Horses for Courses: Mean-Variance for Asset Allocation and 1/N for Stock Selection

European Journal of Operational Research, Forthcoming

45 Pages Posted: 14 May 2019 Last revised: 26 May 2020

See all articles by Emmanouil Platanakis

Emmanouil Platanakis

University of Bath - School of Management

Charles Sutcliffe

University of Reading - ICMA Centre

Xiaoxia Ye

University of Liverpool Management School

Date Written: May 23, 2020

Abstract

For various organizational reasons, large investors typically split their portfolio decision into two stages - asset allocation and stock selection. We hypothesise that mean-variance models are superior to equal weighting for asset allocation, while the reverse applies for stock selection, as estimation errors are less of a problem for mean-variance models when used for asset allocation than for stock selection. We confirm this hypothesis for US data using Bayes-Stein with no short sales and variance based constraints. Robustness checks with four other types of mean-variance model (Black-Litterman with three different reference portfolios, minimum variance, Bayes diffuse prior and Markowitz), and a wide range of parameter settings support our conclusions. We also replicate our core results using Japanese data, with additional replications using the Fama-French 5, 10, 12 and 17 industry portfolios and equities from seven countries. In contrast to previous results, but consistent with our empirical results, we show analytically that the superiority of mean-variance over 1/N is increased when the assets have a lower cross-sectional idiosyncratic volatility, which we also confirm in a simulation analysis calibrated to US data.

Keywords: Investment analysis, asset allocation, stock selection, mean-variance, naive diversification, portfolio theory

JEL Classification: G11, G12

Suggested Citation

Platanakis, Emmanouil and Sutcliffe, Charles M. and Ye, Xiaoxia, Horses for Courses: Mean-Variance for Asset Allocation and 1/N for Stock Selection (May 23, 2020). European Journal of Operational Research, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3372334 or http://dx.doi.org/10.2139/ssrn.3372334

Emmanouil Platanakis (Contact Author)

University of Bath - School of Management ( email )

Claverton Down
Bath, BA2 7AY
United Kingdom

Charles M. Sutcliffe

University of Reading - ICMA Centre ( email )

Whiteknights Park
P.O. Box 242
Reading RG6 6BA
United Kingdom

Xiaoxia Ye

University of Liverpool Management School ( email )

Chatham Street
Liverpool, L69 7ZH
United Kingdom

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
1,141
Abstract Views
2,137
rank
20,025
PlumX Metrics