Quantitative or momentum-based multi-style rotation? UK experience

Andrew Clare, Svetlana Sapuric and Natasa Todorovic ()
Additional contact information
Natasa Todorovic: Faculty of Finance, Cass Business School

Journal of Asset Management, 2010, vol. 10, issue 6, No 3, 370-381

Abstract: Abstract The objective of this article is to examine whether short-term variation in the ranking of size and style index returns in the UK equity market is better predictable and exploitable by means of quantitative or momentum style-rotation strategies. Using UK index data, we assess the profitability of a number of long-only and long/short multi-style-rotation strategies based on these two alternative methods. The findings suggest that trading rules based on simple short-term momentum strategies are able to generate higher Sharpe ratios and greater end-of-period wealth at a reasonable level of transaction costs than our quantitatively based trading rules. This result is particularly pronounced among the long-only strategies.

Keywords: multi-style rotation; ordered logit; momentum (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://link.springer.com/10.1057/jam.2009.19 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:10:y:2010:i:6:d:10.1057_jam.2009.19

Ordering information: This journal article can be ordered from
http://www.springer.com/finance/journal/41260

DOI: 10.1057/jam.2009.19

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 ().