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. ^

Perceptions of French and Creole Among First-Generation Adult Haitian English Language Learners

Context: Due to a unique combination of factors, outdoor athletes in the Southeastern United States are at high risk of lightning deaths and injuries. Lightning detection methods are available to minimize lightning strike victims. Objective: Becoming aware of the risk factors that predispose athletes to lightning strikes and determining the most reliable detection method against hazardous weather will enable Certified Athletic Trainers to develop protocols that protect athletes from injury. Data Sources: A comprehensive literature review of Medline and Pubmed using key words: lightning, lightning risk factors, lightning safety, lightning detection, and athletic trainers and lightning was completed. Data Synthesis: Factors predisposing athletes to lighting death or injury include: time of year, time of day, the athlete’s age, geographical location, physical location, sex, perspiration level, and lack of education and preparedness by athletes and staff. Although handheld lightning detectors have become widely accessible to detect lightning strikes, their performance has not been independently or objectively confirmed. There is evidence that these detectors inaccurately detect strike locations by recording false strikes and not recording actual strikes. Conclusions: Lightning education and preparation are two factors that can be controlled. Measures need to be taken by Certified Athletic Trainers to ensure the safety of athletes during outdoor athletics. It is critical for athletic trainers and supervising staff members to become fully aware of the risks of lightning strikes in order to most effectively protect everyone under their supervision. Even though lightning detectors have been manufactured in an attempt to minimize death and injuries due to lightning strikes, none of the detectors have been proven to be 100% effective. Educating coaches, athletes, and parents on the risks of lightning and the detection methods available, while implementing an emergency action plan for lightning safety, is crucial to ensure the well being of the student-athlete population.

Generational Differences in Work Attitudes: Evidence from the Hospitality Industry

Our understanding of employee attitudes and their impact on business outcomes has been further complicated in recent years by the newest cohort of service workers. Known as Generation Y (Gen Y), they appear to approach employment in a manner different to that of their predecessors. A review of the academic literature reveals little empirical evidence to support an appropriate understanding of the impact of such difference. This paper provides an overview of a large-scale study into generational differences in employee attitudes and reports on the preliminary data analysis of a survey of over 900 hospitality employees. The most important initial finding from the data analysis is that, on the whole, Gen Y employees have lower scores on those constructs that an organization should be attempting to maximize. Non-Gen Y employees are more satisfied with their jobs, more engaged and more affectively committed to the organization they work for than their Gen Y counterparts, amongst a range of other important constructs. Conversely, Gen Y employees display higher scores onthe constructs that an organization would want to minimize in its staff. Gen Y employees are more likely to be planning to quit their jobs, are more likely to perform poorly if their co-workers are doing so, and are also more likely to switch jobs for no particular reason. The discussion covers implications for management as well as directions for future research.

Ethnic identity, self-esteem and academic factors in second -generation post-1970 Jamaican immigrants

Immigrants from Jamaica represent the largest number of migrants to the United States from the English speaking Caribbean. Research indicates that of all Caribbean immigrants they are most likely to retain the ethnic identity of their home country for the longest period of time. This dissertation explored the nature of ethnic identity and sought to determine its impact upon the additional variables of self-esteem and academic factors. A secondary analysis was carried out using data collected in the Spring of 1992 by Portes and Rumbaut on the children of immigrants attending the eighth and ninth grades in local schools in San Diego and southern Florida. A sample of 151 second-generation Jamaican immigrants was selected from the data set. ^ Six hypotheses yielded mixed results. Both parents who have a Jamaican ethnic identity present in the household are the best predictor Jamaican youth who retain a Jamaican ethnic identity. It was expected that ethnic identity would be a predictor of positive academic factors. The study showed that ethnic identity was not associated with one of the academic factors which were examined: help given with homework. ^ Neither family economic status nor parents' level of education played a significant role in the retention of Jamaican identity. Other findings were that there was no mean difference in the self-esteem scores of respondents who had similar ethnic identities to their parents and those who did not. There was also no difference found in the academic factors of either group. The study also showed that there was a small correlation between parent-child conflict and self-esteem. Specifically, the study found that the higher the conflict between youth and their parents, the lower the self-esteem of the youth. Finally it found that time lived in the U.S. was the best predictor of a higher GPA and it was also related to lower self-esteem. ^ Surprisingly, the study found that the relationship between ethnic identity and SES was the opposite of what was expected in that it found that SES was higher when there was no Jamaican identity. ^