Essays on risk aversion, diversification and non -participation

My dissertation consists of three essays. The central theme of these essays is the psychological factors and biases that affect the portfolio allocation decision. The first essay entitled, “Are women more risk-averse than men?” examines the gender difference in risk aversion as revealed by actual investment choices. Using a sample that controls for biases in the level of education and finance knowledge, there is evidence that when individuals have the same level of education, irrespective of their knowledge of finance, women are no more risk-averse than their male counterparts. However, the gender-risk aversion relation is also a function of age, income, wealth, marital status, race/ethnicity and the number of children in the household. The second essay entitled, “Can diversification be learned ?” investigates if investors who have superior investment knowledge are more likely to actively seek diversification benefits and are less prone to allocation biases. Results of cross-sectional analyses suggest that knowledge of finance increases the likelihood that an investor will efficiently allocate his direct investments across the major asset classes; invest in foreign assets; and hold a diversified equity portfolio. However, there is no evidence that investors who are more financially sophisticated make superior allocation decisions in their retirement savings. The final essay entitled, “The demographics of non-participation ”, examines the factors that affect the decision not to hold stocks. The results of probit regression models indicate that when individuals are highly educated, the decision to not participate in the stock market is less related to demographic factors. In particular, when individuals have attained at least a college degree and have advanced knowledge of finance, they are significantly more likely to invest in equities either directly or indirectly through mutual funds or their retirement savings. There is also evidence that the decision not to hold stocks is motivated by short-term market expectations and the most recent investment experience. The findings of these essays should increase the body of research that seeks to reconcile what investors actually do (positive theory) with what traditional theories of finance predict that investors should do (normative theory).

Formal modeling and analysis techniques for high level Petri nets

Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. ^ There are two issues in using HLPNs—modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. ^ For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. ^ For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. ^ The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.^

Reducing Health Disparities: Medical advice and health behavior of minorities with diabetes

OBJECTIVE: to examine the relationships among reported medical advice, diabetes education, health insurance and health behavior of individuals with diabetes by race/ethnicity and gender. METHOD: Secondary analysis of data (N = 654) for adults ages > or = 21 years with diabetes acquired through the National Health and Nutrition Examination Survey (NHANES) for the years 2007-2008 comparing Black, non-Hispanics (BNH) and Mexican-Americans (MA) with White, non-Hispanics (WNH). The NHANES survey design is a stratified, multistage probability sample of the civilian noninstitutionalized U.S. population. Sample weights were applied in accordance with NHANES specifications using the complex sample module of IBM SPSS version 18. RESULTS: The findings revealed statistical significant differences in reported medical advice given. BNH [OR = 1.83 (1.16, 2.88), p = 0.013] were more likely than WNH to report being told to reduce fat or calories. Similarly, BNH [OR = 2.84 (1.45, 5.59), p = 0.005] were more likely than WNH to report that they were told to increase their physical activity. Mexican-Americans were less likely to self-monitor their blood glucose than WNH [OR = 2.70 (1.66, 4.38), p < 0.001]. There were differences by race/ethnicity for reporting receiving recent diabetes education. Black, non-Hispanics were twice as likely to report receiving diabetes education than WNH [OR = 2.29 (1.36, 3.85), p = 0.004]. Having recent diabetes education increased the likelihood of performing several diabetes self-management behaviors independent of race. CONCLUSIONS: There were significant differences in reported medical advice received for diabetes care by race/ethnicity. The results suggest ethnic variations in patient-provider communication and may be a consequence of their health beliefs, patient-provider communication as well as length of visit and access to healthcare. These findings clearly demonstrate the need for government sponsored programs, with a patient-centered approach, augmenting usual medical care for diabetes. Moreover, the results suggest that public policy is needed to require the provision of diabetes education at least every two years by public health insurance programs and recommend this provision for all private insurance companies

Essays on Risk Aversion, Diversification and Non-Participation

My dissertation consists of three essays. The central theme of these essays is the psychological factors and biases that affect the portfolio allocation decision. The first essay entitled, “Are women more risk-averse than men?” examines the gender difference in risk aversion as revealed by actual investment choices. Using a sample that controls for biases in the level of education and finance knowledge, there is evidence that when individuals have the same level of education, irrespective of their knowledge of finance, women are no more risk-averse than their male counterparts. However, the gender-risk aversion relation is also a function of age, income, wealth, marital status, race/ethnicity and the number of children in the household. The second essay entitled, “Can diversification be learned?” investigates if investors who have superior investment knowledge are more likely to actively seek diversification benefits and are less prone to allocation biases. Results of cross-sectional analyses suggest that knowledge of finance increases the likelihood that an investor will efficiently allocate his direct investments across the major asset classes; invest in foreign assets; and hold a diversified equity portfolio. However, there is no evidence that investors who are more financially sophisticated make superior allocation decisions in their retirement savings. The final essay entitled, “The demographics of non-participation”, examines the factors that affect the decision not to hold stocks. The results of probit regression models indicate that when individuals are highly educated, the decision to not participate in the stock market is less related to demographic factors. In particular, when individuals have attained at least a college degree and have advanced knowledge of finance, they are significantly more likely to invest in equities either directly or indirectly through mutual funds or their retirement savings. There is also evidence that the decision not to hold stocks is motivated by short-term market expectations and the most recent investment experience. The findings of these essays should increase the body of research that seeks to reconcile what investors actually do (positive theory) with what traditional theories of finance predict that investors should do (normative theory).

The potential of solid phase microextraction (spme) for the recovery of explosives followed by gas and liquid chromatographic analysis

The potential of solid phase microextraction (SPME) in the analysis of explosives is demonstrated. A sensitive, rapid, solventless and inexpensive method for the analysis of explosives and explosive odors from solid and liquid samples has been optimized using SPME followed by HPLC and GC/ECD. SPME involves the extraction of the organic components in debris samples into sorbent-coated silica fibers, which can be transferred directly to the injector of a gas chromatograph. SPME/HPLC requires a special desorption apparatus to elute the extracted analyte onto the column at high pressure. Re suits for use of GC[ECD is presented and compared to the results gathered by using HPLC analysis. The relative effects of controllable variables including fiber chemistry, adsorption and desorption temperature, extraction time, and desorption time have been optimized for various high explosives.

The Use of Hyphenated Spectrometric Techniques for the Environmental Forensic Assessment of Non-Traditional Pollutants and Degradates in the Greater Florida Everglades

A comprehensive investigation of sensitive ecosystems in South Florida with the main goal of determining the identity, spatial distribution, and sources of both organic biocides and trace elements in different environmental compartments is reported. This study presents the development and validation of a fractionation and isolation method of twelve polar acidic herbicides commonly applied in the vicinity of the study areas, including e.g. 2,4-D, MCPA, dichlorprop, mecroprop, picloram in surface water. Solid phase extraction (SPE) was used to isolate the analytes from abiotic matrices containing large amounts of dissolved organic material. Atmospheric-pressure ionization (API) with electrospray ionization in negative mode (ESP-) in a Quadrupole Ion Trap mass spectrometer was used to perform the characterization of the herbicides of interest. The application of Laser Ablation-ICP-MS methodology in the analysis of soils and sediments is reported in this study. The analytical performance of the method was evaluated on certified standards and real soil and sediment samples. Residential soils were analyzed to evaluate feasibility of using the powerful technique as a routine and rapid method to monitor potential contaminated sites. Forty eight sediments were also collected from semi pristine areas in South Florida to conduct screening of baseline levels of bioavailable elements in support of risk evaluation. The LA-ICP-MS data were used to perform a statistical evaluation of the elemental composition as a tool for environmental forensics. A LA-ICP-MS protocol was also developed and optimized for the elemental analysis of a wide range of elements in polymeric filters containing atmospheric dust. A quantitative strategy based on internal and external standards allowed for a rapid determination of airborne trace elements in filters containing both contemporary African dust and local dust emissions. These distributions were used to qualitative and quantitative assess differences of composition and to establish provenance and fluxes to protected regional ecosystems such as coral reefs and national parks.

Formal Modeling and Analysis Techniques for High Level Petri Nets

Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. There are two issues in using HLPNs - modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.

Evaluation of the Evidential Value of the Elemental Composition of Glass, Ink and Paper by Laser-Based Micro-Spectrochemical Methods

Elemental analysis can become an important piece of evidence to assist the solution of a case. The work presented in this dissertation aims to evaluate the evidential value of the elemental composition of three particular matrices: ink, paper and glass. In the first part of this study, the analytical performance of LIBS and LA-ICP-MS methods was evaluated for paper, writing inks and printing inks. A total of 350 ink specimens were examined including black and blue gel inks, ballpoint inks, inkjets and toners originating from several manufacturing sources and/or batches. The paper collection set consisted of over 200 paper specimens originating from 20 different paper sources produced by 10 different plants. Micro-homogeneity studies show smaller variation of elemental compositions within a single source (i.e., sheet, pen or cartridge) than the observed variation between different sources (i.e., brands, types, batches). Significant and detectable differences in the elemental profile of the inks and paper were observed between samples originating from different sources (discrimination of 87 – 100% of samples, depending on the sample set under investigation and the method applied). These results support the use of elemental analysis, using LA-ICP-MS and LIBS, for the examination of documents and provide additional discrimination to the currently used techniques in document examination. In the second part of this study, a direct comparison between four analytical methods (µ-XRF, solution-ICP-MS, LA-ICP-MS and LIBS) was conducted for glass analyses using interlaboratory studies. The data provided by 21 participants were used to assess the performance of the analytical methods in associating glass samples from the same source and differentiating different sources, as well as the use of different match criteria (confidence interval (±6s, ±5s, ±4s, ±3s, ±2s), modified confidence interval, t-test (sequential univariate, p=0.05 and p=0.01), t-test with Bonferroni correction (for multivariate comparisons), range overlap, and Hotelling’s T2 tests. Error rates (Type 1 and Type 2) are reported for the use of each of these match criteria and depend on the heterogeneity of the glass sources, the repeatability between analytical measurements, and the number of elements that were measured. The study provided recommendations for analytical performance-based parameters for µ-XRF and LA-ICP-MS as well as the best performing match criteria for both analytical techniques, which can be applied now by forensic glass examiners.

Leakage Temperature Dependency Aware Real-Time Scheduling for Power and Thermal Optimization

Catering to society’s demand for high performance computing, billions of transistors are now integrated on IC chips to deliver unprecedented performances. With increasing transistor density, the power consumption/density is growing exponentially. The increasing power consumption directly translates to the high chip temperature, which not only raises the packaging/cooling costs, but also degrades the performance/reliability and life span of the computing systems. Moreover, high chip temperature also greatly increases the leakage power consumption, which is becoming more and more significant with the continuous scaling of the transistor size. As the semiconductor industry continues to evolve, power and thermal challenges have become the most critical challenges in the design of new generations of computing systems. In this dissertation, we addressed the power/thermal issues from the system-level perspective. Specifically, we sought to employ real-time scheduling methods to optimize the power/thermal efficiency of the real-time computing systems, with leakage/ temperature dependency taken into consideration. In our research, we first explored the fundamental principles on how to employ dynamic voltage scaling (DVS) techniques to reduce the peak operating temperature when running a real-time application on a single core platform. We further proposed a novel real-time scheduling method, “M-Oscillations” to reduce the peak temperature when scheduling a hard real-time periodic task set. We also developed three checking methods to guarantee the feasibility of a periodic real-time schedule under peak temperature constraint. We further extended our research from single core platform to multi-core platform. We investigated the energy estimation problem on the multi-core platforms and developed a light weight and accurate method to calculate the energy consumption for a given voltage schedule on a multi-core platform. Finally, we concluded the dissertation with elaborated discussions of future extensions of our research.