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dc.contributor.authorNeděla, David
dc.contributor.authorOrtobelli, Sergio
dc.contributor.authorTichý, Tomáš
dc.date.accessioned2024-01-12T10:52:46Z
dc.date.available2024-01-12T10:52:46Z
dc.date.issued2023
dc.identifier.citationReview of Managerial Science. 2023.cs
dc.identifier.issn1863-6683
dc.identifier.issn1863-6691
dc.identifier.urihttp://hdl.handle.net/10084/151890
dc.description.abstractIn this paper, we provide an alternative trend (time)-dependent risk measure to Ruttiens’ accrued returns variability (Ruttiens in Comput Econ 41:407–424, 2013). We propose to adjust the calculation procedure to achieve an alternative risk measure. Our modification eliminates static mean component and it is based on the deviation of squared dispersions, which reflects the trend (time factor) precisely. Moreover, we also present a new perspective on dependency measures and we apply a PCA to a new correlation matrix in order to determine a parametric and nonparametric return approximation. In addition, the two-phase portfolio selection strategy is considered, where the mean–variance portfolio selection strategies represent the first optimization. The second one is the minimization of deviations from their trend leading to identical mean and final wealth. Finally, an empirical analysis verify the property and benefit of portfolio selection strategies based on these trend-dependent measures. In particular, the ex-post results show that applying the modified measure allows us to reduce the risk with respect to the trend of several portfolio strategies.cs
dc.language.isoencs
dc.publisherSpringer Naturecs
dc.relation.ispartofseriesReview of Managerial Sciencecs
dc.relation.urihttps://doi.org/10.1007/s11846-023-00660-xcs
dc.rightsCopyright © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Naturecs
dc.subjectdependency measurecs
dc.subjectrisk measurecs
dc.subjectvolatilitycs
dc.subjectportfolio selectioncs
dc.subjecttrend analysiscs
dc.titleMean–variance vs trend–risk portfolio selectioncs
dc.typearticlecs
dc.identifier.doi10.1007/s11846-023-00660-x
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.identifier.wos000967804200001


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