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Statistical Inference for the Expected Utility Portfolio in High Dimensions
Stockholm University, Faculty of Science, Department of Mathematics.ORCID iD: 0000-0001-7855-8221
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Number of Authors: 52021 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 69, p. 1-14Article in journal (Refereed) Published
Abstract [en]

In this paper, using the shrinkage-based approach for portfolio weights and modern results from random matrix theory we construct an effective procedure for testing the efficiency of the expected utility (EU) portfolio and discuss the asymptotic behavior of the proposed test statistic under the high-dimensional asymptotic regime, namely when the number of assets p increases at the same rate as the sample size n such that their ratio p/n approaches a positive constant c is an element of (0, 1) as n -> infinity. We provide an extensive simulation study where the power function and receiver operating characteristic curves of the test are analyzed. In the empirical study, the methodology is applied to the returns of S&P 500 constituents.

Place, publisher, year, edition, pages
2021. Vol. 69, p. 1-14
Keywords [en]
Finance, portfolio analysis, mean-variance optimal portfolio, statistical test, shrinkage estimator, random matrix theory
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:su:diva-190066DOI: 10.1109/TSP.2020.3037369ISI: 000603485000001OAI: oai:DiVA.org:su-190066DiVA, id: diva2:1529250
Available from: 2021-02-17 Created: 2021-02-17 Last updated: 2022-02-25Bibliographically approved

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Bodnar, TarasParolya, Nestor

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