Refinement of the hedging ratio using copula-GARCH models
Waël Louhichi () and
Hassen Raïs
Additional contact information
Waël Louhichi: Essca School of Management
Journal of Asset Management, 2019, vol. 20, issue 5, No 7, 403-411
Abstract:
Abstract The goal of this paper is to improve the effectiveness of hedge overlays via futures against certain investment risks. Accordingly, we propose a dynamic generalized autoregressive conditional heteroscedasticity (GARCH) model based on different copulas in order to specify the joint distribution between spot and futures returns. We test our model for several types of asset indices: S&P 500 for stocks, Brent for energy, Wheat for commodities, Gold for precious metals and Euro/Dollar for exchange rate market. The empirical results show that copula-GARCH models outperform the conventional model and improve the effectiveness of the hedging ratio. Our approach is useful for investors and risk managers, when determining their hedging strategy.
Keywords: Hedging ratio; Copula; GARCH (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://link.springer.com/10.1057/s41260-019-00133-5 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:20:y:2019:i:5:d:10.1057_s41260-019-00133-5
Ordering information: This journal article can be ordered from
http://www.springer.com/finance/journal/41260
DOI: 10.1057/s41260-019-00133-5
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 ().