On the informational market efficiency of the worldwide sovereign credit default swaps
Saker Sabkha (),
Christian Peretti and
Additional contact information
Saker Sabkha: Insitute of Management, University of South Brittany
Christian Peretti: Univ Lyon, University Claude Bernard Lyon 1
Dorra Hmaied: Univ of Carthage
Journal of Asset Management, 2019, vol. 20, issue 7, No 6, 608 pages
Abstract In this globalizing world, the search for predictions of asset returns across financial markets has challenged practitioners and academics for decades. Aware of this issue importance in developing investment strategy, we aim in this paper to give new evidence on the efficiency degree of the sovereign CDS markets. The new framework, used in this paper, combining a VECM and a FIGARCH models by a three-step estimation allows us to greatly improve the accuracy of the econometric estimates. Using data from 37 countries all over the world, throughout the period spanning from January 2006 to March 2017, our study provides worldwide evidence rejecting to some extent, conversely to the results of the literature, the randomness of the credit derivative markets. The implication of our results is that speculators can beat the market by predicting CDS performances, especially during crisis periods.
Keywords: Market efficiency; Worldwide sovereign CDS; VECM–FIGARCH (search for similar items in EconPapers)
JEL-codes: G01 G14 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
http://link.springer.com/10.1057/s41260-019-00142-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:pal:assmgt:v:20:y:2019:i:7:d:10.1057_s41260-019-00142-4
Ordering information: This journal article can be ordered from
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 ().