Predicting gold volatility: Exploring the impact of extreme risk in the international commodity market

Yusui Tang and Juandan Zhong

Finance Research Letters, 2023, vol. 58, issue PB

Abstract: This paper mainly examines the performance of the tail risk (TR) constructed by 19 sub-categories of commodity price indices for predicting gold futures market volatility. Under the framework of the AR model, we compared the predictive capabilities of AR-type models incorporating the TR indicator as an additional explanatory variable against the AR benchmark model without the TR indicator. Our findings reveal that the incorporation of the TR indicator significantly improves the predictive accuracy of the gold futures volatility model. Notably, this enhancement is particularly pronounced during periods of heightened volatility.

Keywords: Commodity market; Gold futures; Tail risk; Volatility forecasting (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1544612323008632
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:finlet:v:58:y:2023:i:pb:s1544612323008632

DOI: 10.1016/j.frl.2023.104491

Access Statistics for this article

Finance Research Letters is currently edited by R. Gençay

More articles in Finance Research Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().