Mean–variance vs trend–risk portfolio selection

David Neděla (), Sergio Ortobelli () and Tomáš Tichý ()
Additional contact information
David Neděla: VSB–Technical University of Ostrava
Sergio Ortobelli: VSB–Technical University of Ostrava
Tomáš Tichý: VSB–Technical University of Ostrava

Review of Managerial Science, 2024, vol. 18, issue 7, No 11, 2047-2078

Abstract: Abstract In 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.

Keywords: Dependency measure; Risk measure; Volatility; Portfolio selection; Trend analysis; 62H25; 91G10; 91G70 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11846-023-00660-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:rvmgts:v:18:y:2024:i:7:d:10.1007_s11846-023-00660-x

Ordering information: This journal article can be ordered from
http://www.springer.com/business/journal/11846

DOI: 10.1007/s11846-023-00660-x

Access Statistics for this article

Review of Managerial Science is currently edited by R. Ewert and W. Kürsten

More articles in Review of Managerial Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().