Optimal characteristic portfolios
Richard J. McGee and
Jose Olmo
Quantitative Finance, 2022, vol. 22, issue 10, 1853-1870
Abstract:
Characteristic-sorted portfolios are the workhorses of modern empirical finance, deployed widely to evaluate anomalies and construct asset pricing models. We propose a new method for their estimation that is simple to compute, makes no ex-ante assumption on the nature of the relationship between the characteristic and returns, and does not require ad hoc selections of percentile breakpoints or portfolio weighting schemes. Characteristic portfolio weights are implied directly from data, through maximizing a Mean–Variance objective function with mean and variance estimated non-parametrically from the cross-section of assets. To illustrate the method, we evaluate the size, value and momentum anomalies and find overwhelming empirical evidence of the outperformance of our methodology compared to standard methods for constructing characteristic-sorted portfolios.
Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://hdl.handle.net/10.1080/14697688.2022.2094282 (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:quantf:v:22:y:2022:i:10:p:1853-1870
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RQUF20
DOI: 10.1080/14697688.2022.2094282
Access Statistics for this article
Quantitative Finance is currently edited by Michael Dempster and Jim Gatheral
More articles in Quantitative Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().