Enhanced Mean-Variance Portfolios - A Controlled Integration of Quantitative Return Estimates

39 Pages Posted: 25 Feb 2012 Last revised: 15 Oct 2016

Lars Kaiser

University of Liechtenstein

Marco J. Menichetti

Liechtenstein University

Aron Veress

University of Liechtenstein

Date Written: March 26, 2013


The intuitiveness and practicability of mean-variance portfolios largely depends on the accuracy of moment estimates, which are subject to large estimation errors and conditional on time. We propose a model accounting for factor dynamics in a Bayesian setting, in which the impact of estimation accuracy on the posterior distribution is endogenously derived from a linear predictive regression model. Thereby, we capture upside return potential for periods of high factor explained variance whilst constraining downside risk for periods of low predictive quality. Results are robust in a simulation and empirical setting.

Keywords: Bayesian portfolio construction, Black-Litterman, downside risk, enhanced indexing, goodness-of-fit, random sampling

JEL Classification: C11, C22, C53, C61, D24, G11, G12

Suggested Citation

Kaiser, Lars and Menichetti, Marco J. and Veress, Aron, Enhanced Mean-Variance Portfolios - A Controlled Integration of Quantitative Return Estimates (March 26, 2013). Journalof Portfolio Management, Vol. 40, No. 4, 2014; 25th Australasian Finance and Banking Conference 2012. Available at SSRN: https://ssrn.com/abstract=2010837 or http://dx.doi.org/10.2139/ssrn.2010837

Lars Kaiser (Contact Author)

University of Liechtenstein ( email )

Fürst Franz Josef Strasse
Vaduz, 9490
+423 265 1186 (Phone)

HOME PAGE: http://www.uni.li/lars.kaiser

Marco Josef Menichetti

Liechtenstein University ( email )

Vaduz, FL-9490

HOME PAGE: http://www.uni.li

Aron Veress

University of Liechtenstein ( email )

Vaduz, 9490
+423 265 1178 (Phone)
+423 265 1112 (Fax)

HOME PAGE: http://www.uni.li/

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