Petroleum market volatility tracker in China

Abstract

This paper constructs a China petroleum market volatility (CPMV) tracker based on Chinese newspapers from March 2018 to July 2021 for the first time. Then, we use the Generalized AutoRegressive Conditional Heteroskedasticity mixed-data sampling (GARCH-MIDAS) model to explore the explanatory ability of the CPMV tracker, and the results show that compared with other volatility trackers, the CPMV tracker has a superior ability to explain the volatility of Shanghai crude oil futures (SC). Further, we conduct a more detailed analysis of the CPMV tracker, and find that the CPMV tracker can reflect the information and market sentiment of SC, and needs to be taken into consideration when explaining SC volatility.