The role of coronavirus news in the volatility forecasting of crude oil futures markets: Evidence from China

Zibo Niu, Yuanyuan Liu, Wang Gao and Hongwei Zhang

Resources Policy, 2021, vol. 73, issue C

Abstract: Based on the high-frequency heterogeneous autoregressive (HAR) model, this paper investigates whether coronavirus news (in China and globally) contains incremental information to predict the volatility of China's crude oil, and studies which types of coronavirus news can better forecast China's crude oil volatility. Considering the information overlap among various coronavirus news items and making full use of the information in various coronavirus news items, this paper uses two prevailing shrinkage methods, lasso and elastic nets, to select coronavirus news items and then uses the HAR model to predict China's crude oil volatility. The results show that (i) coronavirus news can be utilized to significantly predict China's crude oil volatility for both in-sample and out-of-sample analyses; (ii) the Panic Index (PI) and the Country Sentiment Index (CSI) have a greater impact on China's crude oil volatility. Additionally, China's Fake News Index (FNI) have a significant impact on China's crude oil volatility forecast; and (iii) global coronavirus news provides more incremental information than China's coronavirus news for predicting the volatility of China's crude oil market, which indicates that global coronavirus news is also a key factor to consider when predicting the market volatility of China's crude oil.

Keywords: China's crude oil futures; COVID-19; Volatility forecasting; Coronavirus news; MCS test (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (29)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jrpoli:v:73:y:2021:i:c:s0301420721001872

DOI: 10.1016/j.resourpol.2021.102173

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