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Estimation of Optimal Portfolio Compositions for Small Sample and Singular Covariance Matrix
Linköping University, Department of Management and Engineering, Production Economics. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-7855-8221
Unit of Statistics, School of Business, Örebro University, Örebro, Sweden; Department of Economics and Statistics, School of Business and Economics, Linnaeus University, Växjö, Sweden.
Linköping University, Department of Management and Engineering, Production Economics. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-0682-8584
2024 (English)In: Advanced Statistical Methods in Process Monitoring, Finance, and Environmental Science: Essays in Honour of Wolfgang Schmid / [ed] Sven Knoth, Yarema Okhrin, Philipp Otto, Cham: Springer Nature, 2024, p. 259-278Chapter in book (Refereed)
Abstract [en]

In the chapter we consider the optimal portfolio choice problem under parameter uncertainty when the covariance matrix of asset returns is singular. Very useful stochastic representations are deduced for the characteristics of the expected utility optimal portfolio. Using these stochastic representations, we derive the moments of higher order of the estimated expected return and the estimated variance of the expected utility optimal portfolio. Another line of applications leads to their asymptotic distributions obtained in the high-dimensional setting. Via a simulation study, it is shown that the derived high-dimensional asymptotic distributions provide good approximations of the exact ones even for moderate sample sizes.

Place, publisher, year, edition, pages
Cham: Springer Nature, 2024. p. 259-278
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Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:liu:diva-211024DOI: 10.1007/978-3-031-69111-9_13ISBN: 9783031691119 (electronic)OAI: oai:DiVA.org:liu-211024DiVA, id: diva2:1928483
Available from: 2025-01-17 Created: 2025-01-17 Last updated: 2025-03-06Bibliographically approved

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Bodnar, TarasNguyen, Hoang

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