Cross-Correlations between Energy and Emissions Markets: New Evidence from Fractal and Multifractal Analysis

摘要

We supply a new perspective to describe and understand the behavior of cross-correlations between energy and emissions markets. Namely, we investigate cross-correlations between oil and gas (Oil-Gas), oil and CO_2 (Oil-CO_2), and gas and CO_2 (Gas-CO_2) based on fractal and multifractal analysis. We focus our study on returns of the oil, gas, and CO_2 during the period of April 22, 2005-April 30, 2013. In the empirical analysis, by using the detrended cross-correlation analysis (DCCA) method, we find that cross-correlations for Oil-Gas, Oil-CO_2, and Gas-CO_2 obey a power-law and are weakly persistent. Then, we adopt the method of DCCA cross-correlation coefficient to quantify cross-correlations between energy and emissions markets. The results show that their cross-correlations are diverse at different time scales. Next, based on the multifractal DCCA method, we find that cross-correlated markets have the nonlinear and multifractal nature and that the multifractality strength for three cross-correlated markets is arranged in the order of Gas-CO_2 ＞ Oil-Gas ＞ Oil-CO_2• Finally, by employing the rolling windows method, which can be used to investigate time-varying cross-correlation scaling exponents, we analyze short-term and long-term market dynamics and find that the recent global financial crisis has a notable influence on short-term and long-term market dynamics.