A risk perspective of estimating portfolio weights of the global minimum-variance portfolio

Thomas Holgersson (), Peter Karlsson () and Andreas Stephan
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Thomas Holgersson: Linnæus University
Peter Karlsson: Linnæus University

AStA Advances in Statistical Analysis, 2020, vol. 104, issue 1, No 4, 59-80

Abstract: Abstract 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).

Keywords: Global minimum-variance portfolio; Portfolio theory; High dimensional; Risk functions (search for similar items in EconPapers)
JEL-codes: C13 C18 C44 G11 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10182-018-00349-7

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