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dc.contributor.authorBarstad, Johannes Andreas
dc.contributor.authorHeitmann, Olve
dc.date.accessioned2017-05-22T08:29:46Z
dc.date.available2017-05-22T08:29:46Z
dc.date.issued2016
dc.identifier.urihttp://hdl.handle.net/11250/2443081
dc.descriptionMasteroppgave(MSc) in Master of Science in Finance - Handelshøyskolen BI, 2016nb_NO
dc.description.abstractThis thesis focuses on the risk measure in the Markowitz algorithm. We discuss why assuming normality is unrealistic, and why the unconditional sample covariance matrix is an inappropriate input for the algorithm. We compare the minimum variance portfolio of Markowitz to the minimum CVaR portfolio, and discuss how the use of GARCH and Copula models can improve upon the precision of the risk estimate. We compare these techniques in two real data applications. Our results suggest that GARCH, and Copula and GARCH in combination outperform the sample estimates if sample correlation is low, and that minimizing variance or CVaR gives very similar results. Keywords: GARCH, Copula, Portfolio Optimization, Modern Portfolio Theory, Risk Measures, Coherent Risk Measures, Conditional Value-at-Risk, Risk Management.nb_NO
dc.language.isoengnb_NO
dc.publisherBI Norwegian Business Schoolnb_NO
dc.subjectfinansnb_NO
dc.subjectfinancenb_NO
dc.subjectfinancial economicsnb_NO
dc.titlePortfolio Optimization : On Risk Measures and Estimation Techniquesnb_NO
dc.typeMaster thesisnb_NO


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