Zhang, Lianmin. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 130-139). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts also in Chinese.

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Ph.D. (Mathematics) / Please refer to full text to view abstract

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We extend Kreps and Porteus' (1978, 1979a,b) temporal utility theory to include measures of suspense for gambles that vary in the timing of uncertainty resolution. Our f$ sp t$-modification (of their theory) defines overall utility and suspense in terms of two functions: a standard utility function and an iterative function whose properties determine attitude towards temporal uncertainty resolution. Suspense, which is increasing with time delay to uncertainty resolution, is defined as the "variance" of the standard utilities of the outcome streams taken about our measure of overall utility (rather than about the standard mean utility). We explore the properties of our measures and their implications for the overall utility and suspense of various key examples. Two preliminary experiments are reported which give some support for our overall utility and suspense measures, and which suggest that risk and suspense are different concepts. Iteration theory is also discussed in some detail.

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"June 2004." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (p. 138-148). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest dissertations and theses, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

Natural resource management models simplify reality for the purpose of planning or management. In much the same way, an uncertainty model simplifies the many uncertainties that pervade the natural resource management model. However, though a number of uncertainty models have been developed, there has been little work on verifying such models against the uncertainty they purport to represent. The central research question addressed by this work is 'can a natural resource management uncertainty model be verified in order to evaluate its utility in real-world management?' Methods to verity uncertainty models are developed in two areas: uncertainty data models, and uncertainty propagation through process models. General methods are developed, and then applied to a specific case study: slope stability uncertainty in the southern Queen Charlotte Islands. Verification of two typical uncertainty data models (of classified soils and continuous slope) demonstrates that (in this case) both expert opinion inputs and published error statistics underestimate the level of uncertainty that exists in reality. Methods are developed to recalibrate the data models, and the recalibrated data are used as input to an uncertainty propagation model. Exploratory analysis methods are then used to verify the output of this model, comparing it with a high-resolution mass wastage database—itself developed using a new set of tools incorporating uncertainty visualisation. Exploratory data analysis and statistical analysis of the verification shows that, given the nature of slope stability modelling, it is not possible to directly verify variability in the model outputs due to the existing distribution of slope variability (based on the nature of slope modelling). However, the verification work indicates that the information retained in uncertaintybased process models allows increased predictive accuracy—in this case of slope failure. It is noted that these verified models and their data increase real-world management and planning options at all levels of resource management. Operational utility is demonstrated throughout this work. Increased strategic planning utility is discussed, and a call is made for integrative studies of uncertainty model verification at this level.

Firms can use financial derivatives to hedge risks and thereby decrease the probability of bankruptcy and increase total expected tax shields. Firms also can adjust their operational policies in response to fluctuations in prices, a strategy that is often referred to as "operational hedging". In this paper, I investigate the relationship between the optimal financial and operational hedging strategies for a firm, which are endogenously determined together with its capital structure. This allows me to examine how operational hedging affects debt capacity and total expected tax shields and to make quantitative predictions about the relationship between debt issues and hedging policies. I also model the effects of asymmetric information about firms' investment opportunities on their financing and hedging decisions. First, I examine the case in which both debt and hedging contracts are observable. Then, I study the case in which firms' hedging activities are not completely transparent. The models are tested using a data set compiled from the annual reports of North American gold mining companies. Supporting evidence is found for the key predictions of the model under asymmetric information.

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