Oil futures volatility predictability: Evidence based on Twitter-based uncertainty

Qiaoqi Lang, Xinjie Lu, Feng Ma and Dengshi Huang

Finance Research Letters, 2022, vol. 47, issue PA

Abstract: This paper explores the influence of the Twitter-based uncertainty index on oil futures market volatility. The Twitter-based Market Uncertainty (TMU) index, based on the novel Markov-regime GARCH-MIDAS model, may significantly improve prediction accuracy for oil futures volatility. Moreover, the TMU was still useful in predicting oil volatility during the COVID-19 pandemic. Furthermore, when the alternative Twitter-based uncertainty index, Twitter-based Economic Uncertainty (TEU), is adopted, these results are also robust. This paper highlights the importance of the Twitter-based uncertainty index for oil futures market.

Keywords: Oil futures market; Twitter-based uncertainty; Markov-regime model; GARCH-MIDAS model; COVID-19 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:47:y:2022:i:pa:s1544612321004992

DOI: 10.1016/j.frl.2021.102536

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