Skewed multifractal cross-correlation between price and volume during the COVID-19 pandemic: Evidence from China and European carbon markets

Zhihui Li and Yun Tian

Applied Energy, 2024, vol. 371, issue C, No S0306261924010997

Abstract: This article presents skewed multifractal cross-correlations between price and volumes on the carbon emissions trading markets in China and Europe. The BEAST algorithm is first used to detect change points in financial time series and to divide series into two adjacent intervals. The study performs a skewed multifractal detrended cross-correlations analysis and further investigates the impact of the COVID-19 pandemic on multifractality and risk between price and volumes on both markets, from 30 April 2014 to 25 July 2023. The results demonstrate that the multifractality of cross-correlations in both markets underwent significant changes before and after the change points, indicating skewed multifractality. In both markets, the price-volume nexus exhibited increased anti-persistence, higher multifractal risks, and reduced market efficiency after the outbreak of the pandemic. This may be attributed to the pandemic-induced shifts in carbon emissions trading market trends and heightened volatility. In conclusion, the outbreak of the pandemic had increased the instability of the carbon markets and the Hubei market exhibited higher levels of multifractality and multifractal risk.

Keywords: Change-point; Skewed multifractal cross-correlation; COVID-19 pandemic; The BEAST algorithm (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.apenergy.2024.123716

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