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

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  • Lang, Qiaoqi
  • Lu, Xinjie
  • Ma, Feng
  • Huang, Dengshi

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.

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  • Lang, Qiaoqi & Lu, Xinjie & Ma, Feng & Huang, Dengshi, 2022. "Oil futures volatility predictability: Evidence based on Twitter-based uncertainty," Finance Research Letters, Elsevier, vol. 47(PA).
    • Handle: RePEc:eee:finlet:v:47:y:2022:i:pa:s1544612321004992
    DOI: 10.1016/j.frl.2021.102536
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    7. Vicknair, David & Tansey, Michael & O'Brien, Thomas E., 2022. "Measuring fossil fuel reserves: A simulation and review of the U.S. Securities and Exchange Commission approach," Resources Policy, Elsevier, vol. 79(C).
    8. Guo, Kun & Liu, Fengqi & Sun, Xiaolei & Zhang, Dayong & Ji, Qiang, 2023. "Predicting natural gas futures’ volatility using climate risks," Finance Research Letters, Elsevier, vol. 55(PA).
    9. Zeng, Qing & Zhang, Jixiang & Zhong, Juandan, 2024. "China's futures market volatility and sectoral stock market volatility prediction," Energy Economics, Elsevier, vol. 132(C).
    10. Zhang, Yonggang & Hyder, Mansoor & Baloch, Zulfiqar Ali & Qian, Chong & Berk Saydaliev, Hayot, 2022. "Nexus between oil price volatility and inflation: Mediating nexus from exchange rate," Resources Policy, Elsevier, vol. 79(C).
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