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

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.