Gold and tail risks

Afees Salisu, Idris Adediran, Philip C. Omoke and Jean Paul Tchankam

Resources Policy, 2023, vol. 80, issue C

Abstract: In this study, we consider as a predictor of gold return predictability, an alternative measure of systematic risk using the tail risk obtained from the four variants (Adaptive, Symmetric absolute value, Asymmetric slope and Indirect GARCH) of the Conditional Autoregressive Value at Risk (CAViaR) of Engle and Manganelli (2004). We conduct distinct analyses for the gold-tail risk nexus for both 1% and 5% VaRs across the in-sample and out-of-sample forecasts. The results of the in-sample predictability indicate contrasting effects of own tail risk and oil tail risk (a proxy for global risk factor) with negative and positive effects, respectively on gold returns reinforcing the safe haven property of the gold market against global risk. Evidence of the out-of-sample predictability supports the inclusion of both own tail risk and oil tail risk over the benchmark model and single-predictor (own tail risk) model for improved out-of-sample forecasts of gold returns. The results leading to these conclusions are robust to alternative proxies for oil price and magnitudes of VaR.

Keywords: Gold returns; Tail risks; Predictability; Forecast evaluation (search for similar items in EconPapers)
JEL-codes: C22 C53 Q02 (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0301420722005979
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:jrpoli:v:80:y:2023:i:c:s0301420722005979

DOI: 10.1016/j.resourpol.2022.103154

Access Statistics for this article

Resources Policy is currently edited by R. G. Eggert

More articles in Resources Policy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().