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dc.contributor.advisorJansen, Dennis W
dc.contributor.advisorXu, Ke-Li
dc.creatorDing, Liyuan 1988-
dc.date.accessioned2013-03-14T16:26:21Z
dc.date.available2013-03-14T16:26:21Z
dc.date.created2012-12
dc.date.issued2012-12-11
dc.date.submittedDecember 2012
dc.identifier.urihttps://hdl.handle.net/1969.1/148430
dc.description.abstractSafety first criterion and mean-shortfall criterion both explore cases of assets allocation with downside risk. In this paper, I compare safety first portfolio selection problem and mean-shortfall portfolio optimization problem, considering risk averse investors in practice. Safety first portfolio selection uses Value at Risk (VaR) as a risk measure, and mean-shortfall portfolio optimization uses expected shortfall as a risk measure, respectively. VaR is estimated by implementing extreme theory using a semi-parametric method. Expected shortfall is estimated by two nonparametric methods: a natural estimation and a kernel-weighted estimation. I use daily data on three international stock indices, ranging from January 1986 to February 2012, to provide empirical evidence in asset allocations and illustrate the performances of safety first and mean-shortfall with their risk measures. Also, the historical data has been divided in two ways. One is truncated at year 1998 and explored the performance during tech boom and financial crisis. the mean-shortfall portfolio optimization with the kernel-weighted method performed better than the safety first criterion, while the safety first criterion was better than the mean-shortfall portfolio optimization with the natural estimation method.en
dc.format.mimetypeapplication/pdf
dc.subjectExpected Shortfallen
dc.subjectVaRen
dc.subjectMean-shortfall portfolio selectionen
dc.subjectSafety first portfolio selectionen
dc.titleEmpirical Analysis of Value at Risk and Expected Shortfall in Portfolio Selection Problemen
dc.typeThesisen
thesis.degree.departmentEconomicsen
thesis.degree.disciplineEconomicsen
thesis.degree.grantorTexas A&M Universityen
thesis.degree.nameMaster of Scienceen
thesis.degree.levelMastersen
dc.contributor.committeeMemberWu, Ximing
dc.type.materialtexten
dc.date.updated2013-03-14T16:26:21Z


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