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.

Collective bargaining and faculty unionization: An administrative perspective

The purpose of this qualitative case study was to gain insight into the perspectives of experienced higher education administrators regarding faculty unionization, the collective bargaining process, and the interpersonal relationships between higher education faculty members and administrators. ^ The primary method of data collection was semi-structured face to face interviews with nine administrators from two community colleges and two universities in the south Florida area. All of the study participants worked with unionized faculty members and had direct experience participating in bargaining negotiations. ^ Upon the completion of each interview, the researcher listened to the taped audio recording of the interview several times and then transcribed all of the information from the audiotape into a Word file. Data collection and analysis for each participant were performed concurrently. Using a modified concept mapping approach, the research questions were written on large yellow sticky notes and placed in the middle of a wall in the researcher’s home with nine descriptive categorical themes written on smaller sticky notes placed around the study questions. The highlighted quotes and key phrases were cut from each transcript and placed under each of the descriptive categories. Over the course of a few months repeatedly reviewing the research questions that guided this study, the theory of symbolic interactionism, and relevant literature the categorical descriptive themes were refined and condensed into five descriptive themes. ^ Study findings indicated that the administrators: (a) must have a clear understanding of what it is that the faculty does to be an effective representative at the bargaining table, (b) experienced role ambiguity and role strain related to a lack of understanding as to their role at the bargaining table and a lack of organizational support, (c) were not offered any type of training in preparation for bargaining, (d) perceived a definite “us versus them” mentality between faculty and administration, and (e) saw faculty collective bargaining at public institutions of higher education in Florida as ineffectual. ^

7 Day advertising countdown to an Florida International University School of Medicine

Quotes and headlines for FLorida International University 's 7 day advertising countdown to the FLorida International University School of Medicine.

The Front Office Manager: Key To Hotel Communications

The Front Office Manager: Key to Hotel Communications is a written study by Denney G. Rutherford, Department of Hotel and Restaurant Administration, College of Business and Economics at Washington State University. In it he initially observes, “Since the front office manager is usually viewed as the key to the efficient and orderly operation of a hotel, the author has researched the job and activities of this individual in an attempt to provide data about an area which he says was "intuitively known" but never "empirically explored." “Current literature implies that the activities of the front office are so important to the daily operations of the hotel that it occupies a preeminent position among other departments,” Rutherford says. He also references, Gray and Liguori, who describe the front office as: “the nerve center of the hote1,” echoing an early work by Heldenbrand indicating that it “becomes a sort of listening post for management.” The quotes are cited. The primary stage of the article relies on a seven-page, two-part questionnaire, which was used to collect data regarding the FOM – front office manager - position. Even though the position is considered a crucial one, it seems there is a significant lack of pragmatic data regarding it. Rutherford graphs the studies. Good communication skills are imperative. “Other recent research has suggested that the skills of effective communication are among the most vital a manager at any level can bring to his/her endeavors in the service industries,” Rutherford notes. He provides a detailed – front office communications model – to illustrate the functions. In, Table 4, for example - Office Manager as Facilitator – Rutherford provides Likert Rating Scale values for a comprehensive list of front office tasks. Rutherford informs you that the communicative skills of a front office manager flow across the board, encompassing variables from guest relation exchanges to all the disparate components of employee relations. Not withstanding and compared to technical knowledge, such as computer and fiscal skills, Rutherford suggests: “The most powerful message derived from analysis of the data on the FOM's job is that communication in its various forms is clearly central to the successful mission of the front office.”

Travel Marketing: Industry Relationships and Benefits

In the discussion - Travel Marketing: Industry Relationships and Benefits - by Andrew Vladimir, Visiting Assistant Professor, School of Hospitality Management at Florida International University, the author initially states: “A symbiotic relationship exists among the various segments of the travel and tourism industry. The author has solicited the thinking of 37experts and leaders in the field in a book dealing with these relationships and how they can be developed to benefit the industry. This article provides some salient points from those contributors.” This article could be considered a primer on networking for the hospitality industry. It has everything to do with marketing and the relationships between varied systems in the field of travel and tourism. Vladimir points to instances of success and failure in marketing for the industry at large. And there are points of view from thirty-seven contributing sources here. “Miami Beach remains a fitting example of a leisure product that has been unable to get its act together,” Vladimir shares a view. “There are some first class hotels, a few good restaurants, alluring beaches, and a splendid convention center, but there is no synergism between them, no real affinity, and so while visitors admire the Fontainebleau Hilton and enjoy the food at Joe's Stone Crabs, the reputation of Miami Beach as a resort remains sullied,” the author makes a point. In describing cohesiveness between exclusive systems, Vladimir says, “If each system can get a better understanding of the inner workings of neighboring related systems, each will ultimately be more successful in achieving its goals.” The article is suggesting that exclusive systems aren’t really exclusive at all; or at least they shouldn’t be. In a word – competition – drives the market, and in order for a property to stay afloat, aggressive marketing integrated with all attendant resources is crucial. “Tisch [Preston Robert Tisch, currently – at the time of this writing - the Postmaster General of the United States and formerly president of Lowe’s Hotels and the New York Visitors and Convention Bureau], in talking about the need for aggressive marketing says: “Never...ever...take anything for granted. Never...not for a moment...think that any product or any place will survive strictly on its own merits.” Vladimir not only sources several knowledgeable representatives in the field of hospitality and tourism, but he also links elements as disparate as real estate, car rental, cruise and airlines, travel agencies and traveler profiles to illustrate his points on marketing integration. In closing, Vladimir quotes the Honorable Donna Tuttle, Undersecretary of Commerce for Travel and Tourism, “Uniting the components of this industry in an effective marketing coalition that can compete on an equal footing with often publicly-owned foreign tourism conglomerates and multi-national consortia must be a high priority as the United States struggles to maintain and expand its share of a rapidly changing global market.”

Three essays on the microstructure of exchange traded funds

Exchange traded funds (ETFs) have increased significantly in popularity since they were first introduced in 1993. However, there is still much that is unknown about ETFs in the extant literature. This dissertation attempts to fill gaps in the ETF literature by using three related essays. In these three essays, we compare ETFs to closed ended mutual funds (CEFs) by decomposing the bid-ask spread into its three components; we look at the intraday shape of ETFs and compare it to the intraday shape of equities as well as examine the co-integration factor between ETFs on the London Stock Exchange and the New York Stock Exchange; we also examine the differences between leveraged ETFs and unleveraged ETFs by analyzing the impact of liquidity and volatility. These three essays are presented in Chapters 1, 2, and 3, respectively. ^ Chapter one uses the Huang and Stoll (1997) model to decompose the bid-ask spread in CEFs and ETFs for two distinct periods—a normal and a volatile period. We show a higher adverse selection component for CEFs than for ETFs without regard to volatility. However, both ETFs and CEFs increased in magnitude of the adverse selection component in the period of high volatility. Chapter two uses a mix of the Werner and Kleidon (1993) and the Hupperets and Menkveld (2002) methods to get the intraday shape of ETFs and analyze co-integration between London and New York trading. We find two different shapes for New York and London ETFs. There also appears to be evidence of co-integration in the overlapping two-hour trading period but not over the entire trading day for the two locations. The third chapter discusses the new class of ETFs called leveraged ETFs. We examine the liquidity and depth differences between unleveraged and leveraged ETFs at the aggregate level and when the leveraged ETFs are classified by the leveraged multiples of -3, -2, -1, 2, and 3, both for a normal and a volatile period. We find distinct differences between leveraged and unleveraged ETFs at the aggregate level, with leveraged ETFs having larger spreads than unleveraged ETFs. Furthermore, while both leveraged and unleveraged ETFs have larger spreads in high volatility, for the leveraged ETFs the change in magnitude is significantly larger than for the unleveraged ETFs. Among the multiples, the -2 leveraged ETF is the most pronounced in its liquidity characteristics, more so in volatile times. ^