An autoregressive conditional filtering process to remove intraday seasonal volatility and its application to testing the noisy rational expectations model

We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.

An Autoregressive Conditional Filtering Process to remove Intraday Seasonal Volatility and its Application to Testing the Noisy Rational Expectations Model

We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.

Patterns of Root Dynamics in Mangrove Forests Along Environmental Gradients in the Florida Coastal Everglades, USA

Patterns of mangrove vegetation in two distinct basins of Florida Coastal Everglades (FCE), Shark River estuary and Taylor River Slough, represent unique opportunities to test hypotheses that root dynamics respond to gradients of resources, regulators, and hydroperiod. We propose that soil total phosphorus (P) gradients in these two coastal basins of FCE cause specific patterns in belowground biomass allocation and net primary productivity that facilitate nutrient acquisition, but also minimize stress from regulators and hydroperiod in flooded soil conditions. Shark River basin has higher P and tidal hydrology with riverine mangroves, in contrast to scrub mangroves of Taylor basin with more permanent flooding and lower P across the coastal landscape. Belowground biomass (0–90 cm) of mangrove sites in Shark River and Taylor River basins ranged from 2317 to 4673 g m-2, with the highest contribution (62–85%) of roots in the shallow root zone (0–45 cm) compared to the deeper root zone (45–90 cm). Total root productivity did not vary significantly among sites and ranged from 407 to 643 g m-2 y-1. Root production in the shallow root zone accounted for 57–78% of total production. Root turnover rates ranged from 0.04 to 0.60 y-1 and consistently decreased as the root size class distribution increased from fine to coarse roots, indicating differences in root longevity. Fine root biomass was negatively correlated with soil P density and frequency of inundation, whereas fine root turnover decreased with increasing soil N:P ratios. Lower P availability in Taylor River basin relative to Shark River basin, along with higher regulator and hydroperiod stress, confirms our hypothesis that interactions of stress from resource limitation and long duration of hydroperiod account for higher fine root biomass along with lower fine root production and turnover. Because fine root production and organic matter accumulation are the primary processes controlling soil formation and accretion in scrub mangrove forests, root dynamics in the P-limited carbonate ecosystem of south Florida have a major controlling role as to how mangroves respond to future impacts of sealevel rise.

The influence of spirituality, race/ethnicity and religion on parent grief and mental health at one and three months after their infant's/child's death in the neonatal or pediatric intensive care unit

The death of an infant/child is one of the most devastating experiences for parents and immediately throws them into crisis. Spiritual and religious coping strategies may help parents with their loss. The purposes of this longitudinal study were to: (1) describe differences in bereaved parents' use of spiritual coping strategies across racial/ethnic and religious groups, mother/father dyads, and time—one (T1) and three (T2) months after the infant's/child's death in the neonatal (NICU) or pediatric intensive care unit (PICU), and (2) test the relationship between spiritual coping strategies and grief, mental health, and personal growth for mothers and fathers at T1 and T2. A sample of 126 Hispanic, Black/African American, and White parents of 119 deceased children completed the Spiritual Coping Strategies scale, Beck Depression Inventory-II, Impact of Events-Revised, Hogan Grief Reaction Checklist, and a demographic form at T1 and T2. Controlling for race and religion, spiritual coping was a strong predictor of lower grief, better mental health, and greater personal growth for mothers at T1 and T2 and lower grief for fathers at T1. The findings of this study will guide bereaved parents to effective strategies to help them cope with their early grief.

The employee satisfaction -performance link: A unit -level analysis

In this dissertation, I present an integrated model of organizational performance. Most prior research has relied extensively on testing individual linkages, often with cross-sectional data. In this dissertation, longitudinal unit-level data from 559 restaurants, collected over a one-year period, were used to test the proposed model. The model was hypothesized to begin with employee satisfaction as a key antecedent that would ultimately lead to improved financial performance. Several variables including turnover, efficiency, and guest satisfaction are proposed as mediators of the satisfaction-performance relationship. The current findings replicate and extend past research using individual-level data. The overall model adequately explained the data, but was significantly improved with an additional link from employee satisfaction to efficiency, which was not originally hypothesized. Management turnover was a strong predictor of hourly level team turnover, and both were significant predictors of efficiency. Full findings for each hypothesis are presented and practical organizational implications are given. Limitations and recommendations for future research are provided. ^

The effect of different instructional groupings on student achievement and attitudes from a computer-based interactive videodisk biology unit

The purpose of this research study was to determine the effect of two different instructional groupings (cooperative and traditional whole-class) on student achievement and attitudes using a computer-based interactive videodisc biology unit. The subjects were 64 high school biology students assigned to two heterogeneous experimental groups, randomly selected from two preassigned summer school biology classes, one honors, the other regular. A two-group, posttest-only, control group experimental research design was utilized. Achievement at three cognitive levels and attitudes towards science laserdisc instruction were measured at the conclusion of the study. The cooperative group consistently outperformed the traditional group in achievement posttest scores. Factorial ANOVA on total (overall) achievement scores indicated that subjects in cooperative groups significantly outperformed those in the traditional group, and also that the instructional group, class level, and gender interacted in an ordinal fashion to make a significant difference in how female and male subjects were affected by the treatments depending on their class (aptitude) level. Regular level females and honors level males performed much better when in cooperative groups, whereas group membership did not appear to make a difference for either honors level females or regular level males. A t-test comparing honors level males revealed that cooperative groups were close to being significantly better in total achievement posttest scores than their traditional group counterparts. Factorial MANOVA comparing the instructional groups at three cognitive levels found no significant difference. Analysis on the attitudes posttest data also revealed that subjects in cooperative groups demonstrated more positive attitudes towards science laserdisc instruction; however these differences were not found to be significant. Significant interactions in attitudes of females and males from different class levels had the opposite effect as achievement: honors level females and regular level males demonstrated more positive attitudes towards science laserdisc instruction when in cooperative groups, whereas group membership did not appear to make a difference for honors level males, and regular level females demonstrated the lowest attitudes ratings of any group when involved in cooperative groups. This contrast between achievement and attitudinal results suggests cross-gender interaction in traditionally defined gender roles.

The Development of a Hybrid Optimization Algorithm for the Evaluation and Optimization of the Asynchronous Pulse Unit

The effectiveness of an optimization algorithm can be reduced to its ability to navigate an objective function’s topology. Hybrid optimization algorithms combine various optimization algorithms using a single meta-heuristic so that the hybrid algorithm is more robust, computationally efficient, and/or accurate than the individual algorithms it is made of. This thesis proposes a novel meta-heuristic that uses search vectors to select the constituent algorithm that is appropriate for a given objective function. The hybrid is shown to perform competitively against several existing hybrid and non-hybrid optimization algorithms over a set of three hundred test cases. This thesis also proposes a general framework for evaluating the effectiveness of hybrid optimization algorithms. Finally, this thesis presents an improved Method of Characteristics Code with novel boundary conditions, which better characterizes pipelines than previous codes. This code is coupled with the hybrid optimization algorithm in order to optimize the operation of real-world piston pumps.