Liquidity and asset pricing: A comparison between three-factor and three-moment capital asset pricing models

Liquidity is an important attribute of an asset that investors would like to take into consideration when making investment decisions. However, the previous empirical evidence whether liquidity is a determinant of stock return is not unanimous. This dissertation provides a very comprehensive study about the role of liquidity in asset pricing using the Fama-French (1993) three-factor and Kraus and Litzenberger (1976) three-moment CAPM as models for risk adjustment. The relationship between liquidity and well-known determinants of stock returns such as size and book-to-market are also investigated. This study examines the liquidity and asset pricing issues for both intertemporal as well as cross-sectional data. ^ The results indicate an existence of a liquidity premium, i.e., less liquid stocks would demand higher rate of return than more liquid stocks. More specifically, a drop of 1 percent in liquidity is associated with a higher rate of return of about 2 to 3 basis points per month. Further investigation reveals that neither the Fama-French three-factor model nor the three-moment CAPM captures the liquidity premium. Finally, the results show that well-known determinants of stock return such as size and book-to-market do not serve as proxy for liquidity. ^ Overall, this dissertation shows that a liquidity premium exists in the stock market and that liquidity is a distinct effect, and is not influenced by the presence of non-market factors, market factors and other stock characteristics.^

Potential for Cell-Transplant Therapy with Human Neuronal Precursors to Treat Neuropathic Pain in Models of PNS and CNS Injury: Comparison of hNT2.17 and hNT2.19 Cell Lines

Effective treatment of sensory neuropathies in peripheral neuropathies and spinal cord injury (SCI) is one of the most difficult problems in modern clinical practice. Cell therapy to release antinociceptive agents near the injured spinal cord is a logical next step in the development of treatment modalities. But few clinical trials, especially for chronic pain, have tested the potential of transplant of cells to treat chronic pain. Cell lines derived from the human neuronal NT2 cell line parentage, the hNT2.17 and hNT2.19 lines, which synthesize and release the neurotransmitters gamma-aminobutyric acid (GABA) and serotonin (5HT), respectively, have been used to evaluate the potential of cell-based release of antinociceptive agents near the lumbar dorsal (horn) spinal sensory cell centers to relieve neuropathic pain after PNS (partial nerve and diabetes-related injury) and CNS (spinal cord injury) damage in rat models. Both cell lines transplants potently and permanently reverse behavioral hypersensitivity without inducing tumors or other complications after grafting. Functioning as cellular minipumps for antinociception, human neuronal precursors, like these NT2-derived cell lines, would likely provide a useful adjuvant or replacement for current pharmacological treatments for neuropathic pain.

A comparison study of the English III/American Literature success of African American high school students and that of students whose home language is Haitian Creole

The purpose of the study was to compare the English III success of students whose home language is Haitian Creole (SWHLIHC) with that of the more visible African American high school students in the Miami Dade County Public Schools System, in an effort to offer insight that might assist educators in facilitating the educational success of SWHLIHC in American Literature class.^ The study was guided by two important theories on how students interact with and learn from literature. They are Reader Response Theory which advocates giving students the opportunity to become involved in the literature experience (Rosenblatt, 1995), and Critical Literacy, a theory developed by Paolo Freire and Henry Giroux, which espouses a critical approach to analysis of society that enables people to analyze social problems through lenses that would reveal social inequities and assist in transforming society into a more equitable entity.^ Data for the study: 10th grade reading FCAT scores, English III/American Literature grades, and Promotion to English IV records for the school year 2010-2011 were retrieved from the records division of the Miami Dade County Public Schools System. The study used a quantitative methods approach, the central feature of which was an ex post facto design with hypotheses (Newman, Newman, Brown, & McNeely, 2006). The ex post facto design with hypotheses was chosen because the researcher postulated hypotheses about the relationships that might exist between the performances of SWHLIHC and those of African American students on the three above mentioned variables. This type of design supported the researcher's purpose of comparing these performances.^ One way analysis of variance (ANOVA), two way ANOVAs, and chi square tests were used to examine the two groups' performances on the 10th grade reading FCAT, their English III grades, and their promotion to English IV. ^ The study findings show that there was a significant difference in the performance of SWHLIHC and African American high school students on all three independent variables. SWHLIHC performed significantly higher on English III success and promotion to English IV. African American high school students performed significantly higher on the reading FCAT.^

Statistical Models for Predicting College Success

Colleges base their admission decisions on a number of factors to determine which applicants have the potential to succeed. This study utilized data for students that graduated from Florida International University between 2006 and 2012. Two models were developed (one using SAT as the principal explanatory variable and the other using ACT as the principal explanatory variable) to predict college success, measured using the student’s college grade point average at graduation. Some of the other factors that were used to make these predictions were high school performance, socioeconomic status, major, gender, and ethnicity. The model using ACT had a higher R^2 but the model using SAT had a lower mean square error. African Americans had a significantly lower college grade point average than graduates of other ethnicities. Females had a significantly higher college grade point average than males.

A Comparison Study of the English III/American Literature Success of African American High School Students and That of Students Whose Home Language is Haitian Creole

The purpose of the study was to compare the English III success of students whose home language is Haitian Creole (SWHLIHC) with that of the more visible African American high school students in the Miami Dade County Public Schools System, in an effort to offer insight that might assist educators in facilitating the educational success of SWHLIHC in American Literature class. The study was guided by two important theories on how students interact with and learn from literature. They are Reader Response Theory which advocates giving students the opportunity to become involved in the literature experience (Rosenblatt, 1995), and Critical Literacy, a theory developed by Paolo Freire and Henry Giroux, which espouses a critical approach to analysis of society that enables people to analyze social problems through lenses that would reveal social inequities and assist in transforming society into a more equitable entity. Data for the study: 10th grade reading FCAT scores, English III/American Literature grades, and Promotion to English IV records for the school year 2010-2011 were retrieved from the records division of the Miami Dade County Public Schools System. The study used a quantitative methods approach, the central feature of which was an ex post facto design with hypotheses (Newman, Newman, Brown, & McNeely, 2006). The ex post facto design with hypotheses was chosen because the researcher postulated hypotheses about the relationships that might exist between the performances of SWHLIHC and those of African American students on the three above mentioned variables. This type of design supported the researcher’s purpose of comparing these performances. One way analysis of variance (ANOVA), two way ANOVAs, and chi square tests were used to examine the two groups’ performances on the 10th grade reading FCAT, their English III grades, and their promotion to English IV. The study findings show that there was a significant difference in the performance of SWHLIHC and African American high school students on all three independent variables. SWHLIHC performed significantly higher on English III success and promotion to English IV. African American high school students performed significantly higher on the reading FCAT.

A comparison of content-based and context-based teaching on ninth-grade mathematics achievement

The purpose of this study was to determine if an experimental context-based delivery format for mathematics would be more effective than a traditional model for increasing the performance in mathematics of at-risk students in a public high school of choice, as evidenced by significant gains in achievement on the standards-based Mathematics subtest of the FCAT and final academic grades in Algebra I. The guiding rationale for this approach is captured in the Secretary's Commission on Achieving Necessary Skills (SCANS) report of 1992 that resulted in school-to-work initiatives (United States Department of Labor). Also, the charge for educational reform has been codified at the state level as Educational Accountability Act of 1971 (Florida Statutes, 1995) and at the national level as embodied in the No Child Left Behind Act of 2001. A particular focus of educational reform is low performing, at-risk students. ^ This dissertation explored the effects of a context-based curricular reform designed to enhance the content of Algebra I content utilizing a research design consisting of two delivery models: a traditional content-based course; and, a thematically structured, content-based course. In this case, the thematic element was business education as there are many advocates in career education who assert that this format engages students who are often otherwise disinterested in mathematics in a relevant, SCANS skills setting. The subjects in each supplementary course were ninth grade students who were both low performers in eighth grade mathematics and who had not passed the eighth grade administration of the standards-based FCAT Mathematics subtest. The sample size was limited to two groups of 25 students and two teachers. The site for this study was a public charter school. Student-generated performance data were analyzed using descriptive statistics. ^ Results indicated that contrary to the beliefs held by many, contextual presentation of content did not cause significant gains in either academic performance or test performance for those in the experimental treatment group. Further, results indicated that there was no meaningful difference in performance between the two groups. ^

Development of prediction models for freeway incident durations using data mining techniques

The nation's freeway systems are becoming increasingly congested. A major contribution to traffic congestion on freeways is due to traffic incidents. Traffic incidents are non-recurring events such as accidents or stranded vehicles that cause a temporary roadway capacity reduction, and they can account for as much as 60 percent of all traffic congestion on freeways. One major freeway incident management strategy involves diverting traffic to avoid incident locations by relaying timely information through Intelligent Transportation Systems (ITS) devices such as dynamic message signs or real-time traveler information systems. The decision to divert traffic depends foremost on the expected duration of an incident, which is difficult to predict. In addition, the duration of an incident is affected by many contributing factors. Determining and understanding these factors can help the process of identifying and developing better strategies to reduce incident durations and alleviate traffic congestion. A number of research studies have attempted to develop models to predict incident durations, yet with limited success. ^ This dissertation research attempts to improve on this previous effort by applying data mining techniques to a comprehensive incident database maintained by the District 4 ITS Office of the Florida Department of Transportation (FDOT). Two categories of incident duration prediction models were developed: "offline" models designed for use in the performance evaluation of incident management programs, and "online" models for real-time prediction of incident duration to aid in the decision making of traffic diversion in the event of an ongoing incident. Multiple data mining analysis techniques were applied and evaluated in the research. The multiple linear regression analysis and decision tree based method were applied to develop the offline models, and the rule-based method and a tree algorithm called M5P were used to develop the online models. ^ The results show that the models in general can achieve high prediction accuracy within acceptable time intervals of the actual durations. The research also identifies some new contributing factors that have not been examined in past studies. As part of the research effort, software code was developed to implement the models in the existing software system of District 4 FDOT for actual applications. ^

Comparison of repeated and two non-repeated readings conditions on reading abilities of students with emotional and/or behavioral disabilities

Students with emotional and/or behavioral disorders (EBD)present considerable academic challenges along with emotional and/or behavioral problems. In terms of reading, these students typically perform one-to-two years below grade level (Kauffman, 2001). Given the strong correlation between reading failure and school failure and overall success (Scott & Shearer-Lingo, 2002), finding effective approaches to reading instruction is imperative for these students (Staubitz, Cartledge, Yurick, & Lo, 2005). This study used an alternating treatments design to comparethe effects of three conditions on the reading fluency, errors, and comprehension of four, sixth-grade students with EBD who were struggling readers. Specifically, the following were compared: (a) Repeated readings in which participants repeatedly read a passage of about 100-150 words, three times, (b) Non-repeated readings in which participants sequentially read an original passage of about 100-150 words once, and (c) Equivalent non-repeated readings in which participants sequentially read a passage of about 300-450 words, equivalent to the number of words in the repeated readings condition. Also examined were the effects of the three repeated readings practice trials per sessions on reading fluency and errors. The reading passage difficulty and length established prior to commencing were used for all participants throughout the standard phase. During the enhanced phase, the reading levels were increased 6 months for all participants, and for two (the advanced readers), the length of the reading passages was increased by 50%, allowing for comparisons under more rigorous conditions. The results indicate that overall repeated readings had the best outcome across the standard and enhanced phases for increasing readers’ fluency, reducing their errors per minute, and supporting fluency answers to literal comprehension questions correctly as compared to non-repeated and equivalent non-repeated conditions. When comparing nonrepeated and equivalent non-repeated readings,there were mixed results. Under the enhanced phases, the positive effects of repeated readings were more demonstrative. Additional research is needed to compare the effects of repeated and equivalent non-repeated readings across other populations of students with disabilities or varying learning styles. This research should include collecting repeated readings practice trial data for fluency and errors to further analyze the immediate effects of repeatedly reading a passage.

Political strategy, leadership, and policy entrepreneurship in Japanese defense policy and politics: A comparison of three prime ministerships

Since the end of the Cold War, Japan's defense policy and politics has gone through significant changes. Throughout the post cold war period, US-Japan alliance managers, politicians with differing visions and preferences, scholars, think tanks, and the actions of foreign governments have all played significant roles in influencing these changes. Along with these actors, the Japanese prime minister has played an important, if sometimes subtle, role in the realm of defense policy and politics. Japanese prime ministers, though significantly weaker than many heads of state, nevertheless play an important role in policy by empowering different actors (bureaucratic actors, independent commissions, or civil actors), through personal diplomacy, through agenda-setting, and through symbolic acts of state. The power of the prime minister to influence policy processes, however, has frequently varied by prime minister. My dissertation investigates how different political strategies and entrepreneurial insights by the prime minister have influenced defense policy and politics since the end of the Cold War. In addition, it seeks to explain how the quality of political strategy and entrepreneurial insight employed by different prime ministers was important in the success of different approaches to defense. My dissertation employs a comparative case study approach to examine how different prime ministerial strategies have mattered in the realm of Japanese defense policy and politics. Three prime ministers have been chosen: Prime Minister Hashimoto Ryutaro (1996-1998); Prime Minister Koizumi Junichiro (2001-2006); and Prime Minister Hatoyama Yukio (2009-2010). These prime ministers have been chosen to provide maximum contrast on issues of policy preference, cabinet management, choice of partners, and overall strategy. As my dissertation finds, the quality of political strategy has been an important aspect of Japan's defense transformation. Successful strategies have frequently used the knowledge and accumulated personal networks of bureaucrats, supplemented bureaucratic initiatives with top-down personal diplomacy, and used a revitalized US-Japan strategic relationship as a political resource for a stronger prime ministership. Though alternative approaches, such as those that have looked to displace the influence of bureaucrats and the US in defense policy, have been less successful, this dissertation also finds theoretical evidence that alternatives may exist.

The relationship between socioeconomic status, course delivery method, and student success at a state college: A single institution analysis

In an effort to improve instruction and better accommodate the needs of students, community colleges are offering courses delivered in a variety of delivery formats that require students to have some level of technology fluency to be successful in the course. This study was conducted to investigate the relationship between student socioeconomic status (SES), course delivery method, and course type on enrollment, final course grades, course completion status, and course passing status at a state college. ^ A dataset for 20,456 students of low and not low SES enrolled in science, technology, engineering, and mathematics (STEM) course types delivered using traditional, online, blended, and web enhanced course delivery formats at Miami Dade College, a large open access 4-year state college located in Miami-Dade County, Florida, was analyzed. A factorial ANOVA using course type, course delivery method, and student SES found no significant differences in final course grades when used to determine if course delivery methods were equally effective for students of low and not low SES taking STEM course types. Additionally, three chi-square goodness-of-fit tests were used to investigate for differences in enrollment, course completion and course passing status by SES, course type, and course delivery method. The findings of the chi-square tests indicated that: (a) there were significant differences in enrollment by SES and course delivery methods for the Engineering/Technology, Math, and overall course types but not for the Natural Science course type and (b) there were no significant differences in course completion status and course passing status by SES and course types overall and SES and course delivery methods overall. However, there were statistically significant but weak relationships between course passing status, SES and the math course type as well as between course passing status, SES, and online and traditional course delivery methods. ^ The mixed findings in the study indicate that strides have been made in closing the theoretical gap in education and technology skills that may exist for students of different SES levels. MDC's course delivery and student support models may assist other institutions address student success in courses that necessitate students having some level of technology fluency. ^

Learning Data-Driven Models of Non-Verbal Behaviors for Building Rapport Using an Intelligent Virtual Agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness. Evidence-based patient-centered Brief Motivational Interviewing (BMI) interven- tions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary. Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems. To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].

Utilizing Traditional Cognitive Measures of Academic Preparation to Predict First-Year Science, Technology, Engineering, and Mathematics (STEM) Majors' Success in Math and Science Courses

For the past several years, U.S. colleges and universities have faced increased pressure to improve retention and graduation rates. At the same time, educational institutions have placed a greater emphasis on the importance of enrolling more students in STEM (science, technology, engineering and mathematics) programs and producing more STEM graduates. The resulting problem faced by educators involves finding new ways to support the success of STEM majors, regardless of their pre-college academic preparation. The purpose of my research study involved utilizing first-year STEM majors’ math SAT scores, unweighted high school GPA, math placement test scores, and the highest level of math taken in high school to develop models for predicting those who were likely to pass their first math and science courses. In doing so, the study aimed to provide a strategy to address the challenge of improving the passing rates of those first-year students attempting STEM-related courses. The study sample included 1018 first-year STEM majors who had entered the same large, public, urban, Hispanic-serving, research university in the Southeastern U.S. between 2010 and 2012. The research design involved the use of hierarchical logistic regression to determine the significance of utilizing the four independent variables to develop models for predicting success in math and science. The resulting data indicated that the overall model of predictors (which included all four predictor variables) was statistically significant for predicting those students who passed their first math course and for predicting those students who passed their first science course. Individually, all four predictor variables were found to be statistically significant for predicting those who had passed math, with the unweighted high school GPA and the highest math taken in high school accounting for the largest amount of unique variance. Those two variables also improved the regression model’s percentage of correctly predicting that dependent variable. The only variable that was found to be statistically significant for predicting those who had passed science was the students’ unweighted high school GPA. Overall, the results of my study have been offered as my contribution to the literature on predicting first-year student success, especially within the STEM disciplines.

Learning data-driven models of non-verbal behaviors for building rapport using an intelligent virtual agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness.^ Evidence-based patient-centered Brief Motivational Interviewing (BMI) interventions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary.^ Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems.^ To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].^

Political Strategy, Leadership, and Policy Entrepreneurship in Japanese Defense Policy and Politics: A Comparison of Three Prime Ministerships

Since the end of the Cold War, Japan’s defense policy and politics has gone through significant changes. Throughout the post cold war period, US-Japan alliance managers, politicians with differing visions and preferences, scholars, think tanks, and the actions of foreign governments have all played significant roles in influencing these changes. Along with these actors, the Japanese prime minister has played an important, if sometimes subtle, role in the realm of defense policy and politics. Japanese prime ministers, though significantly weaker than many heads of state, nevertheless play an important role in policy by empowering different actors (bureaucratic actors, independent commissions, or civil actors), through personal diplomacy, through agenda-setting, and through symbolic acts of state. The power of the prime minister to influence policy processes, however, has frequently varied by prime minister. My dissertation investigates how different political strategies and entrepreneurial insights by the prime minister have influenced defense policy and politics since the end of the Cold War. In addition, it seeks to explain how the quality of political strategy and entrepreneurial insight employed by different prime ministers was important in the success of different approaches to defense. My dissertation employs a comparative case study approach to examine how different prime ministerial strategies have mattered in the realm of Japanese defense policy and politics. Three prime ministers have been chosen: Prime Minister Hashimoto Ryutaro (1996-1998); Prime Minister Koizumi Junichiro (2001-2006); and Prime Minister Hatoyama Yukio (2009-2010). These prime ministers have been chosen to provide maximum contrast on issues of policy preference, cabinet management, choice of partners, and overall strategy. As my dissertation finds, the quality of political strategy has been an important aspect of Japan’s defense transformation. Successful strategies have frequently used the knowledge and accumulated personal networks of bureaucrats, supplemented bureaucratic initiatives with top-down personal diplomacy, and used a revitalized US-Japan strategic relationship as a political resource for a stronger prime ministership. Though alternative approaches, such as those that have looked to displace the influence of bureaucrats and the US in defense policy, have been less successful, this dissertation also finds theoretical evidence that alternatives may exist.