Principal component and second generation wavelet analysis of Treasury yield curve evolution

Prices of U.S. Treasury securities vary over time and across maturities. When the market in Treasurys is sufficiently complete and frictionless, these prices may be modeled by a function time and maturity. A cross-section of this function for time held fixed is called the yield curve; the aggregate of these sections is the evolution of the yield curve. This dissertation studies aspects of this evolution. ^ There are two complementary approaches to the study of yield curve evolution here. The first is principal components analysis; the second is wavelet analysis. In both approaches both the time and maturity variables are discretized. In principal components analysis the vectors of yield curve shifts are viewed as observations of a multivariate normal distribution. The resulting covariance matrix is diagonalized; the resulting eigenvalues and eigenvectors (the principal components) are used to draw inferences about the yield curve evolution. ^ In wavelet analysis, the vectors of shifts are resolved into hierarchies of localized fundamental shifts (wavelets) that leave specified global properties invariant (average change and duration change). The hierarchies relate to the degree of localization with movements restricted to a single maturity at the base and general movements at the apex. Second generation wavelet techniques allow better adaptation of the model to economic observables. Statistically, the wavelet approach is inherently nonparametric while the wavelets themselves are better adapted to describing a complete market. ^ Principal components analysis provides information on the dimension of the yield curve process. While there is no clear demarkation between operative factors and noise, the top six principal components pick up 99% of total interest rate variation 95% of the time. An economically justified basis of this process is hard to find; for example a simple linear model will not suffice for the first principal component and the shape of this component is nonstationary. ^ Wavelet analysis works more directly with yield curve observations than principal components analysis. In fact the complete process from bond data to multiresolution is presented, including the dedicated Perl programs and the details of the portfolio metrics and specially adapted wavelet construction. The result is more robust statistics which provide balance to the more fragile principal components analysis. ^

Essays on corporate reputation: Antecedents and consequences

This dissertation studied the determinants and consequences of corporate reputation. It explored how firm-, industry-, and country-level factors influence the general public’s assessment of a firm’s reputation and how this reputation assessment impacted the firm’s strategic actions and organizational outcomes. The three empirical essays are grounded on separate theoretical paradigms in strategy, organizational theory, and corporate governance. The first essay used signaling theory to investigate firm-, industry-, and country-level determinants of individual-level corporate reputation assessments. Using a hierarchical linear model, it tested the theory based on individual evaluations of the largest companies across countries. Results indicated that variables at multiple analysis levels simultaneously impact individual level reputation assessments. Interactions were also found between industry- and country-level factors. Results confirmed the multi-level nature of signaling influences on reputation assessments. Building on a stakeholder-power approach to corporate governance, the second essay studied how differences in the power and preferences of three stakeholder groups—shareholders, creditors, and workers—across countries influence the general public’s reputation assessments of corporations. Examining the largest companies across countries, the study found that while the influence of stock market return is stronger in societies where shareholders have more power, social performance has a more significant role in shaping reputation evaluations in societies with stronger labor rights. Unexpectedly, when creditors have greater power, the influence of financial stability on reputation assessment becomes weaker. Exploring the consequences of reputation, the third essay investigated the specific effects of intangible assets on strategic actions and organizational outcomes. Particularly, it individually studied the impacts of acquirer acquisition experience, corporate reputation, and approach toward social responsibilities as well as their combined effect on market reactions to acquisition announcements. Using an event study of acquisition announcements, it confirmed the significant impacts of both action-specific (acquisition experience) and general (reputation and social performance) intangible assets on market expectations of acquisition outcomes. Moreover, the analysis demonstrated that reputation magnifies the impact of acquisition experience on market response to acquisition announcements. In conclusion, this dissertation tried to advance and extend the application of management and organizational theories by explaining the mechanisms underlying antecedents and consequences of corporate reputation.

Investigating the outcomes of two chronic disease self-management programs and understanding the correlates of completion for each program

Chronic disease affects 80% of adults over the age of 65 and is expected to increase in prevalence. To address the burden of chronic disease, self-management programs have been developed to increase self-efficacy and improve quality of life by reducing or halting disease symptoms. Two programs that have been developed to address chronic disease are the Chronic Disease Self-Management Program (CDSMP) and Tomando Control de su Salud (TCDS). CDSMP and TCDS both focus on improving participant self-efficacy, but use different curricula, as TCDS is culturally tailored for the Hispanic population. Few studies have evaluated the effectiveness of CDSMP and TCDS when translated to community settings. In addition, little is known about the correlation between demographic, baseline health status, and psychosocial factors and completion of either CDSMP or TCDS. This study used secondary data collected by agencies of the Healthy Aging Regional Collaborative from 10/01/2008–12/31/2010. The aims of this study were to examine six week differences in self-efficacy, time spent performing physical activity, and social/role activity limitations, and to identify correlates of program completion using baseline demographic and psychosocial factors. To examine if differences existed a general linear model was used. Additionally, logistic regression was used to examine correlates of program completion. Study findings show that all measures showed improvement at week six. For CDSMP, self-efficacy to manage disease (p = .001), self-efficacy to manage emotions (p = .026), social/role activities limitations (p = .001), and time spent walking (p = .008) were statistically significant. For TCDS, self-efficacy to manage disease (p = .006), social/role activities limitations (p = .001), and time spent walking (p = .016) and performing other aerobic activity (p = .005) were significant. For CDSMP, no correlates predicting program completion were found to be significant. For TCDS, participants who were male (OR=2.3, 95%CI: 1.15–4.66), from Broward County (OR=2.3, 95%CI: 1.27–4.25), or living alone (OR=2.0, 95%CI: 1.29-–3.08) were more likely to complete the program. CDSMP and TCDS, when implemented through a collaborative effort, can result in improvements for participants. Effective chronic disease management can improve health, quality of life, and reduce health care expenditures among older adults.

Reliability analysis of encapsulation methods for lead -based paint through an accelerated life testing

The adverse health effects of long-term exposure to lead are well established, with major uptake into the human body occurring mainly through oral ingestion by young children. Lead-based paint was frequently used in homes built before 1978, particularly in inner-city areas. Minority populations experience the effects of lead poisoning disproportionately. ^ Lead-based paint abatement is costly. In the United States, residents of about 400,000 homes, occupied by 900,000 young children, lack the means to correct lead-based paint hazards. The magnitude of this problem demands research on affordable methods of hazard control. One method is encapsulation, defined as any covering or coating that acts as a permanent barrier between the lead-based paint surface and the environment. ^ Two encapsulants were tested for reliability and effective life span through an accelerated lifetime experiment that applied stresses exceeding those encountered under normal use conditions. The resulting time-to-failure data were used to extrapolate the failure time under conditions of normal use. Statistical analysis and models of the test data allow forecasting of long-term reliability relative to the 20-year encapsulation requirement. Typical housing material specimens simulating walls and doors coated with lead-based paint were overstressed before encapsulation. A second, un-aged set was also tested. Specimens were monitored after the stress test with a surface chemical testing pad to identify the presence of lead breaking through the encapsulant. ^ Graphical analysis proposed by Shapiro and Meeker and the general log-linear model developed by Cox were used to obtain results. Findings for the 80% reliability time to failure varied, with close to 21 years of life under normal use conditions for encapsulant A. The application of product A on the aged gypsum and aged wood substrates yielded slightly lower times. Encapsulant B had an 80% reliable life of 19.78 years. ^ This study reveals that encapsulation technologies can offer safe and effective control of lead-based paint hazards and may be less expensive than other options. The U.S. Department of Health and Human Services and the CDC are committed to eliminating childhood lead poisoning by 2010. This ambitious target is feasible, provided there is an efficient application of innovative technology, a goal to which this study aims to contribute. ^

Online Education, Accrediting Standards, and Student Success: An Examination of the Relationship Between the Southern Association of Colleges and Schools Commission on Colleges Standards for Online Education and Student Success

Prior to 2000, there were less than 1.6 million students enrolled in at least one online course. By fall 2010, student enrollment in online distance education showed a phenomenal 283% increase to 6.1 million. Two years later, this number had grown to 7.1 million. In light of this significant growth and skepticism about quality, there have been calls for greater oversight of this format of educational delivery. Accrediting bodies tasked with this oversight have developed guidelines and standards for online education. There is a lack of empirical studies that examine the relationship between accrediting standards and student success. The purpose of this study was to examine the relationship between the presence of Southern Association of Colleges and Schools Commission on College (SACSCOC) standards for online education in online courses, (a) student support services and (b) curriculum and instruction, and student success. An original 24-item survey with an overall reliability coefficient of .94 was administered to students (N=464) at Florida International University, enrolled in 24 university-wide undergraduate online courses during fall 2014, who rated the presence of these standards in their online courses. The general linear model was utilized to analyze the data. The results of the study indicated that the two standards, student support services and curriculum and instruction were both significantly and positively correlated with student success but with small R2 and strengths of association less than .35 and .20 respectively. Mixed results were produced from Chi-square tests for differences in student success between higher and lower rated online courses when controlling for various covariates such as discipline, gender, race/ethnicity, GPA, age, and number of online courses previously taken. A multiple linear regression analysis revealed that the curriculum and instruction standard was the only variable that accounted for a significant amount of unique variance in student success. Another regression test revealed that no significant interaction effect exists between the two SACSCOC standards and GPA in predicting student success. The results of this study are useful for administrators, faculty, and researchers who are interested in accreditation standards for online education and how these standards relate to student success.

Fuzzy Modeling and Control Based Virtual Machine Resource Management

Virtual machines (VMs) are powerful platforms for building agile datacenters and emerging cloud systems. However, resource management for a VM-based system is still a challenging task. First, the complexity of application workloads as well as the interference among competing workloads makes it difficult to understand their VMs’ resource demands for meeting their Quality of Service (QoS) targets; Second, the dynamics in the applications and system makes it also difficult to maintain the desired QoS target while the environment changes; Third, the transparency of virtualization presents a hurdle for guest-layer application and host-layer VM scheduler to cooperate and improve application QoS and system efficiency. This dissertation proposes to address the above challenges through fuzzy modeling and control theory based VM resource management. First, a fuzzy-logic-based nonlinear modeling approach is proposed to accurately capture a VM’s complex demands of multiple types of resources automatically online based on the observed workload and resource usages. Second, to enable fast adaption for resource management, the fuzzy modeling approach is integrated with a predictive-control-based controller to form a new Fuzzy Modeling Predictive Control (FMPC) approach which can quickly track the applications’ QoS targets and optimize the resource allocations under dynamic changes in the system. Finally, to address the limitations of black-box-based resource management solutions, a cross-layer optimization approach is proposed to enable cooperation between a VM’s host and guest layers and further improve the application QoS and resource usage efficiency. The above proposed approaches are prototyped and evaluated on a Xen-based virtualized system and evaluated with representative benchmarks including TPC-H, RUBiS, and TerraFly. The results demonstrate that the fuzzy-modeling-based approach improves the accuracy in resource prediction by up to 31.4% compared to conventional regression approaches. The FMPC approach substantially outperforms the traditional linear-model-based predictive control approach in meeting application QoS targets for an oversubscribed system. It is able to manage dynamic VM resource allocations and migrations for over 100 concurrent VMs across multiple hosts with good efficiency. Finally, the cross-layer optimization approach further improves the performance of a virtualized application by up to 40% when the resources are contended by dynamic workloads.

Online education, accrediting standards, and student success: An examination of the relationship between the southern association of colleges and schools commission on colleges standards for online education and student success

Prior to 2000, there were less than 1.6 million students enrolled in at least one online course. By fall 2010, student enrollment in online distance education showed a phenomenal 283% increase to 6.1 million. Two years later, this number had grown to 7.1 million. In light of this significant growth and skepticism about quality, there have been calls for greater oversight of this format of educational delivery. Accrediting bodies tasked with this oversight have developed guidelines and standards for online education. ^ There is a lack of empirical studies that examine the relationship between accrediting standards and student success. The purpose of this study was to examine the relationship between the presence of Southern Association of Colleges and Schools Commission on College (SACSCOC) standards for online education in online courses, (a) student support services and (b) curriculum and instruction, and student success. An original 24-item survey with an overall reliability coefficient of .94 was administered to students (N=464) at Florida International University, enrolled in 24 university-wide undergraduate online courses during fall 2014, who rated the presence of these standards in their online courses. The general linear model was utilized to analyze the data. The results of the study indicated that the two standards, student support services and curriculum and instruction were both significantly and positively correlated with student success but with small R2 and strengths of association less than .35 and .20 respectively. Mixed results were produced from Chi-square tests for differences in student success between higher and lower rated online courses when controlling for various covariates such as discipline, gender, race/ethnicity, GPA, age, and number of online courses previously taken. A multiple linear regression analysis revealed that the curriculum and instruction standard was the only variable that accounted for a significant amount of unique variance in student success. Another regression test revealed that no significant interaction effect exists between the two SACSCOC standards and GPA in predicting student success. ^ The results of this study are useful for administrators, faculty, and researchers who are interested in accreditation standards for online education and how these standards relate to student success.^

Sex-Positive Curricula: An Investigation of the Relationship Between Physical Fitness, Self-Concept and Sexual Functioning

Despite the well-recognized benefits of exercise, Americans are gaining weight in astounding proportions and levels of physical activity are on the decline. The purpose of this study was to investigate a relationship between physical fitness, self-concept and sexual health. There is a dearth of knowledge on this relationship specifically in the context of sex-negative curricula, which is the dominate discourse in the United States. One hundred and thirty-three participants between the ages of 18 - 50 volunteered for fitness testing and data collection. Physical fitness was assessed through body fat, resting metabolic rate, cardiovascular endurance, muscular strength, muscular endurance and flexibility. Self-reported exercise was measured using the International Physical Activity Questionnaire. Self-concept was measured by the Six Factor Self-Concept Scale, which presented a total self-concept score and as six individual concepts of self (likability, morality, task accomplishment, giftedness, power and vulnerability). Additionally, sexual function was measured by Derogatis Interview for Sexual Functioning and presented as both an aggregate score and five separate constructs of sexual functioning (fantasy/cognition, arousal, orgasm, behavior/experience, and drive/desire). Questions pertaining to sexual partners, sex education, and demographic information were also included. The results of the General Linear Model indicated significant relationships between physical fitness, self-concept and total sexual functioning. The sexual behavior/experience of men was predicted by body fat percentage and flexibility. In women, behavior/experience was predicted by body fat percentage and arousal was predicted by cardiovascular endurance. Total self-concept was related to muscular endurance. When men were isolated in the analysis, likability was positively related to sexual behavior/experience, and task accomplishment was inversely related to sexual behavior/experience. In women, giftedness was related to cognition/fantasy, arousal, orgasm and total sexual functioning. No relationships were found between physical fitness and the number of sexual partners in men; however, both muscular strength and the power self-concept were significantly related to number of sexual partners in women. As a result of these findings, women may be inclined to exercise to improve arousal and sexual functioning. Furthermore, educators should note the findings of a positive relationship between physical and psychological health and sexual well-being because they provide support for the development and adoption of sex-positive curricula that incorporate potential benefits of sexual activity.

A non-linear discrete stochastic optimization model for Advanced Access patient appointment scheduling

Access to healthcare is a major problem in which patients are deprived of receiving timely admission to healthcare. Poor access has resulted in significant but avoidable healthcare cost, poor quality of healthcare, and deterioration in the general public health. Advanced Access is a simple and direct approach to appointment scheduling in which the majority of a clinic's appointments slots are kept open in order to provide access for immediate or same day healthcare needs and therefore, alleviate the problem of poor access the healthcare. This research formulates a non-linear discrete stochastic mathematical model of the Advanced Access appointment scheduling policy. The model objective is to maximize the expected profit of the clinic subject to constraints on minimum access to healthcare provided. Patient behavior is characterized with probabilities for no-show, balking, and related patient choices. Structural properties of the model are analyzed to determine whether Advanced Access patient scheduling is feasible. To solve the complex combinatorial optimization problem, a heuristic that combines greedy construction algorithm and neighborhood improvement search was developed. The model and the heuristic were used to evaluate the Advanced Access patient appointment policy compared to existing policies. Trade-off between profit and access to healthcare are established, and parameter analysis of input parameters was performed. The trade-off curve is a characteristic curve and was observed to be concave. This implies that there exists an access level at which at which the clinic can be operated at optimal profit that can be realized. The results also show that, in many scenarios by switching from existing scheduling policy to Advanced Access policy clinics can improve access without any decrease in profit. Further, the success of Advanced Access policy in providing improved access and/or profit depends on the expected value of demand, variation in demand, and the ratio of demand for same day and advanced appointments. The contributions of the dissertation are a model of Advanced Access patient scheduling, a heuristic to solve the model, and the use of the model to understand the scheduling policy trade-offs which healthcare clinic managers must make. ^

Comparison of Some Improved Estimators for Linear Regression Model under Different Conditions

Multiple linear regression model plays a key role in statistical inference and it has extensive applications in business, environmental, physical and social sciences. Multicollinearity has been a considerable problem in multiple regression analysis. When the regressor variables are multicollinear, it becomes difficult to make precise statistical inferences about the regression coefficients. There are some statistical methods that can be used, which are discussed in this thesis are ridge regression, Liu, two parameter biased and LASSO estimators. Firstly, an analytical comparison on the basis of risk was made among ridge, Liu and LASSO estimators under orthonormal regression model. I found that LASSO dominates least squares, ridge and Liu estimators over a significant portion of the parameter space for large dimension. Secondly, a simulation study was conducted to compare performance of ridge, Liu and two parameter biased estimator by their mean squared error criterion. I found that two parameter biased estimator performs better than its corresponding ridge regression estimator. Overall, Liu estimator performs better than both ridge and two parameter biased estimator.