Item Type | Monograph (Working Paper) |
Abstract | We propose an averaging rule that combines established minimum-variance strategies to minimize the expected out-of-sample variance. Our rule overcomes the problem of selecting the “best” strategy ex-ante and diversifies remaining estimation errors of the single strategies included in the averaging. Extensive simulations show that the contributions of estimation errors to the out-of-sample variances are uncorrelated between the considered strategies. This implies that averaging over multiple strategies o˙ers sizable diversification benefits. Our rule leverages these benefits and compares favorably to eleven strategies in terms of out-of-sample variance on both simulated and empirical data sets. The Sharpe ratio is across all data sets at least 25% higher than for the 1/N portfolio. |
Authors | Füss, Roland; Koeppel, Christian & Miebs, Felix |
Language | English |
Keywords | Averaging; diversification; estimation error; portfolio optimization; shrinkage |
Subjects | economics finance |
HSG Classification | contribution to scientific community |
HSG Profile Area | SOF - System-wide Risk in the Financial System |
Date | 8 February 2021 |
Publisher | SoF-HSG |
Place of Publication | St.Gallen |
Series Name | School of Finance Working Paper Series |
Volume | 2021/05 |
Number | 05 |
Page Range | 1-69 |
Number of Pages | 69 |
Contact Email Address | Roland.Fuess@unisg.ch |
Depositing User | Carolin Hitz |
Date Deposited | 08 Feb 2021 14:32 |
Last Modified | 08 Feb 2021 14:32 |
URI: | https://www.alexandria.unisg.ch/publications/262294 |
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CitationFüss, Roland; Koeppel, Christian & Miebs, Felix: Diversifying estimation errors: An efficient averaging rule for portfolio optimization. School of Finance Working Paper Series, 2021, 05. Statisticshttps://www.alexandria.unisg.ch/id/eprint/262294
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