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Estimation of Optimal Portfolio Compositions for Small Sample and Singular Covariance Matrix
Linköping University, Sweden.
Linnaeus University, School of Business and Economics, Department of Economics and Statistics (NS).ORCID iD: 0000-0002-1395-9427
Linköping University, Sweden.
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 (Other academic)
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
National Category
Probability Theory and Statistics
Research subject
Natural Science, Mathematics
Identifiers
URN: urn:nbn:se:lnu:diva-142642DOI: 10.1007/978-3-031-69111-9_13Scopus ID: 2-s2.0-105006863896ISBN: 9783031691102 (print)ISBN: 9783031691119 (electronic)OAI: oai:DiVA.org:lnu-142642DiVA, id: diva2:2015317
Available from: 2025-11-20 Created: 2025-11-20 Last updated: 2025-11-20Bibliographically approved

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Mazur, Stepan

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Citation style
  • apa
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  • de-DE
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  • en-US
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf