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dc.contributor.authorKara, Güray
dc.contributor.authorÖzmen, Ayşe
dc.contributor.authorWeber, Gerhard-Wilhelm
dc.date.accessioned2018-04-05T08:10:57Z
dc.date.available2018-04-05T08:10:57Z
dc.date.created2017-12-11T14:56:59Z
dc.date.issued2017
dc.identifier.citationCentral European Journal of Operations Research. 2017, 1-21.nb_NO
dc.identifier.issn1435-246X
dc.identifier.urihttp://hdl.handle.net/11250/2492740
dc.description.abstractIn financial markets with high uncertainties, the trade-off between maximizing expected return and minimizing the risk is one of the main challenges in modeling and decision making. Since investors mostly shape their invested amounts towards certain assets and their risk aversion level according to their returns, scientists and practitioners have done studies on that subject since the beginning of the stock markets’ establishment. In this study, we model a Robust Optimization problem based on data. We found a robust optimal solution to our portfolio optimization problem. This approach includes the use of Robust Conditional Value-at-Risk under Parallelepiped Uncertainty, an evaluation and a numerical finding of the robust optimal portfolio allocation. Then, we trace back our robust linear programming model to the Standard Form of a Linear Programming model; consequently, we solve it by a well-chosen algorithm and software package. Uncertainty in parameters, based on uncertainty in the prices, and a risk-return analysis are crucial parts of this study. A numerical experiment and a comparison (back testing) application are presented, containing real-world data from stock markets as well as a simulation study. Our approach increases the stability of portfolio allocation and reduces the portfolio risk.nb_NO
dc.language.isoengnb_NO
dc.publisherSpringer Verlagnb_NO
dc.titleStability advances in robust portfolio optimization under parallelepiped uncertaintynb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.pagenumber1-21nb_NO
dc.source.journalCentral European Journal of Operations Researchnb_NO
dc.identifier.doi10.1007/s10100-017-0508-5
dc.identifier.cristin1525774
dc.description.localcodeThis is a post-peer-review, pre-copyedit version of an article published in [Central European Journal of Operations Research] Locked until 29.11.2018 due to copyright restrictions. The final authenticated version is available online at: https://link.springer.com/article/10.1007%2Fs10100-017-0508-5nb_NO
cristin.unitcode194,60,25,0
cristin.unitnameInstitutt for industriell økonomi og teknologiledelse
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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