Abstract
This article discusses why the maximization of any portfolio optimization model cannot be isolated from the investor’s risk perception. To allow for differing risk preferences among investors, the efficient frontiers of Sharpe ratio maximization (SRM) and geometric mean maximization (GMM) are the appropriate metrics for making a comparison. The authors demonstrate that, for a given level of risk, the two optimization techniques will choose the same portfolio asset weights. Although GMM provides investors with a different way to approach portfolio optimization (maximizing terminal wealth), it is not a competing portfolio optimization technique to mean–variance maximization but, rather, a complementary one.
Original language | English |
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Pages (from-to) | 87-94 |
Number of pages | 8 |
Journal | Journal of Investing |
Volume | 30 |
Issue number | 4 |
DOIs | |
State | Published - Jun 2021 |
Scopus Subject Areas
- Finance
- Strategy and Management
- Management of Technology and Innovation
Keywords
- Performance measurement
- Portfolio construction
- Quantitative methods
- Statistical methods