Stability analysis of optimal mean-variance portfolio due to covariance estimation

dc.contributor.authorŠedivá, Blanka
dc.contributor.authorMarek, Patrice
dc.date.accessioned2018-10-21T10:00:13Z
dc.date.available2018-10-21T10:00:13Z
dc.date.issued2017
dc.description.abstract-translatedThe objective of this paper is to study the stability of the mean-variance portfolio optimization. The results of the mean-variance optimal selection problem are very sensitive to the model parameters (portfolio calibration window and frequency of portfolio rebalancing). There are presented three methods of stabilization of covariance matrix estimation and further analysis are focused on the influence of estimation of covariance matrix to robustness of optimal selection. For practical verification, the proposed approaches were tested the suitability of these methods to the performance of the investment portfolio. This were done within the framework of 2000 to 2016 using daily data of 100 companies from the New York Stock Exchange.en
dc.format6 s.cs
dc.format.mimetypeapplication/pdf
dc.identifier.document-number427151400130
dc.identifier.isbn978-80-7435-678-0
dc.identifier.obd43922156
dc.identifier.urihttp://hdl.handle.net/11025/30445
dc.language.isoenen
dc.project.IDLO1506/PUNTIS - Podpora udržitelnosti centra NTIS - Nové technologie pro informační společnostcs
dc.publisherUniverzita Hradec Královécs
dc.relation.ispartofseriesProcedings of the 35th International Conference Mathematical Methods in Economicsen
dc.rights© Univerzita Hradec Královécs
dc.rightsPlný text je přístupný v rámci univerzity přihlášeným uživatelům.cs
dc.rights.accessrestrictedAccessen
dc.subject.translatedPortfolio Selection Problemen
dc.subject.translatedCovariance Estimationen
dc.subject.translatedMean-Variance-Optimizationen
dc.subject.translatedRandom Matrixen
dc.titleStability analysis of optimal mean-variance portfolio due to covariance estimationen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen

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