Optimizing tracking error-constrained portfolios
Michael Maxwell,
Michael Daly,
Daniel Thomson and
Gary van Vuuren
Applied Economics, 2018, vol. 50, issue 54, 5846-5858
Abstract:
Active portfolios subject to tracking error (TE) constraints are the typical setup for active managers tasked with outperforming a benchmark. The risk and return relationship of such constrained portfolios is described by an ellipse in traditional mean-variance space and the ellipse’s flat shape suggests an additional constraint which improves the performance of the active portfolio. Although subsequent work isolated and explored different portfolios subject to these constraints, absolute portfolio risk has been consistently ignored. A different restriction – maximization of the traditional Sharpe ratio on the constant TE frontier in absolute risk/return space – is added here to the existing constraint set, and a method to generate this portfolio is explained. The resultant portfolio has a lower volatility and higher return than the benchmark, it satisfies the TE constraint and the ratio of excess absolute return to risk is maximized (i.e. maximum Sharpe ratio in absolute space).
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)
Downloads: (external link)
http://hdl.handle.net/10.1080/00036846.2018.1488069 (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:applec:v:50:y:2018:i:54:p:5846-5858
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20
DOI: 10.1080/00036846.2018.1488069
Access Statistics for this article
Applied Economics is currently edited by Anita Phillips
More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().