Efficient integration of risk premia exposures into equity portfolios
B. Vaucher () and
A. Medvedev
Additional contact information
B. Vaucher: Syz Asset Management, Systematic Investments Group
A. Medvedev: Lombard Odier Asset Managers
Journal of Asset Management, 2017, vol. 18, issue 7, No 4, 538-546
Abstract:
Abstract We present a stock selection methodology that maximizes the expected returns of equity portfolios by efficiently managing their exposures to a given ensemble of risk premia, also known as factors. Our approach is mathematically grounded, robust in its design, and applicable in practice. It addresses several issues specific to factor investing, such as cross-sectional interactions between factors, the mismatch between the factors performance cycles and typical rebalancing periods, or the mitigation of interactions between the capital allocation schemes and factor exposures.
Keywords: Equity risk premia; Factor investing; Portfolio construction; Portfolio allocation; Stock selection (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://link.springer.com/10.1057/s41260-017-0052-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
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:pal:assmgt:v:18:y:2017:i:7:d:10.1057_s41260-017-0052-9
Ordering information: This journal article can be ordered from
http://www.springer.com/finance/journal/41260
DOI: 10.1057/s41260-017-0052-9
Access Statistics for this article
Journal of Asset Management is currently edited by Marielle de Jong and Dan diBartolomeo
More articles in Journal of Asset Management from Palgrave Macmillan
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().