The primary aim of this study is to investigate the stock return volatility surrounding management earnings forecasts. Disclosure by managers of expected earnings are particularly important communications, and as such, it is important to understand the capital market implications surrounding them. In doing so, the research questions are essentially aimed at examining the stock return volatility, first, at the release of a management earnings forecast, and second, at the eventual announcement of the realised earnings for that period. The first test investigates whether there is an increase in volatility surrounding a management earnings forecast for those firms who release them compared to a matched-firm sample of firms without a management earnings forecast at that date, and then further examines that result based on different forecast antecedents and forecast characteristics. Next, this study tests, for firms who do release a management earnings forecast during the year, whether stock volatility is lower than firms who do not release a management earnings forecast at the eventual earnings announcement date. In brief, the evidence using the Garman and Klass [1980] ???best analytic scale-invariant estimator??? of volatility in an Australian context, between 1993 and 2003, finds that stock return volatility is greater for bad news forecasts, forecasts of low specificity, and forecasts issued by firms perceived ex ante as being of lower credibility using both permutation analysis and modelling daily volatility. At the earnings announcement date, however, there is no evidence that stock return volatility is lower for firms that issue management earnings forecasts during the year. Overall, this result challenges the information asymmetry argument in the literature that disclosure will reduce volatility in the long-run.

Research Doctorate - Doctor of Philosophy (PhD) / Mobile agents are programs that travel autonomously through a computer network in order to perform some computation or gather information on behalf of a human user or an application. In the last several years numerous applications of mobile agents have emerged, including e-commerce. However, mobile agent paradigm introduces a number of security threats both to the agents themselves and to the servers that they visit. This thesis gives an overview of the main security issues related to the mobile agent paradigm. The first part of the thesis focuses on security of mobile agent itself. In this part, we propose a new coupling technique based on trust as a social control to work together with existing traditional security mechanisms. It relies on the “reputation” of the hosts in the itinerary and ensures that the agent succeeds in accomplishing its task with a high probability. Due to the fact that the coupling technique requires an agent’s itinerary to be known in advance, we introduce two new concepts: a “Scout mobile agent”, whose primary purpose is to determine the itinerary required for accomplishing a given task, and a “Routed mobile agent”, which operates with an itinerary known in advance. This enables the Routed agent to incorporate various security mechanisms, including our new coupling technique. Our Routed agent technique is also applicable independently of the Scout agent, whenever the itinerary and the trust values of the platforms in the itinerary are known. We also proposed a Petrol Station as an entity that would provide a service to other entities, in the form of certifying mobile agents and equipping them with safe itinerary based on trust score and applying the Routed agent. In the second part of the thesis, we shed some light on the security of mobile agent platforms as it is considered more critical than the security of agents. In particular, we consider a scenario where a platform hosts a database containing confidential individual information and allows mobile agentstoquery the data base. This mobile agent maybe behave maliciously which is similar to an intruder in the Statistical Disclosure Control(SDC), where measuring disclosure risk is still considered as a difficult and only partly solved problem[111]. We introduce a scenario that is not adequately covered by any of the previous discloser risk measures. Shannon’s entropy can be considered a satisfactory measure for the disclosure risk that is related to the exact compromise. However, in the case of approximate compromise, we argue that Shannon’s entropy does not express precisely the intruder’s knowledge about a particular confidential value. We introduce a novel disclosure risk measure that is based on Shannon’s entropy but covers both exact and approximate compromise. The main advantage of our measure over previously proposed measures that it gives careful consideration to the attribute values in addition to the probabilities with which the values occur. We use a dynamic programming algorithm to calculate the disclosure risk for various levels of approximate compromise. Importantly, our proposed measure is independent of the applied SDC technique. Finally, we show how this measure can be used to evaluate the security mechanisms for protecting privacy in statistical databases and data mining. We conduct extensive experiments and apply our proposed security measure to three different data sets protected by three different SDC techniques, namely Sampling, Query Restriction, and Noise Addition.

Thesis (Ph.D.)--Hong Kong Baptist University, 2007. / Adviser: Zhijun Lin. Includes bibliographical references.

Thesis (M.A.)--University of Toronto, 2004. / Adviser: Margaret Schneider.

Thesis (Ph.D.)--Columbia University, 2001. / Includes bibliographical references.

Thesis (M.S.W.)--Smith College School for Social Work, Northampton, Mass., 2007 / Thesis submitted in partial fulfillment for the degree of Master of Social Work. Includes bibliographical references (leaves 82-88).

Thesis (Ph. D.)--University of North Texas, May, 2008. / Title from title page display. Includes bibliographical references.

Thesis (Ph. D.)--University of Washington, 1991. / Vita. Includes bibliographical references (leaves [129]-137).

Thesis (M. Phil.)--University of Hong Kong, 2007. / Title proper from title frame. Also available in printed format.

Thesis (Ph.D.)--Michigan State University. Media and Information Studies , 2008. / Title from PDF t.p. (viewed on July 2, 2009) Includes bibliographical references (p. 108-123). Also issued in print.