In this paper we use model-free estimates of daily exchange rate volatilities employing high-frequency intraday data, known as Realized Volatility, which is then forecasted with ARMA-models and used to produce one-day-ahead Value-at-Risk predictions. The forecasting accuracy of the method is contrasted against the more widely used ARCH-models based on daily squared returns. Our results indicate that the ARCH-models tend to underestimate the Value-at-Risk in foreign exchange markets compared to models using Realized Volatility

The aim of the thesis is to identify an appropriate model in forecasting Value-at-Risk on a morevolatile period than that one from which the model is estimated. We estimate 1-day-ahead and10-days-ahead Value-at-Risk on a number of exchange rates. The Value-at-Risk estimates arebased on three models combined with three distributional assumptions of the innovations, andthe evaluations are made with Kupiec's (1995) test for unconditional coverage. The data rangesfrom January 1st 2006 through June 30th 2011. The results suggest that the GARCH(1,1) andGJR-GARCH(1,1) with normally distributed innovations are models adequately capturing theconditional variance in the series.

Competitive Bidding, Competitive Sealed Proposal, construction management agency, construction management at risk, Design-Build, Design-Build-Bridging, and job order contracting are seven project delivery methods that are commonly used in the state of Texas today. This paper empirically compares the cost, schedule, and change order management performance of these project delivery methods in 2009 Engineering News Record (ENR) Best Construction Projects in Texas, using the data collected from the projects representative of the population. Also information is collected on lessons learned from these projects. The thesis included development of survey instrument, getting approval from Institutional Review Board (IRB), data collection from the industry, statistical analysis and inferences. Based on the data collected, project performances were measured in terms of five identified variables and then plotted in the form of probability distribution curves to understand the characteristics of the target population. Then, the results were grouped into six categories based on project delivery methods used and compared to understand their impacts on these projects. Findings revealed predominant usage of CM at Risk PDM, and better cost and schedule performance of CM at Risk, Design-Build, and Owner customized PDM. Detailed performance metrics, results, interpretations and conclusions are presented.

It is a well-known fact that macro-economic conditions, such as prices of commodities (e.g. oil, cement and steel) affect the cost of construction projects. In a volatile market environment, highway agencies often pass such risk to contractors using fixed-price contracts. In turn, the contractors respond by adding premiums in bid prices. If the contractors overprice the risk, the price of fixed-price contract could exceed the price of the contract with adjustment clauses. Consequently, highway agencies have the opportunity to design a contract that not only reduces the future risk of exposure, but also reduces the initial contract price. The main goal of this dissertation is to investigate the impact of commodity price risk on construction cost and the optimal risk hedging of such risks using price adjustment clauses. More specifically, the objective of the dissertation is to develop models that can help highway agencies manage commodity price risks. In this dissertation, a weighted least square regression model is used to estimate the risk premium; both univariate and vector time series models are estimated and applied to simulate changes in commodity prices over time, including the effect of correlation; while the genetic algorithm is used as a solution approach to a multi-objective optimization formulation. The data set used in this dissertation consists of TxDOT bidding data, market-based data including New York Mercantile Exchange (NYMEX) future options data, and Engineering News-Record (ENR) material cost index data. The results of this dissertation suggest that the optimal risk mitigation actions are conditional on owners' risk preferences, correlation among the prices of commodities, and volatility of the market.

Currently, many researchers and stakeholders believe that effective delivery systems for construction projects are key to improving project quality and value in the construction industry. Therefore, it is important that owners use the best project delivery system because there are significant consequence due to differences in contracting processes and roles and responsibilities among contracting parties. For the reason, this research aims to compare the efficiency of DB with that of CMAR, as two methods used to select or deny expectations, specifically through quantitative and qualitative analysis. In order to do that, the researcher identified performance data and benefits, drawbacks, and success factors of DB and CMAR through survey and case projects and also analyzed performance data collected from two case projects. Consequently, owners will be able to understand characteristics, differences, and success factors of two different PDSs based on the comparative study. Furthermore, this research could be used to develop a decision support system for owners to select an appropriate PDS.

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This dissertation includes two topics. The first topic focuses on the problem of investor optimization of dynamic asset allocation to maximize expected utility under the value at risk (VaR) constraint. Different to previous researches, this study considers a common realistic case where the VaR horizon is equal to the whole investment horizon without a complete market constraint. Since the problem cannot be solved using the standard dynamic programming method or the martingale method, this study particularly provides an algorithm to solve this difficult problem. Similar to the mean-variance frontier suggested by Markowitz (1952), this study draws the frontiers of dynamic and static asset allocations under the VaR constraint. The analytical results clearly show that the dynamic asset allocations are more efficient than the static asset allocations. The second topic designs an optimal insurance policy form endogenously, assuming the objective of the insured is to maximize expected final wealth under the VaR constraint. The optimal insurance policy can be replicated using three options, including a long call option with a small strike price, a short call option with a large strike price, and a short cash-or-nothing call option. Moreover, expected wealth is increasing and concave in VaR and in significance level. Finally, Mean-VaR Frontiers are drawn, and reveal that the optimal insurance is more efficient than alternative insurance forms.

Many financial time series show heavy tail behavior. Such tail characteristic is important for risk management. In this research, we focus on the calculation of Value-at-Risk (VaR) for portfolios of financial assets. We consider nonlinear autoregressive models with heavy tail innovations to model the return. Predictive distribution of the return are used to compute the VaR of the portfolios of financial assets. Examples are also given to compare the VaR computed by our approach with those by other methods.

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This case study focuses on the influence of certain sociocultural factors on the ability of adolescent girls to fulfill their potentials. Specifically, the purpose of this research is to advance an alternative perspective on the relationship between the sociocultural influences of friendship, mother/daughter relationship, school experience, and body image and a loss of potential among adolescent girls from a historical, poststructural, postmodern-feminist perspective. The dissertation is presented in the form of narrative from both the author’s and girls’ and women’s perspectives in order to seek a rich and thick description. Throughout the study, the author integrates moments from her own journey during adolescence with the young girls and their mothers or grandmothers encountering the oftentimes overwhelming negative sociocultural challenges existing today. The data consist of interviews with four girls and four women; interviews with two school personnel; and observations covering 7 weeks of guided discussion groups. Personal stories are closely examined with current and in-depth research to produce valuable insight and recommendations linking sociocultural factors and potentiality among adolescent girls. In general, these data contribute to an existing body of knowledge as well as advance educational theory regarding adolescent girls and potentiality. Moreover, these findings bolster the argument that, although realistic approaches to create necessary change require a certain resignation to the forces that exist within our culture, educational psychologists will increase the discipline’s impact on students by conducting comprehensive research that creates and supports genuine efforts to teach girls effective strategies on ways to not relinquish control to relentless, disingenuous sociocultural pressures. The case study indicates that, although many positive gains have been made to support young girls, there remain many obstacles as well.