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The Application of Symbolic Regression on Identifying Implied Volatility Surface

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  • Jiayi Luo

    (Department of Statistics, Iowa State University, Ames, IA 50011, USA)

  • Cindy Long Yu

    (Department of Statistics, Iowa State University, Ames, IA 50011, USA)

Abstract

One important parameter in the Black–Scholes option pricing model is the implied volatility. Implied volatility surface (IVS) is an important concept in finance that describes the variation of implied volatility across option strike price and time to maturity. Over the last few decades, economists and financialists have long tried to exploit the predictability in the IVS using various parametric models, which require deep understanding of financial practices in the area. In this paper, we explore how a data-driven machine learning method, symbolic regression, performs in identifying the implied volatility surface even without deep financial knowledge. Two different approaches of symbolic regression are explored through a simulation study and an empirical study using a large panel of option data in the United States options market.

Suggested Citation

  • Jiayi Luo & Cindy Long Yu, 2023. "The Application of Symbolic Regression on Identifying Implied Volatility Surface," Mathematics, MDPI, vol. 11(9), pages 1-28, April.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:9:p:2108-:d:1136037
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    References listed on IDEAS

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    1. Canina, Linda & Figlewski, Stephen, 1993. "The Informational Content of Implied Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 659-681.
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    4. Heston, Steven L & Nandi, Saikat, 2000. "A Closed-Form GARCH Option Valuation Model," The Review of Financial Studies, Society for Financial Studies, vol. 13(3), pages 585-625.
    5. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    6. repec:bla:jfinan:v:53:y:1998:i:6:p:2059-2106 is not listed on IDEAS
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    Cited by:

    1. Zihao Chen & Yuyang Li & Cindy Long Yu, 2024. "Modeling Implied Volatility Surface Using B-Splines with Time-Dependent Coefficients Predicted by Tree-Based Machine Learning Methods," Mathematics, MDPI, vol. 12(7), pages 1-30, April.

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