Journal article

Multi-asset portfolio optimization and out-of-sample performance: an evaluation of Black-Litterman, mean-variance, and naive diversification approaches


Authors listBessler, Wolfgang; Opfer, Heiko; Wolff, Dominik

Publication year2017

Pages1-30

JournalEuropean Journal of Finance

Volume number23

Issue number1

ISSN1351-847X

eISSN1466-4364

Open access statusGreen

DOI Linkhttps://doi.org/10.1080/1351847X.2014.953699

PublisherTaylor and Francis Group


Abstract
The Black-Litterman model aims to enhance asset allocation decisions by overcoming the problems of mean-variance portfolio optimization. We propose a sample-based version of the Black-Litterman model and implement it on a multi-asset portfolio consisting of global stocks, bonds, and commodity indices, covering the period from January 1993 to December 2011. We test its out-of-sample performance relative to other asset allocation models and find that Black-Litterman optimized portfolios significantly outperform naive-diversified portfolios (1/N rule and strategic weights), and consistently perform better than mean-variance, Bayes-Stein, and minimum-variance strategies in terms of out-of-sample Sharpe ratios, even after controlling for different levels of risk aversion, investment constraints, and transaction costs. The BL model generates portfolios with lower risk, less extreme asset allocations, and higher diversification across asset classes. Sensitivity analyses indicate that these advantages are due to more stable mixed return estimates that incorporate the reliability of return predictions, smaller estimation errors, and lower turnover.



Citation Styles

Harvard Citation styleBessler, W., Opfer, H. and Wolff, D. (2017) Multi-asset portfolio optimization and out-of-sample performance: an evaluation of Black-Litterman, mean-variance, and naive diversification approaches, European Journal of Finance, 23(1), pp. 1-30. https://doi.org/10.1080/1351847X.2014.953699

APA Citation styleBessler, W., Opfer, H., & Wolff, D. (2017). Multi-asset portfolio optimization and out-of-sample performance: an evaluation of Black-Litterman, mean-variance, and naive diversification approaches. European Journal of Finance. 23(1), 1-30. https://doi.org/10.1080/1351847X.2014.953699



Keywords


Bayes-SteinBlack-LittermanC61COMMODITY FUTURESCOVARIANCESG11mean-varianceminimum-variancenNAIVE DIVERSIFICATIONRETURNSSHARPEUTILITY

Last updated on 2025-10-06 at 10:40