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Factors explaining movements in the implied volatility surface

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  • Scott Mixon

Abstract

This article explores the relationship of changes in the S&P 500 index implied volatility surface to economic state variables. Observable variables can explain some of the variation in implied volatility, with the majority of explanatory power from index returns. Although the contemporaneous return is most important for explaining changes in short dated volatility, the path of the index is important for explaining changes in long dated volatility. Other variables also display statistically significant relations to volatility changes. Shocks to the Nikkei 225, short‐term interest rates, and the corporate/government bond yield spread are correlated with small, systematic changes in implied volatility. The results suggest a multifactor model for market volatility, with factors other than index returns adding negligible explanatory ability. © 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:915–937, 2002

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  • Scott Mixon, 2002. "Factors explaining movements in the implied volatility surface," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 22(10), pages 915-937, October.
    • Handle: RePEc:wly:jfutmk:v:22:y:2002:i:10:p:915-937
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    Cited by:

    1. Adjemian, Michael K. & Bruno, Valentina & Robe, Michel A. & Wallen, Jonathan, 2017. "What Drives Volatility Expectations in Grain and Oilseed Markets?," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258452, Agricultural and Applied Economics Association.
    2. Qian Han & Jufang Liang & Boqiang Wu, 2016. "Cross Economic Determinants of Implied Volatility Smile Dynamics: Three Major European Currency Options," European Financial Management, European Financial Management Association, vol. 22(5), pages 817-852, November.
    3. Scott Mixon & Esen Onur, 2019. "Derivatives pricing when supply and demand matter: Evidence from the term structure of VIX futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(9), pages 1035-1055, September.
    4. 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.
    5. Gang Li & Chu Zhang, 2010. "On the Number of State Variables in Options Pricing," Management Science, INFORMS, vol. 56(11), pages 2058-2075, November.
    6. Marcel T. P. Van Dijk & Cornelis S. L. De Graaf & Cornelis W. Oosterlee, 2018. "Between ℙ and ℚ: The ℙ ℚ Measure for Pricing in Asset Liability Management," JRFM, MDPI, vol. 11(4), pages 1-23, October.
    7. Mixon, Scott, 2007. "The implied volatility term structure of stock index options," Journal of Empirical Finance, Elsevier, vol. 14(3), pages 333-354, June.
    8. 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.
    9. Ulze, Markus & Stadler, Johannes & Rathgeber, Andreas W., 2021. "No country for old distributions? On the comparison of implied option parameters between the Brownian motion and variance gamma process," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 163-184.
    10. Soohan Kim & Seok-Bae Yun & Hyeong-Ohk Bae & Muhyun Lee & Youngjoon Hong, 2022. "Physics-Informed Convolutional Transformer for Predicting Volatility Surface," Papers 2209.10771, arXiv.org, revised Nov 2023.

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