An averaging framework for minimum-variance portfolios: Optimal rules for combining portfolio weights

Roland Füss, Thorsten Glück, Christian Koeppel and Felix Miebs
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Roland Füss: Swiss Finance Institute; University of St. Gallen - School of Finance
Thorsten Glück: Wiesbaden Business School
Christian Koeppel: University of St. Gallen
Felix Miebs: University of Applied Sciences Cologne

No 24-10, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: We propose an averaging framework for combining minimum-variance strategies to either minimize the expected out-of-sample variance or maximize the expected out-of-sample Sharpe ratio. Our framework overcomes the problem of selecting the “best” strategy ex-ante by optimally averaging over portfolio weights. This averaging procedure has an intuitive economic interpretation because it resembles a fund-of-fund approach, where each minimum-variance strategy represents a single fund. In a range of simulations, for a set of well-established strategies, we show that optimally averaging over portfolio weights improves the out-ofsample variance and Sharpe ratio. We confirm the finding of our simulation study on empirical data.

Keywords: Averaging; diversification; estimation error; portfolio optimization; shrinkage. (search for similar items in EconPapers)
JEL-codes: G11 (search for similar items in EconPapers)
Pages: 55 pages
Date: 2024-01
New Economics Papers: this item is included in nep-rmg
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp2410

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