Mean-variance optimization using forward-looking return estimates

Patrick Bielstein () and Matthias X. Hanauer ()
Additional contact information
Patrick Bielstein: Technical University of Munich
Matthias X. Hanauer: Technical University of Munich

Review of Quantitative Finance and Accounting, 2019, vol. 52, issue 3, No 6, 815-840

Abstract: Abstract Despite its theoretical appeal, Markowitz mean-variance portfolio optimization is plagued by practical issues. It is especially difficult to obtain reliable estimates of a stock’s expected return. Recent research has therefore focused on minimum volatility portfolio optimization, which implicitly assumes that expected returns for all assets are equal. We argue that investors are better off using the implied cost of capital based on analysts’ earnings forecasts as a forward-looking return estimate. Correcting for predictable analyst forecast errors, we demonstrate that mean-variance optimized portfolios based on these estimates outperform on both an absolute and a risk-adjusted basis the minimum volatility portfolio as well as naive benchmarks, such as the value-weighted and equally-weighted market portfolio. The results continue to hold when extending the sample to international markets, using different methods for estimating the forward-looking return, including transaction costs, and using different optimization constraints.

Keywords: Portfolio optimization; Expected returns; Implied cost of capital; Momentum; Maximum sharpe ratio (search for similar items in EconPapers)
JEL-codes: G11 G12 G17 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s11156-018-0727-4 Abstract (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:rqfnac:v:52:y:2019:i:3:d:10.1007_s11156-018-0727-4

Ordering information: This journal article can be ordered from
http://www.springer.com/finance/journal/11156/PS2

DOI: 10.1007/s11156-018-0727-4

Access Statistics for this article

Review of Quantitative Finance and Accounting is currently edited by Cheng-Few Lee

More articles in Review of Quantitative Finance and Accounting from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().