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Can we forecast the implied volatility surface dynamics of equity options? Predictability and economic value tests

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  • Bernales, Alejandro
  • Guidolin, Massimo

Abstract

We examine whether the dynamics of the implied volatility surface of individual equity options contains exploitable predictability patterns. Predictability in implied volatilities is expected due to the learning behavior of agents in option markets. In particular, we explore the possibility that the dynamics of the implied volatility surface of individual stocks may be associated with movements in the volatility surface of S&P 500 index options. We present evidence of strong predictable features in the cross-section of equity options and of dynamic linkages between the volatility surfaces of equity and S&P 500 index options. Moreover, time-variation in stock option volatility surfaces is best predicted by incorporating information from the dynamics in the surface of S&P 500 options. We analyze the economic value of such dynamic patterns using strategies that trade straddle and delta-hedged portfolios, and find that before transaction costs such strategies produce abnormal risk-adjusted returns.

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  • Bernales, Alejandro & Guidolin, Massimo, 2014. "Can we forecast the implied volatility surface dynamics of equity options? Predictability and economic value tests," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 326-342.
    • Handle: RePEc:eee:jbfina:v:46:y:2014:i:c:p:326-342
    DOI: 10.1016/j.jbankfin.2014.06.002
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    Cited by:

    1. Kearney, Fearghal & Shang, Han Lin & Sheenan, Lisa, 2019. "Implied volatility surface predictability: The case of commodity markets," Journal of Banking & Finance, Elsevier, vol. 108(C).
    2. Gradojevic Nikola, 2016. "Multi-criteria classification for pricing European options," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(2), pages 123-139, April.
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    6. Tanha, Hassan & Dempsey, Michael, 2016. "The evolving dynamics of the Australian SPI 200 implied volatility surface," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 43(C), pages 44-57.
    7. Murad Samsudin, Najmi Ismail & Mohamad, Azhar & Sifat, Imtiaz Mohammad, 2021. "Implied volatility of structured warrants: Emerging market evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 464-479.
    8. Michel van der Wel & Sait R. Ozturk & Dick van Dijk, 2015. "Dynamic Factor Models for the Volatility Surface," CREATES Research Papers 2015-13, Department of Economics and Business Economics, Aarhus University.
    9. Han Lin Shang & Yang Yang & Fearghal Kearney, 2019. "Intraday forecasts of a volatility index: functional time series methods with dynamic updating," Annals of Operations Research, Springer, vol. 282(1), pages 331-354, November.
    10. Bernales, Alejandro & Cañón, Carlos & Verousis, Thanos, 2018. "Bid–ask spread and liquidity searching behaviour of informed investors in option markets," Finance Research Letters, Elsevier, vol. 25(C), pages 96-102.
    11. Wenyong Zhang & Lingfei Li & Gongqiu Zhang, 2021. "A Two-Step Framework for Arbitrage-Free Prediction of the Implied Volatility Surface," Papers 2106.07177, arXiv.org, revised Jan 2022.
    12. Shengli Chen & Zili Zhang, 2019. "Forecasting Implied Volatility Smile Surface via Deep Learning and Attention Mechanism," Papers 1912.11059, arXiv.org.
    13. 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).
    14. Guidolin, Massimo & Wang, Kai, 2023. "The empirical performance of option implied volatility surface-driven optimal portfolios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 618(C).
    15. Bernales, Alejandro & Guidolin, Massimo, 2015. "Learning to smile: Can rational learning explain predictable dynamics in the implied volatility surface?," Journal of Financial Markets, Elsevier, vol. 26(C), pages 1-37.
    16. Shi, Yunkun & Stasinakis, Charalampos & Xu, Yaofei & Yan, Cheng & Zhang, Xuan, 2022. "Stock price default boundary: A Black-Cox model approach," International Review of Financial Analysis, Elsevier, vol. 83(C).
    17. Quaye, Enoch & Tunaru, Radu, 2022. "The stock implied volatility and the implied dividend volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    18. Alejandro Bernales & Thanos Verousis & Nikolaos Voukelatos & Mengyu Zhang, 2020. "What do we know about individual equity options?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(1), pages 67-91, January.
    19. Chen, Ying & Grith, Maria & Lai, Hannah L. H., 2023. "Neural Tangent Kernel in Implied Volatility Forecasting: A Nonlinear Functional Autoregression Approach," MPRA Paper 119022, University Library of Munich, Germany.

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    More about this item

    Keywords

    Equity options; Index options; Implied volatility surface; Predictability; Trading strategies;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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