The spillover effects between natural gas and crude oil markets: The correlation network analysis based on multi-scale approach

Abstract This paper proposes a new compound model to investigate the dynamic linkage mechanism between the natural gas and crude oil markets from the multi-scale perspective. In the proposed model, two main steps are involved: multi-scale analysis and network research. Based on the bivariate empirical mode decomposition (BEMD) and Fine-to-Coarse algorithm, the multi-scale analysis ensures the relationship between price fluctuations can be studied under three different time-scales, which corresponding to market disequilibrium, significant events, and long term trend. By integrating the grey correlation degree and Coarse-Gaining algorithm, the network research reveals the dynamic spillover effects of the two markets at different time-scales. To capture the different linked characteristic in different periods, the sample data of Henry Hub and WTI spot prices from 1997 to 2017 is divided into three periods. We transfer the daily correlations between the price fluctuations with specific time-scale into the correlation patterns and establish the network based on their transmission relations. The crucial correlation patterns and the significant transmission relations are revealed by some network indicators. And the proposed approach in this paper can be applied to other field of research.