The role of long memory in hedging effectiveness

Jerry Coakley, Jian Dollery and Neil Kellard ()

Computational Statistics & Data Analysis, 2008, vol. 52, issue 6, 3075-3082

Abstract: A joint fractionally integrated, error-correction and multivariate GARCH (FIEC-BEKK) approach is applied to investigate hedging effectiveness using daily data 1995-2005. The findings reveal the proxied error-correction term has a long memory component that theoretically should affect hedging effectiveness. When the FIEC model empirical conditions are satisfied, the FIEC-BEKK hedging strategy outperforms the OLS benchmark out of sample in terms of both variance reduction and hedger utility. A bootstrap exercise indicates that the variance reduction is statistically significant.

Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-9473(07)00415-X
Full text for ScienceDirect subscribers only.

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:eee:csdana:v:52:y:2008:i:6:p:3075-3082

Access Statistics for this article

Computational Statistics & Data Analysis is currently edited by S.P. Azen

More articles in Computational Statistics & Data Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().