This paper examines the capital - asset pricing model (CAPM) which has been extended with a factor for geo-political risk. I use monthly stock return data for all stocks listed on a major US exchange from January 1990 to December 2016 and utilize a Fama-Macbeth Regression with Newey-West standard errors to test the geo-political augmented Sharpe-Lintner CAPM. The paper first determines if increased sensitivity to geopolitical risk lead s to lower average returns and second assesses if geo-political risk as an explanatory variable is a significant enough to expose a failure of the CAPM to capture expected returns fully through beta. The results of our regressions do not confirm the hypothesis that firms with high sensitivities to geo-political risk have expressly different returns in the long run. Furthermore, our Fama-Macbeth regression does not find expressly significant average slopes for geo-political risk as a variable.

This thesis describes general function of biometric access systems and summarizes problems of their practical use. It also shows security risks of these systems. It defines basic terms, which are used in this area, describes kinds of errors and their representation. One part of this thesis deals with biometric method of fingerprints recognition. It explains fingerprints’ atomic basics, basic principles and processing of digital fingerprint image. Next part describes concrete biometric access system V-Station by Bioscrypt Inc. Besides basic description it focuses on technology of biometric sensor and algorithm, essential parts of biometric system. The thesis continues with security analysis of this concrete system. In this part I target on weak points of the system and I design possible attack on the system. In the last part of my thesis I designed laboratory exercise, which is supposed to be realized by student. It is composed it by several tasks to let students understand working with the system and attached software. At the same time, they have opportunity to think about system by themselves a make their own opinion about possibilities of the system. There are many pictures in this thesis to make term clear and to better understanding of problems of biometric security systems.

Level crossing times and their applications in finance are of importance, given certain threshold levels that represent the "desirable" or "sell" values of a stock. In this thesis, we make use of Wald's lemmas and various deep results from renewal theory, in the context of finance, in modelling the growth of a portfolio of stocks. Several models are employed .

The Cost of Feeling Good attempts to quantify the optimum portfolio returns of Socially Responsible Investment Funds and Dual-Purpose Portfolios. In order to meet the demands of investors who want to create a social impact and generate financial returns, investors can choose two methods. For the purpose of this study, the social returns were quantified and the financial returns were quantified using net present value. In every scenario, the socially responsible investment decision generated higher financial returns. Because of the immediate loss to an investor after choosing the DPP strategy, financially, the SRI fund appears to be the better approach for a financially driver investor. In terms of social returns, the DPP has a more clear impact on society. Measured as the charitable contribution given on an $1,000 investment, the socially responsible fund contributes far less to society on a per investor basis. Therefore, if an investor is interested in generating higher social returns and wants to be selective in terms of their charitable donation, they should choose the DPP model. In terms of tax brackets, investors in higher tax brackets have to generate higher financial returns on socially responsible investments in order to match the returns of a DPP. This is also true with investors who invest less in charity. Therefore, the investors that are in the highest tax bracket and contribute little to charity will need to generate far higher SRI returns according to the constructed theory. This finding is important to the growing millennial trend in sustainable investing.

This study examines the relationship between company management guidance, and ex-ante crash risk over the duration of 2008(Jan 2006-Dec 2009) financial crisis using the implied volatility skew, which is based upon ex-ante volatility implied by the pricing model developed by Black-Scholes (1973). The study finds that over the duration of this crisis period, management guidance decreases with a rise in ex-ante crash risk. Further, the study provides evidence on the relationship of management guidance and earnings volatility, and how that is affected by a firm's industry product concentration based on the Herfindahl-Hirschman Index (HHI) score.

The demands on maritime operations today are increasingly higher in terms of control, efficiency and cost. The margins for accidents and security incidents are therefore decreasing. In the area of ship safety the regulations, guidelines and methods have a history and culture of systematic research, development and implementation. In contrast, international security is highly politicized and therefore not as transparent. The result is that a tradition of ship security is not as well established. The overall aim of this thesis is to propose a method for ship security analysis that increases the overall safety of the crew and the ship. The objective is to develop a method that is systematic in order to ensure that assessment and response are complete and effective, and that the process is documented to provide evidence of decision-making. The method used is probabilistic risk assessment where quantitative analysis is central. The proposed approach is consistent with the requirements of maritime safety work. However, in the work here, the proposed methods are specifically tested for security cases. This is because hazards (without intent) and threats (with intent) evolve in different ways into risk. Therefore, they must be analysed differently in order to capture the causal relationship. The proposed approach consists of three steps: the first step consists of a threat description that documents qualitative and quantitative aspects that together describe how the threat most likely will act in relation to the ship’s vulnerability; the second step uses the threat description to define the system studied as well as the scenarios that collectively describe the harmful consequences; the third step evaluates the risk with tools from probabilistic risk assessment. The overall conclusion is that the proposed method brings the procedure and results of ship security analysis into the open and therefore allows for criticism, improvements and shared risk knowledge, not possible with less structured methods. The results also show that the calculated probabilities agree with available statistics, which indicates that the analysis succeeds in describing the central causal relationships of the scenarios modelled.

Submitted by Silvana Teresinha Dornelles Studzinski (sstudzinski) on 2016-03-17T15:55:04Z No. of bitstreams: 1 Iverson Farias Costa_.pdf: 1955231 bytes, checksum: 026a292f3b36f9d497620ffb02e502b4 (MD5) / Made available in DSpace on 2016-03-17T15:55:04Z (GMT). No. of bitstreams: 1 Iverson Farias Costa_.pdf: 1955231 bytes, checksum: 026a292f3b36f9d497620ffb02e502b4 (MD5) Previous issue date: 2012-03-29 / Nenhuma / A importância de um suprimento confiável de energia elétrica, para a sociedade industrial atual, é inquestionável. Em um centro de controle de uma rede elétrica, uma importante tarefa computacional é a Análise de Segurança. Nesta tarefa, uma contingência é saída de operação de um ou mais equipamentos, enquanto que a seleção de contingências é a determinação das contingências mais severas existentes no sistema. A despeito dos avanços tecnológicos atuais, uma análise de todas as contingências possíveis é impraticável. Neste trabalho, um método é apresentado para realizar, de forma eficiente, a seleção de contingências múltiplas. O problema é modelado como um problema de otimização combinatória, e é resolvido através de dois algoritmos genéticos. Um método robusto, que considera aspectos de fluxo de potência e tensão, é apresentado e testado em uma rede IEEE e em um sistema real de grande porte, considerando saídas duplas de linha. Os resultados apresentados, obtidos através da varredura de porções reduzidas do espaço de busca, demonstram uma acurácia próxima a 100%, quando comparados a um método exato. / The importance of a reliable supply of electricity to the industrial society is unquestionable. In a control center of an electrical utility, an important computational task is the Security Analysis. In this task, contingency is the out of operation of one or more devices, and contingencies selection is the determination of the most severe contingencies for the system. Despite the current technological advances, an analysis of all possible contingencies, for a real grid, is impracticable. In this work, a method to efficiently perform the selection of multiple contingencies is presented. The problem is modeled as a combinatorial optimization problem, and solved by two genetic algorithms. A robust method, which considers aspects of power flow and voltage, is presented and tested over an IEEE test system and a large real network, considering double outages of branches. The results presented, obtained with scans of reduced portions of search space, shows accuracy close to 100%, when compared with an exact method.

In order to assess the continuing imbalance of top executives between genders, I examine the effects of gender diversity within top management teams on firm risk, performance, and executive compensation. Capitalizing on previous analysis, I apply three unique differentiators. First, I utilize current data from 2012 to 2017 from Compustat, CRSP, and ExecuComp. Second, I provide a unique subset view on a firm and individual performance of female CEOs to examine executive compensation. Third, my scope of analysis expands to S&P Composite 1500 companies. I use separate models to estimate the effect of gender diversity on firm risk by examining a firm’s beta and standard deviation of daily returns, on firm performance by examining a firm’s Tobin’sQ, and lastly on executive compensation by examining an executive’s natural logarithm of total compensation. My findings suggest gender diversity among executives appears to have an immaterial effect on a firm’s risk and performance. In turn, I also find that female executives continue to receive less compensation than their male colleagues. However, I find an average female CEO receives a higher level of compensation than an average male CEO. Lastly, I find as gender diversity increases among executives, specifically CEOs, the compensation differences between genders decreases.

The role of electric power systems has grown steadily in both scope and importance over time making electricity increasingly recognized as a key to social and economic progress in many developing countries. In a sense, reliable power systems constitute the foundation of all prospering societies. The constant expansion in electric power systems, along with increased energy demand, requires that power systems become more and more complex. Such complexity results in much uncertainty which demands comprehensive reliability and security assessment to ensure reliable energy supply. Power industries in many countries are facing these challenges and are trying to increase the computational capability to handle the ever-increasing data and analytical needs of operations and planning. Moreover, the deregulated electricity markets have been in operation in a number of countries since the 1990s. During the deregulation process, vertically integrated power utilities have been reformed into competitive markets, with initial goals to improve market efficiency, minimize production costs and reduce the electricity price. Given the benefits that have been achieved by deregulation, several new challenges are also observed in the market. Due to fundamental changes to the electric power industry, traditional management and analysis methods cannot deal with these new challenges. Deterministic reliability assessment criteria still exists but it doesn’t satisfy the probabilistic nature of power systems. In the deterministic approach the worst case analysis results in excess operating costs. On the other hand, probabilistic methods are now widely accepted. The analytical method uses a mathematical formula for reliability evaluation and generates results more quickly but it needs accurate and a lot of assumptions and is not suitable for large and complex systems. Simulation based techniques take care of much uncertainty and simulates the random behavior of the system. However, it requires much computing power, memory and other computing resources. Power engineers have to run thousands of times domain simulations to determine the stability for a set of credible disturbances before dispatching. For example, security analysis is associated with the steady state and dynamic response of the power system to various disturbances. It is highly desirable to have real time security assessment, especially in the market environment. Therefore, novel analysis methods are required for power systems reliability and security in the deregulated environment, which can provide comprehensive results, and high performance computing (HPC) power in order to carry out such analysis within a limited time. Further, with the deregulation in power industry, operation control has been distributed among many organizations. The power grid is a complex network involving a range of energy resources including nuclear, fossil and renewable energy resources with many operational levels and layers including control centers, power plants and transmission and distribution systems. The energy resources are managed by different organizations in the electricity market and all these participants (including producers, consumers and operators) can affect the operational state of the power grid at any time. Moreover, adequacy analysis is an important task in power system planning and can be regarded as collaborative tasks, which demands the collaboration among the electricity market participants for reliable energy supply. Grid computing is gaining attention from power engineering experts as an ideal solution to the computational difficulties being faced by the power industry. Grid computing infrastructure involves the integrated and collaborative use of computers, networks, databases and scientific instruments owned and managed by multiple organizations. Grid computing technology offers potentially feasible support to the design and development of grid computing based infrastructure for power system reliability and security analysis. It can help in building infrastructure, which can provide a high performance computing and collaborative environment, and offer an optimal solution between cast and efficiency. While power system analysis is a vast topic, only a limited amount of research has been initiated in several places to investigate the applications of grid computing in power systems. This thesis will investigate probabilistic based reliability and security analysis of complex power systems in order to develop new techniques for providing comprehensive result with enormous efficiency. A review of existing techniques was conducted to determine the computational needs in the area of power systems. The main objective of this research is to propose and develop a general framework of computing grid and special grid services for probabilistic power system reliability and security assessment in the electricity market. As a result of this research, grid computing based techniques are proposed for power systems probabilistic load flow analysis, probabilistic small signal analysis, probabilistic transient stability analysis, and probabilistic contingencies analysis. Moreover, a grid computing based system is designed and developed for the monitoring and control of distributed generation systems. As a part of this research, a detailed review is presented about the possible applications of this technology in other aspects of power systems. It is proposed that these grid based techniques will provide comprehensive results that will lead to great efficiency, and ultimately enhance the existing computing capabilities of power companies in a cost-effective manner. At a part of this research, a small scale computing grid is developed which will consist of grid services for probabilistic reliability and security assessment techniques. A significant outcome of this research will be the improved performance, accuracy, and security of data sharing and collaboration. More importantly grid based computing will improve the capability of power system analysis in a deregulated environment where complex and large amounts of data would otherwise be impossible to analyze without huge investments in computing facilities.

The role of electric power systems has grown steadily in both scope and importance over time making electricity increasingly recognized as a key to social and economic progress in many developing countries. In a sense, reliable power systems constitute the foundation of all prospering societies. The constant expansion in electric power systems, along with increased energy demand, requires that power systems become more and more complex. Such complexity results in much uncertainty which demands comprehensive reliability and security assessment to ensure reliable energy supply. Power industries in many countries are facing these challenges and are trying to increase the computational capability to handle the ever-increasing data and analytical needs of operations and planning. Moreover, the deregulated electricity markets have been in operation in a number of countries since the 1990s. During the deregulation process, vertically integrated power utilities have been reformed into competitive markets, with initial goals to improve market efficiency, minimize production costs and reduce the electricity price. Given the benefits that have been achieved by deregulation, several new challenges are also observed in the market. Due to fundamental changes to the electric power industry, traditional management and analysis methods cannot deal with these new challenges. Deterministic reliability assessment criteria still exists but it doesn’t satisfy the probabilistic nature of power systems. In the deterministic approach the worst case analysis results in excess operating costs. On the other hand, probabilistic methods are now widely accepted. The analytical method uses a mathematical formula for reliability evaluation and generates results more quickly but it needs accurate and a lot of assumptions and is not suitable for large and complex systems. Simulation based techniques take care of much uncertainty and simulates the random behavior of the system. However, it requires much computing power, memory and other computing resources. Power engineers have to run thousands of times domain simulations to determine the stability for a set of credible disturbances before dispatching. For example, security analysis is associated with the steady state and dynamic response of the power system to various disturbances. It is highly desirable to have real time security assessment, especially in the market environment. Therefore, novel analysis methods are required for power systems reliability and security in the deregulated environment, which can provide comprehensive results, and high performance computing (HPC) power in order to carry out such analysis within a limited time. Further, with the deregulation in power industry, operation control has been distributed among many organizations. The power grid is a complex network involving a range of energy resources including nuclear, fossil and renewable energy resources with many operational levels and layers including control centers, power plants and transmission and distribution systems. The energy resources are managed by different organizations in the electricity market and all these participants (including producers, consumers and operators) can affect the operational state of the power grid at any time. Moreover, adequacy analysis is an important task in power system planning and can be regarded as collaborative tasks, which demands the collaboration among the electricity market participants for reliable energy supply. Grid computing is gaining attention from power engineering experts as an ideal solution to the computational difficulties being faced by the power industry. Grid computing infrastructure involves the integrated and collaborative use of computers, networks, databases and scientific instruments owned and managed by multiple organizations. Grid computing technology offers potentially feasible support to the design and development of grid computing based infrastructure for power system reliability and security analysis. It can help in building infrastructure, which can provide a high performance computing and collaborative environment, and offer an optimal solution between cast and efficiency. While power system analysis is a vast topic, only a limited amount of research has been initiated in several places to investigate the applications of grid computing in power systems. This thesis will investigate probabilistic based reliability and security analysis of complex power systems in order to develop new techniques for providing comprehensive result with enormous efficiency. A review of existing techniques was conducted to determine the computational needs in the area of power systems. The main objective of this research is to propose and develop a general framework of computing grid and special grid services for probabilistic power system reliability and security assessment in the electricity market. As a result of this research, grid computing based techniques are proposed for power systems probabilistic load flow analysis, probabilistic small signal analysis, probabilistic transient stability analysis, and probabilistic contingencies analysis. Moreover, a grid computing based system is designed and developed for the monitoring and control of distributed generation systems. As a part of this research, a detailed review is presented about the possible applications of this technology in other aspects of power systems. It is proposed that these grid based techniques will provide comprehensive results that will lead to great efficiency, and ultimately enhance the existing computing capabilities of power companies in a cost-effective manner. At a part of this research, a small scale computing grid is developed which will consist of grid services for probabilistic reliability and security assessment techniques. A significant outcome of this research will be the improved performance, accuracy, and security of data sharing and collaboration. More importantly grid based computing will improve the capability of power system analysis in a deregulated environment where complex and large amounts of data would otherwise be impossible to analyze without huge investments in computing facilities.