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A risk perspective of estimating portfolio weights of the global minimum-variance portfolio
Linnæus University, Växjö, Sweden.
Linnæus University, Växjö, Sweden.
Jönköping University, Jönköping International Business School, JIBS, Economics. Jönköping University, Jönköping International Business School, JIBS, Center for Family Enterprise and Ownership (CeFEO).ORCID iD: 0000-0001-5776-9396
2019 (English)In: AStA Advances in Statistical Analysis, ISSN 1863-8171, E-ISSN 1863-818XArticle in journal (Refereed) Epub ahead of print
Abstract [en]

The problem of how to determine portfolio weights so that the variance of portfolio returns is minimized has been given considerable attention in the literature, and several methods have been proposed. Some properties of these estimators, however, remain unknown, and many of their relative strengths and weaknesses are therefore difficult to assess for users. This paper contributes to the field by comparing and contrasting the risk functions used to derive efficient portfolio weight estimators. It is argued that risk functions commonly used to derive and evaluate estimators may be inadequate and that alternative quality criteria should be considered instead. The theoretical discussions are supported by a Monte Carlo simulation and two empirical applications where particular focus is set on cases where the number of assets (p) is close to the number of observations (n). 

Place, publisher, year, edition, pages
Springer, 2019.
Keywords [en]
Global minimum-variance portfolio, High dimensional, Portfolio theory, Risk functions
National Category
Economics and Business
Identifiers
URN: urn:nbn:se:hj:diva-43301DOI: 10.1007/s10182-018-00349-7Scopus ID: 2-s2.0-85061199749OAI: oai:DiVA.org:hj-43301DiVA, id: diva2:1294288
Available from: 2019-03-07 Created: 2019-03-07 Last updated: 2019-03-07

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Stephan, Andreas

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