Information spillover and market connectedness: multi-scale quantile-on-quantile analysis of the crude oil and carbon markets

Xiaohang Ren, Yue Dou, Kangyin Dong () and Yiying Li

Applied Economics, 2022, vol. 54, issue 38, 4465-4485

Abstract: The asymmetric interdependence of carbon futures and crude oil futures prices in different market conditions remains unsettled in the literature. This study aims to quantify the crude oil price impacts on carbon price across the carbon-oil distribution in Phase III. For this purpose, we employ two novel methods, namely the quantile Granger causality test and the quantile-on-quantile regression methods. To detect the short-, medium-, and long-term impacts of the crude oil price on carbon price, we further decompose the sample series into six components using the wavelet method. Accordingly, we are able to estimate the nexus between carbon futures and crude oil futures prices in different time and frequency domains. Through a series of robustness checks, we find our results stable and robust, indicating that the crude oil impact on carbon price is asymmetric, conditional on the whole carbon and crude oil price distributions. Furthermore, the crude oil impact varies across different time scales, and shows negative signs throughout the whole carbon price distribution in the short term and basically positive signs in the medium and long term. Based on the above findings, we highlight several important policy implications to promote better market regulation and portfolio optimization.

Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (26)

Downloads: (external link)
http://hdl.handle.net/10.1080/00036846.2022.2030855 (text/html)
Access to full text is restricted to subscribers.

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:taf:applec:v:54:y:2022:i:38:p:4465-4485

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20

DOI: 10.1080/00036846.2022.2030855

Access Statistics for this article

Applied Economics is currently edited by Anita Phillips

More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().