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

Author

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  • 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 three volatility components in the model. We show that these 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 the short-term component is highly correlated with the VIX index. We further demonstrate that macroeconomic and financial variables help explain these volatility components. The long-term component is driven by macroeconomic variables, the medium-term by market default risk and the short-term by financial market conditions. These are revealing because after decades of research existing literature have failed to link these variables to option pricing. We also show that the Nelson-Siegel model has superior performance in forecasting the volatility term structure, compared with the popular implied volatility function method and the Heston stochastic volatility model. Finally, we demonstrate that the three-factor Nelson-Siegel model is better in out-of-sample prediction than a two-factor model, providing support to the literature of component volatility models.

Suggested Citation

  • Qian Han & Bin Zhao, 2014. "The Nelson-Siegel Model of the Term Structure of Option Implied Volatility and Volatility Components," Working Papers 2014-01-15, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
  • Handle: RePEc:wyi:wpaper:002218
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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. Won Joong Kim & Gunho Jung & Sun-Yong Choi, 2020. "Forecasting CDS Term Structure Based on Nelson–Siegel Model and Machine Learning," Complexity, Hindawi, vol. 2020, pages 1-23, July.
    10. 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.
    11. 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.
    12. 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.
    13. F. Leung & M. Law & S. K. Djeng, 2024. "Deterministic modelling of implied volatility in cryptocurrency options with underlying multiple resolution momentum indicator and non-linear machine learning regression algorithm," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-25, December.
    14. Lovreta, Lidija & Silaghi, Florina, 2020. "The surface of implied firm’s asset volatility," Journal of Banking & Finance, Elsevier, vol. 112(C).

    More about this item

    Keywords

    term structure of option prices; market efficiency;

    JEL classification:

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

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