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

Gang-Jin Wang, Chi Xie, Shou Chen and Feng Han

Mathematical Problems in Engineering, 2014, vol. 2014, 1-13


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 (Gas- ) based on fractal and multifractal analysis. We focus our study on returns of the oil, gas, and 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- , and Gas- 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- > Oil-Gas > Oil- . 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.

Date: 2014
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DOI: 10.1155/2014/197069

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