Diversifying Estimation Errors: An Efficient Averaging Rule for Portfolio Optimization

71 Pages Posted: 11 Feb 2021 Last revised: 8 Jan 2023

See all articles by Roland Füss

Roland Füss

Swiss Finance Institute; University of St. Gallen - School of Finance

Christian Koeppel

University of St. Gallen

Felix Miebs

University of Applied Sciences Cologne

Date Written: February 8, 2021

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 offers 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.

Keywords: Averaging; diversification; estimation error; portfolio optimization; shrinkage

JEL Classification: G11

Suggested Citation

Füss, Roland and Koeppel, Christian and Miebs, Felix, Diversifying Estimation Errors: An Efficient Averaging Rule for Portfolio Optimization (February 8, 2021). University of St.Gallen, School of Finance Research Paper No.2021/05, Available at SSRN: https://ssrn.com/abstract=3781592 or http://dx.doi.org/10.2139/ssrn.3781592

Roland Füss (Contact Author)

Swiss Finance Institute ( email )

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

University of St. Gallen - School of Finance ( email )

Unterer Graben 21
St.Gallen, CH-9000
Switzerland
+41 (0)71 224 70 42 (Phone)
+41 (0)71 224 70 88 (Fax)

HOME PAGE: http://www.sbf.unisg.ch/en/Lehrstuehle/Lehrstuhl_Fuess.aspx

Christian Koeppel

University of St. Gallen ( email )

Langgasse 1
St. Gallen, 9008
Switzerland

Felix Miebs

University of Applied Sciences Cologne ( email )

Claudiusstrasse 1
Cologne, 50678
United States

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