Yeung Yu Ming. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 35-38). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Risk Measures --- p.3 / Chapter 2.1 --- Extreme Value Thoery --- p.4 / Chapter 2.2 --- Estimating Excess Distributions --- p.7 / Chapter 2.3 --- Estimating Tails of Distributions --- p.9 / Chapter 2.4 --- VaR and ES --- p.10 / Chapter 3 --- Fitting VaR Time Series --- p.13 / Chapter 3.1 --- Autoregressive Integrated Moving Average Models --- p.13 / Chapter 3.2 --- Regression Quantiles --- p.14 / Chapter 4 --- Analysis of Hang Seng Index --- p.16 / Chapter 4.1 --- Risk Measures --- p.20 / Chapter 4.2 --- Backtesting --- p.21 / Chapter 4.3 --- Expected Shortfall --- p.25 / Chapter 4.4 --- Forecasting VaR and ES --- p.26 / Chapter 4.4.1 --- Regression Quantiles --- p.27 / Chapter 4.4.2 --- ARIMA Models --- p.28 / Chapter 5 --- Conclusion --- p.33 / References --- p.35

Financial institutions are interconnected directly by holding debt claims against each other (the network channel), and they are also bound by market liquidity in selling assets to meet debt liabilities when facing distress (the liquidity channel). The goal of our study is to investigate how these two channels of risk transmission interact to propagate individual defaults to a system-wide catastrophe. We formulate the model as an optimization problem with equilibrium constraints and derive a partition algorithm to solve it. The sensitivity analysis on the obtained solution enables us to identify two factors, the network multiplier and the liquidity amplifier, to characterize the contributions of these two channels to financial systemic risk, whereby we can acquire a better understanding of the effectiveness of several policy interventions. The analysis behind the algorithm yields estimates for the contagion probability on the basis of the market value of the institutions' net worths, underscoring the importance of equity capital as a cushion against systemic shocks in the presence of the liquidity channel. The optimization formulation also provides more structural insights to allow us to extend the study of systemic risk to a system with debts of different seniorities and meanwhile presents a close connection to the literature of stochastic networks. Even more, this optimization-based approach and sensitivity analysis can be applied to systems with capital adequacy requirements. Finally, we illustrate the impacts of the network and the liquidity channels — in particular, the significance of the latter — in the formation of systemic risk with data on the European banking system. / 金融机构之间常常通过相互持有各自的债务而直接相连（这被称为网络渠道），同时，当他们面临困境而被迫需要变卖资产来偿还债务时也必将受到市场流动性的影响（这被称为流动性渠道）。我们这篇论文的目标就是要研究个别金融机构的破产是如何通过这两种渠道的交互作用进行风险传播从而导致整个系统发生灾难的。我们将初始模型转化成一个带有均衡约束的优化问题并推出一个分离算法去找出它的解，从而可以得到一个市场清算均衡。通过对这个均衡做敏感度分析，我们就能进一步得到两个因子来刻画前面介绍的两种渠道对金融系统风险传播所做出的贡献，而这两个因子分别就是网络放大因子和流动性放大因子。除此之外，我们利用敏感度分析还可以对一些政府政策和干预措施的有效性进行更加深入的了解。通过对分离算法的分析，我们还可以进行一些基于金融机构净资产市场的分析，从而估计出破产传染的概率，并且指出主权资本在流动性渠道存在的情况下对于抵抗系统性冲击能够起到重要的缓冲作用。转换而成的优化问题则可以给我们提供更多的结构性的见解，让我们对系统风险的研究可以扩展到带有不同债务优先权的系统当中，同时还可以使我们看到系统风险模型与随机网络的紧密联系。甚至，这些基于优化的方法和敏感度分析还可以应用到带有资本充足率要求的系统之中。最后，我们利用欧洲银行系统的数据进行实证检验分析，从而进一步阐述了网络渠道和流动性渠道（特别是后者）在系统风险传播过程中所产生的影响。 / Liu, Xin. / Thesis Ph.D. Chinese University of Hong Kong 2015. / Includes bibliographical references (leaves 104-109). / Abstracts also in Chinese. / Title from PDF title page (viewed on 12, October, 2016). / Detailed summary in vernacular field only.

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Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Nuclear Engineering, 1980. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE. / Bibliography: leaves 169-171. / by Dan Litai. / Ph.D.

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This thesis is concerned with utilizing new mathematical techniques developed in Sweden for inverting characteristic functions of probability distributions of functionals defined on the collective risk stochastic process. A characteristic function is a Fourier transform. However, such transforms-could not be inverted. With the advent of the electronic computer, the Fast Fourier Transform technique was developed for inverting Fourier Transforms. Essentially these techniques replace integrals over an uncountable number of points by series over a discrete set of points. This thesis will convert some Swedish results into useful forms for American students. It will be concerned with the probability distribution of aggregate claims in a fixed time, as well as ruin probabilities. The thesis will illustrate the basic mathematical techniques with several practical problems. Computer programs and numerical examples will be included.

Thesis (Ph. D.)--University of Hawaii at Manoa, 1981. / Bibliography: leaves 177-181. / Microfiche. / xvi, 181 leaves, bound ill., maps 29 cm

Weather and climate events are costly to society both financially and in terms of human health and well being. The costs associated with extreme climate events have motivated governments, NGOs, private investors, and insurance companies to use the data and tools at their disposal to estimate the past, present, and future hazards associated with a wide range of natural phenomena in an effort to develop mitigation and/or adaptation strategies. The nonstationary nature of climate risks requires the use of numerical climate models, often general circulation models (GCMs), to project future risk. The climate risk field, however, currently finds itself in a predicament because GCMs can be biased and do not provide a clear way to credibly estimate their uncertainty with respect to simulations of future surface climate conditions. In response to this predicament, I lay the groundwork for a set of GCM credibility assessments by identifying the large-scale drivers of surface climate events that evolve over a range of timescales ranging from daily to multi-decadal. I specifically focus on three types of climate events relevant to the water and energy sectors: 1) seasonal precipitation, which impacts drinking water supplies and agricultural productivity; 2) extreme precipitation and the costly associated riverine flooding; and 3) temperature, wind, and solar radiation fields that modulate both electricity demand and potential renewable electricity supply. In chapter I, I derive a set of atmospheric indices and investigate their efficacy to predict distributed seasonal precipitation throughout the conterminous United States. These indices can also be used to diagnose the impact of tropical sea surface temperature heating patterns on conterminous United States precipitation. This is particularly of interest in the aftermath of the unexpected precipitation patterns in the conterminous United States during the 2015-2016 El Niño event. I show that the set of atmospheric indices, which I derive from zonal winds over the conterminous United States and portions of the North Atlantic and Pacific oceans, can skillfully predict precipitation over most regions of the conterminous United States better than previously recognized mid-latitude atmospheric and tropical oceanic indices. This work contributes a set of intermediate atmospheric indices that can be used to assess the efficacy of forecasting and simulation climate models to capture signal that exists between tropical heating, mid-latitude circulation, and mid-latitude precipitation. In chapter II, I first show that the frequency of regional extreme precipitation events, which are predictive of riverine flooding, in the Ohio River Basin are poorly simulated by a GCM relative to historical precipitation observations. I then illustrate that the same GCM is much better able to simulate the statistical characteristics of a set of atmospheric field-derived indices that I show to be strongly related to the precipitation events of interest. Thus, I develop a statistical model that allows for the simulation of the precipitation events based on the GCM's atmospheric fields, which allows me to estimate future hazard based on credibly simulated GCM fields. Lastly, I validate the fully Bayesian statistical model against historical observations and use the statistical model to project the future frequency of the regional extreme precipitation events. I conclude that there is evidence of increasing regional riverine flood hazard in the Central US river basin out to the year 2100, but that there is high uncertainty regarding the magnitude of the trend. This work suggests that the identification of atmospheric circulation patterns that modulate the probability of extreme precipitation and riverine flood risk may improve flood hazard projections by allowing risk analysts to assess GCMs with respect to their ability to simulate relevant atmospheric patterns. In chapter III, I present the first comprehensive assessment of quasi-periodic decadal variations in wind and solar electricity potential and of covariability between heating and cooling electricity demand and potential wind and solar electricity production. I focus on six locations/regions in the conterminous United States that represent different climate zones and contain major load centers. The decadal variations are linked to quasi-oscillatory variations of the global climate system and lead to time-varying risks of meeting heating + cooling demand using wind/solar power. The quasi-cyclical patterns in renewable energy availability have significant ramifications for energy systems planning as we continue to increase our reliance on renewable, weather- and climate-dependent energy generation. This work suggests that certain modes of low frequency climate variability influence potential wind and solar energy supplies and are thus especially important for GCMs to credibly simulate. All of the investigations are designed to be broadly applicable throughout the mid-latitudes and are demonstrated with specific case studies in the conterminous United States. The dissertation sections represent three cases where statistical techniques can be used to understand surface climate and climate hazards. This understanding can ultimately help to mitigate and adapt to climate variabilities and secular changes, which impact society, by assisting in the development, improvement, and credibility assessment of GCMs capable of reliably projecting future climate hazards.

Li Ka-leung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 85-88). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Structural models of credit risk --- p.9 / Chapter 2.1 --- The original Merton model --- p.10 / Chapter 2.2 --- The extended Merton model --- p.11 / Chapter 2.3 --- The Black and Cox model --- p.12 / Chapter 2.4 --- The LS model --- p.14 / Chapter 2.5 --- The CDG model --- p.16 / Chapter 2.6 --- Comments on structural models --- p.19 / Chapter 3 --- Proxies and their implications --- p.20 / Chapter 3.1 --- Reviews of the EHH's empirical studies --- p.20 / Chapter 3.2 --- The proxy for market values of firms --- p.23 / Chapter 3.2.1 --- Zero coupon bonds under the Merton model --- p.23 / Chapter 3.2.2 --- Coupon bearing bonds under the extended Merton model --- p.25 / Chapter 3.2.3 --- Zero coupon bonds under the LS model --- p.26 / Chapter 3.2.4 --- Coupon bearing bonds under the LS model --- p.28 / Chapter 3.3 --- Implications of other proxies --- p.29 / Chapter 4 --- Maximum Likelihood Estimation --- p.33 / Chapter 4.1 --- The MLE approach for the Merton model --- p.33 / Chapter 4.2 --- The MLE approach for the barrier dependent models --- p.35 / Chapter 4.3 --- Survivorship consideration --- p.36 / Chapter 4.4 --- Simulation tests --- p.37 / Chapter 4.5 --- Simulation results --- p.39 / Chapter 4.5.1 --- Simulation results for the Merton model --- p.39 / Chapter 4.5.2 --- Simulation results for the LS model --- p.42 / Chapter 5 --- Empirical test --- p.47 / Chapter 5.1 --- Criteria of bond selection --- p.47 / Chapter 5.2 --- Parameters of models --- p.51 / Chapter 5.2.1 --- Firm specific parameters --- p.51 / Chapter 5.2.2 --- Interest rate parameters --- p.54 / Chapter 5.2.3 --- Stationary leverage process parameters --- p.55 / Chapter 5.2.4 --- Bond specific parameters --- p.57 / Chapter 5.3 --- Empirical results --- p.58 / Chapter 5.3.1 --- Empirical results for the Merton model --- p.59 / Chapter 5.3.2 --- Empirical results for the LS model --- p.66 / Chapter 5.3.3 --- Empirical results for the CDG model --- p.71 / Chapter 6 --- Conclusion --- p.77 / Appendix --- p.80 / Chapter A.1 --- Appendix 1 --- p.80 / Chapter A.2 --- Appendix 2 --- p.82 / Chapter A.3 --- Appendix 3 --- p.84 / Bibliography --- p.85

Finally, we study a multi-period, risk-averse inventory model. The objective is to maximize the expected pay-offs. The risk-averse behavior is modeled as to penalize the decision maker if a target-profit level is not satisfied for each financial reporting cycle. We recognize that the operational period is usually faster than the financial reporting cycle. Therefore, the financial reporting cycle can be considered as an integer times of the operational periods. We study this model under both accrual-basis accounting principle and cash-basis accounting principle. We prove that the optimal inventory policy is a state-dependent base-stock policy under the accrual-basis accounting method. We then show that the structure of an optimal policy is a complicated one for the cash-basis accounting method. / In this thesis we study three supply chain models which address downside risk from a different angle. We start with a commitment-option supply contract in a Conditional Value-at-Risk (CVaR) framework. We show that a CVaR trade-off analysis with advanced reservation can be carried out efficiently. Moreover, our study indicates how the corresponding contract decisions differ from decisions for optimizing an expected value. / Key words. Downside Risk Measure; CVaR; Risk; Loss-Averse; Dynamic Programming. / Owing to the growing globalization in economy and the advances in commerce, research in supply chain management has attracted large number of researchers in the last two decades. Yet standard treatments of supply chain models are mainly confined for the optimization of expected values with little reflection on risk considerations. Even for those that consider a risk measure in the objective function, there are quite few literatures employing downside risk measure. The downside risk measure takes into account only the part of the distribution that is below a critical value. Thus it indicates a safety-first strategy for decision maker. / The thesis is organized in five chapters. In Chapter 1, we provide the background and research motivation for considering downside risk measures in supply chain models. In Chapter 2, we study the pay-to-delay supply contracts with a Conditional Value-at-Risk (CVaR) framework. In Chapter 3, we study the loss-averse newsvendor problem. In Chapter 4, we extend the loss-averse model to a multi-period setting. We conclude the thesis in Chapter 5 with discussions for future research. / Then, we employ a loss-aversion utility function to characterize newsvendor's decision-making behavior. We find that when there is no shortage cost, the loss-averse newsvendor consistently orders less than a risk-neutral newsvendor. Further, we discover that the loss-averse newsvendor orders a constant quantity when the reference target is sufficiently large. We discuss the importance of initial inventory to achieve the target profit level. When the target is a decision variable, the newsvendor always sets the target no higher or no lower. / Ma, Lijun. / "October 2007." / Adviser: Houmin Yan. / Source: Dissertation Abstracts International, Volume: 69-08, Section: B, page: 5003. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (p. 140-154). / 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 Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.