Modelling time varying volatility spillovers and conditional correlations across commodity metal futures
Menelaos Karanasos,
Faek Menla Ali,
Zannis Margaronis and
Rajat Nath
International Review of Financial Analysis, 2018, vol. 57, issue C, 246-256
Abstract:
This paper examines how the most prevalent stochastic properties of key metal futures returns have been affected by the recent financial crisis using both mapped and unmapped data. Our results suggest that copper and gold futures returns exhibit time-varying persistence in their corresponding conditional volatilities over the crisis period; in particular, such persistence increases during periods of high volatility compared with low volatility. The estimation of a bivariate GARCH model further shows the existence of time-varying volatility spillovers between these returns during the different stages of such a crisis. Our results, which are broadly the same in relation to the use of mapped or unmapped data, suggest that the volatilities of copper and gold are inherently linked, although these metals have very different applications.
Keywords: Financial crisis; Metal futures; Structural breaks; Time-varying volatility spillovers (search for similar items in EconPapers)
JEL-codes: C32 Q02 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S105752191730176X
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:finana:v:57:y:2018:i:c:p:246-256
DOI: 10.1016/j.irfa.2017.11.003
Access Statistics for this article
International Review of Financial Analysis is currently edited by B.M. Lucey
More articles in International Review of Financial Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().