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The Nelson–Siegel Model of the Term Structure of Option Implied Volatility and Volatility Components

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  • Biao Guo
  • Qian Han
  • Bin Zhao

Abstract

We develop the Nelson–Siegel model in the context of option‐implied volatility term structure and study the time series of volatility components. Three components, corresponding to the level, slope, and curvature of the volatility term structure, can be interpreted as the long‐, medium‐, and short‐term volatilities. The long‐term component is persistent and driven by macroeconomic variables, the medium‐term by market default risk, and the short‐term by financial market conditions. The three‐factor Nelson–Siegel model has superior performance in forecasting the volatility term structure, with better out‐of‐sample forecasts than the popular deterministic implied volatility function and a restricted two‐factor model, providing support to the literature of component volatility models. © 2014 Wiley Periodicals, Inc. Jrl Fut Mark 34:788–806, 2014

Suggested Citation

  • Biao Guo & Qian Han & Bin Zhao, 2014. "The Nelson–Siegel Model of the Term Structure of Option Implied Volatility and Volatility Components," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(8), pages 788-806, August.
    • Handle: RePEc:wly:jfutmk:v:34:y:2014:i:8:p:788-806
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    Cited by:

    1. Chen, Ying & Han, Qian & Niu, Linlin, 2018. "Forecasting the term structure of option implied volatility: The power of an adaptive method," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 157-177.
    2. Wu, Lingke & Liu, Dehong & Yuan, Jianglei & Huang, Zhenhuan, 2022. "Implied volatility information of Chinese SSE 50 ETF options," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 609-624.
    3. Peter K. Friz & Paul Gassiat & Paolo Pigato, 2022. "Short-dated smile under rough volatility: asymptotics and numerics," Quantitative Finance, Taylor & Francis Journals, vol. 22(3), pages 463-480, March.
    4. Alexander Bogin & William Doerner, 2014. "Generating historically-based stress scenarios using parsimonious factorization," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 15(5), pages 591-611, November.
    5. Anders Merrild Posselt, 2022. "Dynamics in the VIX complex," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(9), pages 1665-1687, September.
    6. Biao Guo & Qian Han & Hai Lin, 2018. "Are there gains from using information over the surface of implied volatilities?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(6), pages 645-672, June.
    7. Shi, Yukun & Stasinakis, Charalampos & Xu, Yaofei & Yan, Cheng, 2022. "Market co-movement between credit default swap curves and option volatility surfaces," International Review of Financial Analysis, Elsevier, vol. 82(C).
    8. Covindassamy, Genevre & Robe, Michel A. & Wallen, Jonathan, 2016. "Sugar With Your Coffee?: Financials, Fundamentals, and Soft Price Uncertainty," IDB Publications (Working Papers) 8588, Inter-American Development Bank.
    9. Sudarshan Kumar & Sobhesh Kumar Agarwalla & Jayanth R. Varma & Vineet Virmani, 2023. "Harvesting the volatility smile in a large emerging market: A Dynamic Nelson–Siegel approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(11), pages 1615-1644, November.
    10. Giovanni Campisi & Silvia Muzzioli, 2021. "Designing volatility indices for Austria, Finland and Spain," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(3), pages 369-455, September.
    11. Michel A. Robe & Jonathan Wallen, 2016. "Fundamentals, Derivatives Market Information and Oil Price Volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(4), pages 317-344, April.
    12. Lovreta, Lidija & Silaghi, Florina, 2020. "The surface of implied firm’s asset volatility," Journal of Banking & Finance, Elsevier, vol. 112(C).

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    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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