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dc.contributor.advisorMiller, Douglas, 1965-eng
dc.contributor.authorKim, Moohwaneng
dc.date.issued2011eng
dc.date.submitted2011 Summereng
dc.description"July 2011"eng
dc.descriptionTitle from PDF of title page (University of Missouri--Columbia, viewed on May 17, 2012).eng
dc.descriptionThe entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.eng
dc.descriptionDissertation advisor: Dr. Douglas J. Millereng
dc.descriptionVita.eng
dc.description.abstractFaced with the current financial crisis, several US and foreign banks and investment firms have failed due to excessive losses. The Value-at-Risk (VaR) was a widely-used risk model that was problematic. We evaluate competing claims from the financial economics literature about the relative importance of the VaR flaws (e.g., subadditivity) and probability model specification errors in risk measurement under Extreme Value Theory. In particular, we use the peaks-over-threshold method based on the Generalized Pareto model to compare the relative performance of the VaR and Conditional VaR for assessing forward-looking risk in observed hedge fund returns. In the second chapter, focus is on how to improve our ability to manage financial risks by developing a better understanding of the microstructure of financial markets. Using high frequency foreign exchange rate data, we want to see if we can better assess the current risk of financial positions and improve our predictions of future price movements. To handle the fact that high frequency returns might be correlated in a nonlinear fashion, we may use copula-based probability models that are involved with GARCH models. We compare the performance of the alternative dynamic hedging models with the hedging effectiveness of the static model. In chapter three, we try to choose an appropriate copula model that provides the “best” fit to the observed data. Along with the discussions of the existing model selection procedures, we propose a non-nested test procedure for copula model selection that is based on the Cox test statistic.eng
dc.description.bibrefIncludes bibliographical referenceseng
dc.format.extentxiii, 201 pageseng
dc.identifier.oclc872560398eng
dc.identifier.urihttps://doi.org/10.32469/10355/14212eng
dc.identifier.urihttps://hdl.handle.net/10355/14212
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcommunityUniversity of Missouri--Columbia. Graduate School. Theses and Dissertations.eng
dc.rightsOpenAccess.eng
dc.rights.licenseThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.
dc.subjectrisk measureeng
dc.subjectmodel selectioneng
dc.subjectCopula methodeng
dc.subjectfinancial marketseng
dc.titleEconometric methods for improved measures of financial riskeng
dc.typeThesiseng
thesis.degree.disciplineEconomics (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelDoctoraleng
thesis.degree.namePh. D.eng


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