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dc.contributor.advisorBurke, James V.en_US
dc.contributor.authorZhang, Yunen_US
dc.date.accessioned2013-02-25T17:54:32Z
dc.date.available2013-02-25T17:54:32Z
dc.date.issued2013-02-25
dc.date.submitted2012en_US
dc.identifier.otherZhang_washington_0250E_10711.pdfen_US
dc.identifier.urihttp://hdl.handle.net/1773/21869
dc.descriptionThesis (Ph.D.)--University of Washington, 2012en_US
dc.description.abstractModern Portfolio Theory dates back to 1950s, when Markowitz proposed mean-variance portfolio optimization to construct portfolios. It provided a systematic approach to determine portfolio allocation when one is facing complicated risk structure that not only exists for individual assets but also across different assets. Since then there has been much research exploring better ways to quantify risk. In particular, asymmetric risk measures including the more recent downside risk measures. Here we use expected tail loss (ETL) as the risk measure which is a coherent risk measure, and define a reward measure, expected tail gain (ETG), to measure the upside return. We formulate the portfolio optimization problem using these two measures and developed an iterative algorithm to find its optimal solution.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoen_USen_US
dc.rightsCopyright is held by the individual authors.en_US
dc.subjectcoherent risk measure; downside risk; ETG; ETL; Portfolio optimization; upside returnen_US
dc.subject.otherApplied mathematicsen_US
dc.subject.otherFinanceen_US
dc.subject.otherApplied mathematicsen_US
dc.titleETG-ETL Portfolio Optimizationen_US
dc.typeThesisen_US
dc.embargo.termsNo embargoen_US


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