Factor-Targeted Asset Allocation: A Reverse Optimization Approach

Jacky S. H. Lee and Marco Salerno

Financial Analysts Journal, 2023, vol. 79, issue 3, 75-94

Abstract: We demonstrate that using a mean-variance portfolio to obtain implied factor risk premia can result in stable weights for a factor portfolio when assets’ expected returns follow a factor structure that is subject to pricing errors. We propose a methodology to construct asset portfolios based on these factor portfolio weights, taking into account the possibility of pricing errors. Our simulation shows that these “factor-targeted” portfolios have higher and more stable Sharpe ratios than traditional allocation methodologies in various scenarios involving expected return assumptions. Furthermore, while our factor-targeted portfolios exhibit similar Sharpe ratios to the mean-variance portfolio built using factors for high levels of pricing errors, the factor-targeted portfolios have more stable portfolio weights, which makes them more appealing in practice.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/0015198X.2023.2214074 (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:taf:ufajxx:v:79:y:2023:i:3:p:75-94

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/ufaj20

DOI: 10.1080/0015198X.2023.2214074

Access Statistics for this article

Financial Analysts Journal is currently edited by Maryann Dupes

More articles in Financial Analysts Journal from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().