Can implied volatility predict returns on oil market? Evidence from Cross-Quantilogram Approach

Bechir Raggad

Resources Policy, 2023, vol. 80, issue C

Abstract: This paper employs the Cross-Quantilogram methodology proposed by Han et al. (2016) to investigate whether the implied volatility of crude oil (OVX) ameliorates the directional predictability of the oil price returns. Our main result documents the existence of a quantile predictability from OVX to WTI returns when the crude oil implied volatility is in the upper conditional quantile. On the other hand, no sufficient evidence in directional predictability is found when the OVX is at the lower to intermediate level. As a part of robustness check, the same analysis was conducted to the Brent returns. The pattern of directional predictability (similar signs) broadly corresponds with those observed on the WTI returns, however, it seems that OVX is more predictive for Brent than WTI. Particularly, the predictive power of OVX is found to be significant during periods of moderate to high OVX and mainly concentrated on lower to intermediate variations in Brent returns. As a result, implied volatility can be considered as a driver with respect to the forthcoming variations of the returns in the spot oil market. Insights gleaned from this study could have important implications for investors and policymakers in terms of portfolio and risk management decisions.

Keywords: Quantile dependence; Directional predictability; Granger causalities in quantiles; Cross-quantilogram; Crude oil volatility index (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0301420722007206
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:s0301420722007206

DOI: 10.1016/j.resourpol.2022.103277

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 ().