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.

Thesis (Ed.D)--Boston University / PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you. / Is it possible for at-risk students attending a rural community college to succeed in attaining their stated academic goals if exposed to a retention program customized to suit the needs of students attending their type of institution? What role does a student's motivation to succeed play in his or her decision to pursue achievement behavior in college? Are academically at-risk learners aware of behaviors that limit their success in the classroom? If so, what affective and cognitive variables determine individual success and to what extent can these variables be screened for on entrance? To address the above questions, the LASSI and Trice Locus of Control inventory were administered to 45 students enrolled in the Opportunity For Success program, a retention effort for at-risk 17-21 years old students at Quinebaug Valley Community College in Connecticut. Using SPSS, a multiple regression analysis was performed by entering the 10 variables of the LASS I and the GP A for the subjects. Also, two 90- minute, in-depth interviews were conducted of 26 of the 45 students. Faculty and advisors of these students were asked to rate their performance. The findings support the literature on student success and college student attrition. At-risk learners are aware of behaviors that limit their success. Successful at-risk students possess a variety of strategies to cope with academic challenge while low achieving students often do not. Instead, the low achieving students develop theories to explain their failure to succeed. Similarly, this research illustrates that failure, like success, is a habit learned over time and context dependent; the high school experiences of underachieving subjects demonstrate that they are often unmotivated to succeed in the classroom because they lack the interest to invest in academic endeavors. Low achieving students in this study continued this pattern in college, while those who became high and moderately achieving adopted multiple strategies to ensure success. Participants were motivated to perform in classes they considered "fun" and relevant to their future goals. The findings also show that educators should assist at-risk students to overcome their fear of failure by increasing their ability to self-regulate learning, set goals, and evolve healthy self concept. This study concludes that the desire to persist, information processing, and attitude towards learning play a major role in the learner's decision to pursue achievement behavior. / 2999-01-01

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).