Behavior of realized volatility and correlation in exchange markets

We study time-varying realized volatility and related correlation measures as proxies for the true volatility and correlation. We investigate measures of Two-Scale realized Absolute Volatility (TSAV) and correlation (TSACORxy) which are helpful to cope effectively with the problem of market microstructure effects at very high frequency financial time series. The measures are constructed based on subsampling and averaging method so that they possess rather less bias even in presence of market microstructure noise. Absolute transformation of return values has been proved in literature to be more robust than squared transformation when considering large values. With respect to some stylized facts of markets, realized squared correlation does not display dynamic behavior. Motivated by robustness of realized absolute volatility, we study an alternative measure of correlation, built on absolute-transformed volatility. This measure of correlation exhibits experimentally some dynamics and hence some predictability capability on minute-by-minute frequency exchange market data. We show that the distribution of realized correlation series computed based on TSACORxy tends to comply a rightward asymmetric shape implying that upside co-movements are greater than downside ones. Moreover we study the association between realized volatility and correlation. According to the two-scale measure, our findings empirically suggest that when returns in Euro/USD exchange rate are highly volatile, the relation between Euro/USD and Euro/GBP exchange markets is strong, and when Euro/USD calms down, the relationship relaxes.Realized Volatility and Correlation, Long Memory, Scaling Law, Self-Similarity Dimension, Market Microstructure Effects.

Soap Opera Viewers\u27 Perceptions of the Real World

The frequency of occurrence on typical soap operas of incidents such as homicide, infidelity, and mental breakdown is much greater than is the case in real life. Also, various occupations (e.g., medical profession, legal profession) are overrepresented in these programs. The present study investigated the extent to which heavy soap opera viewers are influenced by these representations. Specifically, the differences between long term soap opera viewers’ and non-soap opera viewers’ perceptions about people and events in the real world were investigated. The subjects’ perceptions of the frequency of occurrences in the general population of such events as divorce, extramarital affairs, serious accidents, deception, having illegitimate children, death by homicide, being institutionalized, working in the medical profession, and being a lawyer were measured utilizing standard survey techniques. Also, the subjects’ estimates of the potential likelihood of future personal involvement in such events were measured. Results indicated that with respect to the probability of having extramarital affairs, nonviewers are more likely to anticipate being unfaithful than viewers [t(98) = -1.94, p \u3c.05]. Also, female nonviewers are more likely to predict that they will be sexually assaulted than female viewers [t(98) = -2.23, p \u3c.05]. No other statistically significant results were found. The results of this study provide no strong evidence that viewing soap operas directly affects viewers conceptions of reality

She Speaks Her Truth: Black Female Self-Empowerment in African-American Centric Texts

A Master\u27s Portfolio that looks into African-American Women in African-American literature and theatrical works

Lewis Online Travel System: Preparer's/Traveler's Manual, Release 1.0

The Lewis Online Travel System (LOTS) is a menu-driven interactive application that automates nearly all of the functions associated with government travel. The purpose of this manual is to provide LOTS users with concise instructions for using the computerized application. As such, it will not go into the details of travel regulations

Faculty Experiences Of Implementing Co-Teaching Strategies

Co-teaching is defined as two or more certified teachers working together to meet the needs of the diverse learners in their classroom, especially students with disabilities. Co-teaching is a widely implemented method used in public schools to educate children with and without disabilities in the general education setting to comply with state and national legislation requirements. There are six commonly used co-teaching strategies and approaches: one teach, one observe; one teach, one assist; parallel teaching; station teaching; alternative teaching; and team teaching. The research questions asked and answered were: What approach is most widely used and most effective at the secondary level? And what are the teacher’s perception of students with disabilities in the general education and co-teaching setting? Data was collected via surveys from high school and middle school general and special education teachers in the researcher’s school district. Data found that one teach, one assist was reported as the most used strategy among secondary teachers in the researcher’s school district. Additionally, teacher perspectives on students with disabilities in their classrooms were examined with primarily positive perceptions. A professional development seminar was created, and handouts were made to disseminate to staff outlining the findings and the most effective co-teaching strategies. A plan for coaching, with resources, was created for continued teacher support and education. Keywords: co-teaching, special education, co-teaching strategies, pre-professional teacher training, academic achievement, coaching, professional development, shared expectations, teamwork, student success, collaboration

Algorithms for Spectral Analysis of Irregularly Sampled Time Series

In this paper, we present a spectral analysis method based upon least square approximation. Our method deals with nonuniform sampling. It provides meaningful phase information that varies in a predictable way as the samples are shifted in time. We compare least square approximations of real and complex series, analyze their properties for sample count towards infinity as well as estimator behaviour, and show the equivalence to the discrete Fourier transform applied onto uniformly sampled data as a special case. We propose a way to deal with the undesirable side effects of nonuniform sampling in the presence of constant offsets. By using weighted least square approximation, we introduce an analogue to the Morlet wavelet transform for nonuniformly sampled data. Asymptotically fast divide-and-conquer schemes for the computation of the variants of the proposed method are presented. The usefulness is demonstrated in some relevant applications.