Long memory and structural breaks in modeling the return and volatility dynamics of precious metals
Mohamed Arouri (),
Amine Lahiani and
Duc Khuong Nguyen
The Quarterly Review of Economics and Finance, 2012, vol. 52, issue 2, 207-218
We investigate the potential of structural changes and long memory (LM) properties in returns and volatility of the four major precious metal commodities traded on the COMEX markets (gold, silver, platinum and palladium). Broadly speaking, a random variable is said to exhibit long memory behavior if its autocorrelation function is not integrable, while structural changes can induce sudden and significant shifts in the time-series behavior of that variable. The results from implementing several parametric and semiparametric methods indicate strong evidence of long range dependence in the daily conditional return and volatility processes for the precious metals. Moreover, for most of the precious metals considered, this dual long memory is found to be adequately captured by an ARFIMA–FIGARCH model, which also provides better out-of-sample forecast accuracy than several popular volatility models. Finally, evidence shows that conditional volatility of precious metals is better explained by long memory than by structural breaks.
Keywords: Precious metal prices; Long memory; Structural breaks; ARFIMA–FIGARCH (search for similar items in EconPapers)
JEL-codes: C22 O13 Q47 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (97) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
Working Paper: Long memory and structural breaks in modeling the return and volatility dynamics of precious metals (2013)
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:eee:quaeco:v:52:y:2012:i:2:p:207-218
Access Statistics for this article
The Quarterly Review of Economics and Finance is currently edited by R. J. Arnould and J. E. Finnerty
More articles in The Quarterly Review of Economics and Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().