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Uncertainty and the volatility forecasting power of option‐implied volatility

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  • Byounghyun Jeon
  • Sung Won Seo
  • Jun Sik Kim

Abstract

This study investigates the impact of uncertainty on the volatility forecasting power of option‐implied volatility. Option‐implied volatility is a powerful predictor of future volatility, particularly during periods of high uncertainty. This is consistent with option‐implied volatility being largely determined by volatility‐informed traders (rather than directional traders) when uncertainty is high. New volatility forecasting models that incorporate such interaction outperform benchmark models, both in‐ and out‐of‐sample. The new models also better predict future volatility during the 2008 global financial crisis, for which benchmark models perform poorly. The results are robust to alternative choices of benchmark models, loss functions, and estimation windows.

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  • Byounghyun Jeon & Sung Won Seo & Jun Sik Kim, 2020. "Uncertainty and the volatility forecasting power of option‐implied volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1109-1126, July.
  • Handle: RePEc:wly:jfutmk:v:40:y:2020:i:7:p:1109-1126
    DOI: 10.1002/fut.22116
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    3. Zhang, Hailiang & Sattar, Muhammad Atif & Wang, Haijun, 2024. "Uncertainty measure: As a proxy for the degree of market imperfection," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 159-171.
    4. Dimos S. Kambouroudis & David G. McMillan & Katerina Tsakou, 2021. "Forecasting realized volatility: The role of implied volatility, leverage effect, overnight returns, and volatility of realized volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1618-1639, October.
    5. Gu, Tiantian & Venkateswaran, Anand & Erath, Marc, 2023. "Impact of fiscal stimulus on volatility: A cross-country analysis," Research in International Business and Finance, Elsevier, vol. 65(C).
    6. Lu, Fei & Ma, Feng & Li, Pan & Huang, Dengshi, 2022. "Natural gas volatility predictability in a data-rich world," International Review of Financial Analysis, Elsevier, vol. 83(C).
    7. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2021. "Realized skewness and the short-term predictability for aggregate stock market volatility," Economic Modelling, Elsevier, vol. 103(C).
    8. Wael DAMMAK, 2024. "Assessing Effect of Market Sentiment on Pricing of European Currency Options ‎," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(6), pages 1224-1244, June.
    9. Hui Qu & Tianyang Wang & Peng Shangguan & Mengying He, 2024. "Revisiting the puzzle of jumps in volatility forecasting: The new insights of high‐frequency jump intensity," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(2), pages 218-251, February.
    10. Yanchu Liu & Chen Liu & Yiyao Chen & Xianming Sun, 2024. "Option‐Implied Ambiguity and Equity Return Predictability," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(9), pages 1556-1577, September.
    11. Li, Xiafei & Liang, Chao & Chen, Zhonglu & Umar, Muhammad, 2022. "Forecasting crude oil volatility with uncertainty indicators: New evidence," Energy Economics, Elsevier, vol. 108(C).

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