout among U.S. high school students identified as at-risk. Research indicates that student motivation and academic identification may be linked to improvements in students academic achievement and reductions in dropout rates. The purpose of this quantitative investigation was to address high dropout rates among at-risk, high school students by exploring the extent to which students motivational beliefs in school predicted their academic identification and achievement. Specifically, I explored the extent to which the MUSICSM Model of Academic Motivation Inventory (MUSIC Inventory) produced valid scores among at-risk high school students, and the extent to which students motivational beliefs about school predicted their academic identification and achievement. This quantitative study utilized structural equation modeling (SEM) and involved a sample of 100 at-risk students from an alternative high school in the Mid-Atlantic United States. Data were collected via paper surveys, which I administered to students during October, 2015. All survey data were entered into SPSS 23 for analysis. Results indicated that Cronbach's alpha coefficients were low for all MUSIC Model components except for care, which demonstrated modest reliability. Data analysis also indicated that three of the five components of the MUSIC Model " usefulness, success, and caring" were positively associated with academic identification. Thus, there is preliminary evidence to suggest that teachers may be able to have a positive effect on the academic success of at-risk high school students by finding ways to improve students perceptions of usefulness, success, and care. Educational stakeholders can utilize findings from the present study to prompt an exploration of ways to improve these motivational components to promote greater academic success among this student population. / Ph. D.

Abstract In these years, Value at Risk (VaR) has been an important tool of risk management in the bank industry. In the past, property and casualty insurance industry does not have many correlation research in this aspect, especially in the key of the underwriting risk application may be collection difficulty in data , the domestic correlation research literature were actually few. In this paper, we use TEJ data bank to study the statistical data which needs for the research , the research sample total has 9 property insurance companies, By using the public information of TEJ data bank, it obtains the yearly and quarterly data, and uses the ¡§Fuzzy Distance Weighting Method¡¨ to change the quarterly data into monthly data , calculates loss ratio of the yearly, quarterly, monthly, then use the idea of VaR to compare the different of loss ratio-at-risk in yearly, quarterly, monthly¡CMoreover this study discusses the underwriting risk influence factor of domestic property and casualty insurance industry .This research discovers that yearly data will underestimate the actual of loss ratio at risk . In addition using regression analysis, the underwriting loss ratio-at- risk is influenced by free cash flow , leverage ratio , and firm size. According to the result of this paper, it could provide the reference rule when property and casualty insurance industry or supervisory authority set up the risk management rule. Keywords: Value at risk, Loss ratio, Loss ratio-at-risk, Underwriting risk

Value at Risk (VaR) är en finansiell metod för att skatta risker och som används i stor utsträckning av banker och företag. VaR beräknar att en eventuell förlust inte skall överstiga ett visst belopp med 95/99 procents konfidens. Denna uppsats syfte är att undersöka om VaR kan appliceras på en svensk aktie när Riskmetrics-modellen (IGARCH) skattar volatiliteten på aktien trots oro på den finansiella marknaden. Undersökningen genomfördes på Volvos B-aktie med data från perioden 2003-01-01 till 201 2-12-31. Vi genererade enstegsprognoser över den potentiella förlusten (VaR) givet en fiktiv investering av 10 000 000 SEK. Det estimerade VaR jämfördes sedan med de verkliga historiska utfallen. Resultaten visade att VaR med Riskmetrics-metoden lyckas täcka den verkliga förlusten i 96.31 procent av fallen. Detta resultat tyder på att Riskmetrics lyckas att skatta volatiliteten även under oroligheter, dels på den finansiella marknaden och dels inom företaget.

Diss. Wirtschaftswiss. Zürich (kein Austausch). / Im Buchh.: Zürich : Versus-Verlag. Register. Literaturverz.

Diss. Univ. St. Gallen, 2005.

O grande número de publicações na área de finanças atualmente utilizando a modelagem de cópulas pode ser explicada pela capacidade de esta técnica estatística conseguir lidar com a evidência de não normalidade das séries de retornos de ativos financeiros. A não normalidade é evidenciada através do “sorriso de volatilidade” presente em séries de opções de ações perto do vencimento; existência de “caudas pesadas” em carteiras de instituições e consequentemente no gerenciamento de risco das Instituições. Particularmente com relação ao Value at Risk (VaR), que é uma técnica estatística que tem por objetivo calcular a perda máxima de uma carteira em dado horizonte de tempo considerando um nível de significância adotado, a existência de caudas pesadas nas séries gera um problema para a determinação da distribuição de probabilidade conjunta, implicando em grande dificuldade na mensuração do grau de exposição aos fatores de risco. Esse fato acaba por dificultar o correto e efetivo gerenciamento de risco de uma carteira, pois em tese, devido à existência de não normalidade, não é possível separar os efeitos de ativos de diferentes características. Em casos de crises e bolhas, o portfólio pode ser mais arriscado que o desejado ou excessivamente conversador. Neste sentido, a utilização de Cópulas torna-se atrativa, pois com esta técnica é possível separar as distribuições marginais de cada ativo da estrutura de dependência das variáveis. O objetivo do trabalho é propor uma modelagem de risco a partir do uso de Cópulas para o cálculo do Value at Risk (VaR), utilizando os métodos de volatilidade GARCH (1,1), EWMA e HAR. A aplicação empírica do modelo foi efetuada a partir de uma amostra de uma série de retornos de uma carteira teórica composta por ativos de renda variável (ações preferenciais) das empresas Petrobras, Vale, Usiminas e Gerdau. A amostra utilizada corresponde aos preços diários entre o período de 03 de março de 2006 até 30 de abril de 2010, representando 1.026 observações diárias. Os resultados apurados para a amostra demonstraram que as cópulas tendem a gerar um Value at Risk (VaR) significativo para a maioria das famílias de Cópulas, quando testado pelo Teste de Kupiec (1995). / The large number of publications in finance using currently copulas can be explained by the ability of this technique to deal with statistical evidence of non-normality of the return series of financial assets. The non-normality is evidenced by the "volatility smile" in the series of stock options near expiration, the existence of "heavy tails" in portfolios of institutions and consequently the risk management of the institutions. Especially regarding the Value at Risk (VaR), which is a statistical technique that aims to calculate the maximum loss a portfolio at a given time horizon considering a significance level, the existence of heavy tails in the series creates a problem for determining the joint probability distribution, resulting in great difficulty in measuring the degree of exposure to risk factors. This fact makes difficult the correct and effective risk management of a portfolio, because in theory, due to the existence of non-normality, it is not possible to separate the effects of assets with different characteristics. In cases of crises and bubbles, the portfolio may be riskier than desired or overly chatty. In this regard, the use of copulas becomes attractive, because with this technique is possible to separate the marginal distributions of each dependence structure of the variables. The objective is to propose a model of risk using copulas for the calculation of Value at Risk (VaR), using the methods of volatility GARCH (1,1), EWMA and HAR. The empirical application of the model was made from a sample of a series of returns of a theoretical portfolio of assets in equities (shares) of Petrobras, Vale, Usiminas and Gerdau. The sample corresponds to the daily prices in the period between March 3rd, 2006 until April 30th, 2010, representing 1026 daily observations. The results obtained showed that copulas tend to generate a Value at Risk (VaR) for the most significant families of copulas, when tested by the Test of Kupiec (1995).

O grande número de publicações na área de finanças atualmente utilizando a modelagem de cópulas pode ser explicada pela capacidade de esta técnica estatística conseguir lidar com a evidência de não normalidade das séries de retornos de ativos financeiros. A não normalidade é evidenciada através do “sorriso de volatilidade” presente em séries de opções de ações perto do vencimento; existência de “caudas pesadas” em carteiras de instituições e consequentemente no gerenciamento de risco das Instituições. Particularmente com relação ao Value at Risk (VaR), que é uma técnica estatística que tem por objetivo calcular a perda máxima de uma carteira em dado horizonte de tempo considerando um nível de significância adotado, a existência de caudas pesadas nas séries gera um problema para a determinação da distribuição de probabilidade conjunta, implicando em grande dificuldade na mensuração do grau de exposição aos fatores de risco. Esse fato acaba por dificultar o correto e efetivo gerenciamento de risco de uma carteira, pois em tese, devido à existência de não normalidade, não é possível separar os efeitos de ativos de diferentes características. Em casos de crises e bolhas, o portfólio pode ser mais arriscado que o desejado ou excessivamente conversador. Neste sentido, a utilização de Cópulas torna-se atrativa, pois com esta técnica é possível separar as distribuições marginais de cada ativo da estrutura de dependência das variáveis. O objetivo do trabalho é propor uma modelagem de risco a partir do uso de Cópulas para o cálculo do Value at Risk (VaR), utilizando os métodos de volatilidade GARCH (1,1), EWMA e HAR. A aplicação empírica do modelo foi efetuada a partir de uma amostra de uma série de retornos de uma carteira teórica composta por ativos de renda variável (ações preferenciais) das empresas Petrobras, Vale, Usiminas e Gerdau. A amostra utilizada corresponde aos preços diários entre o período de 03 de março de 2006 até 30 de abril de 2010, representando 1.026 observações diárias. Os resultados apurados para a amostra demonstraram que as cópulas tendem a gerar um Value at Risk (VaR) significativo para a maioria das famílias de Cópulas, quando testado pelo Teste de Kupiec (1995). / The large number of publications in finance using currently copulas can be explained by the ability of this technique to deal with statistical evidence of non-normality of the return series of financial assets. The non-normality is evidenced by the "volatility smile" in the series of stock options near expiration, the existence of "heavy tails" in portfolios of institutions and consequently the risk management of the institutions. Especially regarding the Value at Risk (VaR), which is a statistical technique that aims to calculate the maximum loss a portfolio at a given time horizon considering a significance level, the existence of heavy tails in the series creates a problem for determining the joint probability distribution, resulting in great difficulty in measuring the degree of exposure to risk factors. This fact makes difficult the correct and effective risk management of a portfolio, because in theory, due to the existence of non-normality, it is not possible to separate the effects of assets with different characteristics. In cases of crises and bubbles, the portfolio may be riskier than desired or overly chatty. In this regard, the use of copulas becomes attractive, because with this technique is possible to separate the marginal distributions of each dependence structure of the variables. The objective is to propose a model of risk using copulas for the calculation of Value at Risk (VaR), using the methods of volatility GARCH (1,1), EWMA and HAR. The empirical application of the model was made from a sample of a series of returns of a theoretical portfolio of assets in equities (shares) of Petrobras, Vale, Usiminas and Gerdau. The sample corresponds to the daily prices in the period between March 3rd, 2006 until April 30th, 2010, representing 1026 daily observations. The results obtained showed that copulas tend to generate a Value at Risk (VaR) for the most significant families of copulas, when tested by the Test of Kupiec (1995).