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Rare Disaster Concerns in Predicting Oil

Author

Listed:
  • Zhen Cao
  • Yuanzhi Wang
  • Lean Yu
  • Qunzi Zhang

Abstract

We construct a text‐based measure of oil market uncertainty using Wall Street Journal front‐page articles from January 1986 to December 2022. This measure, the news implied oil volatility (NOVX), is derived from over 100,000 articles and reflects oil market uncertainty during key historical events. NOVX emerges as a significant predictor of oil returns, both in‐sample and out‐of‐sample, outperforming existing predictors like real‐time, interest rate, and macroeconomic variables, as well as other news‐based indices. Following Manela and Moreira (2017), we decompose NOVX to identify different rare disaster concerns. Among these concerns, those related to government and natural disasters play particularly significant roles in forecasting oil returns. Additionally, we identify an economic mechanism: increases in news‐implied oil volatility reduce oil production and economic activity, while increasing oil inventories and decreasing oil prices.

Suggested Citation

  • Zhen Cao & Yuanzhi Wang & Lean Yu & Qunzi Zhang, 2026. "Rare Disaster Concerns in Predicting Oil," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 46(1), pages 20-42, January.
    • Handle: RePEc:wly:jfutmk:v:46:y:2026:i:1:p:20-42
    DOI: 10.1002/fut.70047
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    References listed on IDEAS

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