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A neural network approach to understanding implied volatility movements

Author

Listed:
  • Jay Cao
  • Jacky Chen
  • John Hull

Abstract

The expected response of an index volatility surface to index movements is quite different in high and low volatility environments

Suggested Citation

  • Jay Cao & Jacky Chen & John Hull, 2020. "A neural network approach to understanding implied volatility movements," Quantitative Finance, Taylor & Francis Journals, vol. 20(9), pages 1405-1413, September.
    • Handle: RePEc:taf:quantf:v:20:y:2020:i:9:p:1405-1413
    DOI: 10.1080/14697688.2020.1750679
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    Citations

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    Cited by:

    1. 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.
    2. Jie Chen & Lingfei Li, 2021. "Data-driven Hedging of Stock Index Options via Deep Learning," Papers 2111.03477, arXiv.org.
    3. 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.
    4. Xia, Kun & Yang, Xuewei & Zhu, Peng, 2023. "Delta hedging and volatility-price elasticity: A two-step approach," Journal of Banking & Finance, Elsevier, vol. 153(C).
    5. Taicir Mezghani & Mouna Boujelbène Abbes, 2023. "Forecast the Role of GCC Financial Stress on Oil Market and GCC Financial Markets Using Convolutional Neural Networks," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 30(3), pages 505-530, September.
    6. Gregory Benton & Wesley J. Maddox & Andrew Gordon Wilson, 2022. "Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes," Papers 2207.06544, arXiv.org.
    7. 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).
    8. Yichi Zhang & Mihai Cucuringu & Alexander Y. Shestopaloff & Stefan Zohren, 2023. "Dynamic Time Warping for Lead-Lag Relationships in Lagged Multi-Factor Models," Papers 2309.08800, arXiv.org.
    9. Zheng Gong & Wojciech Frys & Renzo Tiranti & Carmine Ventre & John O'Hara & Yingbo Bai, 2022. "A new encoding of implied volatility surfaces for their synthetic generation," Papers 2211.12892, arXiv.org, revised Jun 2023.
    10. Chunhui Qiao & Xiangwei Wan, 2024. "Enhancing Black-Scholes Delta Hedging via Deep Learning," Papers 2407.19367, arXiv.org, revised Aug 2024.
    11. Yichi Zhang & Mihai Cucuringu & Alexander Y. Shestopaloff & Stefan Zohren, 2023. "Robust Detection of Lead-Lag Relationships in Lagged Multi-Factor Models," Papers 2305.06704, arXiv.org, revised Sep 2023.
    12. 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.

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