 Volatility forecasting of Chinese energy market: Which uncertainty have better performance?Jiaming Zhang, Yitian Xiang, Yang Zou and Songlin Guo International Review of Financial Analysis, 2024, vol. 91, issue C Abstract: This paper examines the effects of seven uncertainty indices on Chinese energy price volatility and analyses the influencing factors using the extended GARCH-MIDAS model. Our in-sample analysis shows that energy market volatility is negatively impacted by global and Chinese economic policy uncertainty (GEPU, CNEPU), the geopolitical risk act index (GPRA), and the climate policy uncertainty index (CPU). Out-of-sample forecasting results demonstrate that the CPU is a major cause of energy volatility in China, and our extended model exhibits higher forecast accuracy. Additionally, we discover that the CPU has a greater capacity for energy volatility during periods of low volatility, while high energy volatility is often associated with GPR. Finally, the outbreak of the Russia-Ukraine conflict resulted in a decline in the predictive capacity of the CPU while causing a boost in the EPU's predictive power. Keywords: Chinese energy market; Uncertainty index; GARCH-MIDAS; Volatility forecasting (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:91:y:2024:i:c:s1057521923004684 DOI: 10.1016/j.irfa.2023.102952 Access Statistics for this article International Review of Financial Analysis is currently edited by B.M. Lucey More articles in International Review of Financial Analysis from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.