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A qualitative approach to financial riskShedden, Jason Patrick. January 2006 (has links)
Thesis (M. Com. (Financial management ))--University of Pretoria, 2006. / Summary in English. Includes bibliographical references (leaves 181-187). Available on the Internet via the World Wide Web.
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Operational risk management (ORM) systems : an Australian study /Pitinanondha, Thitima. January 2008 (has links)
Thesis (Ph. D.)--University of Technology Sydney, 2008.
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Identification of methods for use as an academic assessment within the University of Wisconsin-Stout, Risk Control programMarcuk, Gregg R. January 1998 (has links) (PDF)
Thesis--PlanB (M.S.)--University of Wisconsin--Stout, 1998. / Includes bibliographical references.
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Empirical studies on risk management of investors and banksAngerer, Xiaohong W., January 2004 (has links)
Thesis (Ph. D.)--Ohio State University, 2004. / Title from first page of PDF file. Document formatted into pages; contains xi, 135 p.; also includes graphics. Includes bibliographical references (p. 131-135). Available online via OhioLINK's ETD Center
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Why managers and companies take risksColeman, Les, January 1900 (has links)
Revised thesis (Ph.D.)--University of Melbourne. / Title from e-book title screen (viewed August 18, 2008). Includes bibliographical references (p. [237]-345) and index.
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Why managers and companies take risksColeman, Les, January 1900 (has links)
Revised Thesis (Ph. D.)--University of Melbourne. / Includes bibliographical references and index.
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A case study in industrial risk managementRaubenheimer, Pieter Jacobus 06 December 2011 (has links)
M.Ing. / This dissertation focuses on an industrial risk management case study, which aims to illustrate how the risks involved in a new project have to be identified, approached and managed. The aim of this dissertation is therefore to act as an example of modem risk management theory and implementation in an industrial engineering environment. The first part of the dissertation focuses on the theoretical background of risk management. It starts by giving the history of risk after which a definition of risk is concluded from a variety of text books. The history of risk shows how risk developed through the ages and evolved into a way of making sure that the right strategic decisions are taken. The following chapters focus on the frameworks that have been developed by different international parties to structure the risk management process. The financial environment is also highlighted as an industry in which risk has been developed to help companies tremendously in making investment decisions. Although there are fundamental differences between risk management in the industrial and financial environment, there are however a few similarities. One aspect that can be taken from the financial environment and be implemented in the industrial environment is the fact that risk management has to be done according to a fixed structure or framework. A short literature case study shows how businesses made crucial mistakes in the past, and how implementing modem risk management techniques can rectify these mistakes. A big part of risk management is not only the qualitative analysis, but also in the quantitative analysis, which was ignored in the literature case study. The theory behind these quantitative techniques is highlighted as the last theoretical background before the second part of the dissertation focuses on the risk involved in the expansion project of an oil refinery. After the theoretical background of the expansion project is given as an introduction to the case study, the quantitative analysis for the expansion project is done. Through A Case Study in Industrial Risk Management 2 the quantitative analysis, the high risks involved in the project are highlighted more clearly and numbers or figures will indicate how realistic the objectives of the project are. By monitoring and controlling these critical project variables through the project life cycle, the chances of achieving the project results are greatly increased.
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Term structure models with unspanned factors and unspanned stochastic volatilityBackwell, Alexander 11 February 2019 (has links)
Certain models of the term structure of interest rates exhibit unspanned stochastic volatility (USV). A model has this property if it involves a source of stochastic variation — called an unspanned factor — that does not affect the model’s interest rates directly, but does affect the extent to which future interests are liable to change (that is, interest-rate volatility). This thesis is concerned with these models, from a variety of perspectives. Firstly, the theoretical foundation of the USV property is addressed. Formal definitions of unspanned factors and USV are developed, generalising ones tentatively proposed in the literature. Several results from these definitions and the accompanying framework are derived. Particularly, the ability to hedge general claims (i.e., the completeness or lack thereof) of these models is examined in detail. Examples are given to illustrate the features of the proposed framework and the necessity of the generalised definitions. Secondly, the empirical issue of whether USV models are necessary to plausibly represent observed interest-rate markets is interrogated. An empirical derivative-hedging approach is adopted, the results of which are contextualised by also treating data simulated from models with USV and non-USV versions. It is shown that hedging effectiveness is relatively robust to the presence of USV, which resolves the apparent conflict between the two studies that have taken a hedging approach to this question. Despite the cross-sectional hedging effects being surprisingly minor, further regression results show that USV models are needed to model the time series of market interest rates. Finally, the thesis addresses a certain class of models that exhibit USV: those with one spanned factor (driving interest-rate variation) and one unspanned, volatility-related factor. Being the simplest non-trivial USV models, these bivariate USV models are fundamental, and — like onefactor models in general settings — are helpful in introducing and comparing higher-factor models when simple ones are insufficient. These models are shown to exist (contradicting a claim in the literature); to share a particular affine form for their bond pricing functions; and to necessarily exhibit a short-term interest rate with dynamics of a certain type. A specific bivariate USV model is then proposed, which is analysed and compared to others in the literature.
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Estimating Long Term Equity Implied VolatilityCrawford, Danielle Ana 27 February 2020 (has links)
Estimating and extrapolating long term equity implied volatilities is of importance in the investment and insurance industry, where ’long term’ refers to periods of ten to thirty years. Market-consistent calibration is difficult to perform in the South African market due to lack of long term liquid tradable derivatives. In this case, practitioners have to estimate the implied volatility surface across a range of expiries and moneyness levels. A detailed evaluation is performed for different estimation techniques to assess the strengths and weaknesses of each of the models. The estimation techniques considered include statistical and time-series techniques, non-parametric techniques and three potential methods which use the local volatility model.
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Enterprise risk management implementation : perceptions of risk practitioners in the South African mining industry09 December 2013 (has links)
M.Comm. (Financial Economics) / Enterprise risk management (ERM) is emerging as a risk management methodology that is seemingly superior to that of traditional, silo-based risk management. Although ERM implementation is on the increase, research into ERM is still limited. There is, for instance, a lack of clarity within the literature regarding which factors lead to companies embracing ERM, as well as a lack of consensus on ERM’s benefits. The purpose of this study was therefore to explore the drivers of ERM implementation, its inhibitors and enablers, the benefits that are realised through ERM, as well as the advantages and disadvantages associated with ERM as a risk management methodology. Data were gathered through semi-structured, face-to-face interviews with seven risk practitioners working in the South African mining industry. The study found that drivers of ERM implementation include regulatory pressure and compliance with corporate governance and listing requirements, but that there are other incentives. Inhibitors of ERM implementation include the large amount of managerial time needed, competition with other initiatives, resistance, and low initial buy-in levels, as well as a shortage of experienced ERM practitioners. Regarding ERM enablers, the design of the ERM framework is seen as critical, as is sound project discipline in planning and organising the implementation, along with visible support from executive and senior management, and ongoing training. Benefits derived through ERM include greater confidence that the company has a complete understanding of its risk profile, better decision-making, and improved tracking of risk mitigation. Disadvantages associated with ERM include the tendency of it being regarded as a corporate administrative function, subjectivity, and difficulty in aligning ERM to short- and medium-term priorities, as compared to longer-term strategic issues. This study makes a unique contribution to the existing body of knowledge on ERM by exploring the disadvantages associated with ERM as a risk management methodology. At a practical level and with reference to the South African mining industry, in particular, this study provides more clarity on the rationale for adopting ERM, as well as the challenges associated with implementing and sustaining ERM programmes. Recommendations are made with respect to ERM in practice, as well as for further research on ERM.
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