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Volatility of Volatility and Leverage Effect from Options

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  • Carsten H. Chong
  • Viktor Todorov

Abstract

We propose model-free (nonparametric) estimators of the volatility of volatility and leverage effect using high-frequency observations of short-dated options. At each point in time, we integrate available options into estimates of the conditional characteristic function of the price increment until the options' expiration and we use these estimates to recover spot volatility. Our volatility of volatility estimator is then formed from the sample variance and first-order autocovariance of the spot volatility increments, with the latter correcting for the bias in the former due to option observation errors. The leverage effect estimator is the sample covariance between price increments and the estimated volatility increments. The rate of convergence of the estimators depends on the diffusive innovations in the latent volatility process as well as on the observation error in the options with strikes in the vicinity of the current spot price. Feasible inference is developed in a way that does not require prior knowledge of the source of estimation error that is asymptotically dominating.

Suggested Citation

  • Carsten H. Chong & Viktor Todorov, 2023. "Volatility of Volatility and Leverage Effect from Options," Papers 2305.04137, arXiv.org, revised Jan 2024.
  • Handle: RePEc:arx:papers:2305.04137
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    References listed on IDEAS

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    1. Viktor Todorov & Yang Zhang, 2022. "Information gains from using short‐dated options for measuring and forecasting volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 368-391, March.
    2. Ilze Kalnina & Dacheng Xiu, 2017. "Nonparametric Estimation of the Leverage Effect: A Trade-Off Between Robustness and Efficiency," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 384-396, January.
    3. Huang, Darien & Schlag, Christian & Shaliastovich, Ivan & Thimme, Julian, 2019. "Volatility-of-Volatility Risk," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(6), pages 2423-2452, December.
    4. Simona Sanfelici & Imma Valentina Curato & Maria Elvira Mancino, 2015. "High-frequency volatility of volatility estimation free from spot volatility estimates," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1331-1345, August.
    5. Chernov, Mikhail & Ronald Gallant, A. & Ghysels, Eric & Tauchen, George, 2003. "Alternative models for stock price dynamics," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 225-257.
    6. Carsten H. Chong & Viktor Todorov, 2023. "Asymptotic Expansions for High-Frequency Option Data," Papers 2304.12450, arXiv.org.
    7. Simon Clinet & Yoann Potiron, 2021. "Estimation for high-frequency data under parametric market microstructure noise," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(4), pages 649-669, August.
    8. Agarwal, Vikas & Arisoy, Y. Eser & Naik, Narayan Y., 2017. "Volatility of aggregate volatility and hedge fund returns," Journal of Financial Economics, Elsevier, vol. 125(3), pages 491-510.
    9. Baltussen, Guido & van Bekkum, Sjoerd & van der Grient, Bart, 2018. "Unknown Unknowns: Uncertainty About Risk and Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(4), pages 1615-1651, August.
    10. Fei Sun & Yijun Hu, 2018. "Quasiconvex risk measures with markets volatility," Papers 1806.08701, arXiv.org, revised Jun 2019.
    11. Fei Sun & Yijun Hu, 2018. "Systemic risk measures with markets volatility," Papers 1812.06185, arXiv.org, revised Jun 2019.
    12. Michael Donadelli & Marcus Jüppner & Antonio Paradiso & Christian Schlag, 2019. "Temperature Volatility Risk," Working Papers 2019:05, Department of Economics, University of Venice "Ca' Foscari".
    13. P. Carr & D. Madan, 2001. "Optimal positioning in derivative securities," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 19-37.
    14. Giacomo Toscano & Giulia Livieri & Maria Elvira Mancino & Stefano Marmi, 2021. "Volatility of volatility estimation: central limit theorems for the Fourier transform estimator and empirical study of the daily time series stylized facts," Papers 2112.14529, arXiv.org, revised Sep 2022.
    15. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
    16. Junjie Hu & Wolfgang Karl Hardle & Weiyu Kuo, 2019. "Risk of Bitcoin Market: Volatility, Jumps, and Forecasts," Papers 1912.05228, arXiv.org, revised Dec 2021.
    17. Todorov, Viktor, 2021. "Higher-order small time asymptotic expansion of Itô semimartingale characteristic function with application to estimation of leverage from options," Stochastic Processes and their Applications, Elsevier, vol. 142(C), pages 671-705.
    18. Yacine Aït-Sahalia & Jianqing Fan & Roger J. A. Laeven & Christina Dan Wang & Xiye Yang, 2017. "Estimation of the Continuous and Discontinuous Leverage Effects," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1744-1758, October.
    19. Te-Feng Chen & Tarun Chordia & San-Lin Chung & Ji-Chai Lin, 2022. "Volatility-of-Volatility Risk in Asset Pricing [Stock returns and volatility: Pricing the short-run and long-run components of market risk]," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 12(1), pages 289-335.
    20. Li, Yingying & Liu, Guangying & Zhang, Zhiyuan, 2022. "Volatility of volatility: Estimation and tests based on noisy high frequency data with jumps," Journal of Econometrics, Elsevier, vol. 229(2), pages 422-451.
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    Cited by:

    1. Alessio Brini & Giacomo Toscano, 2024. "SpotV2Net: Multivariate Intraday Spot Volatility Forecasting via Vol-of-Vol-Informed Graph Attention Networks," Papers 2401.06249, arXiv.org, revised Aug 2024.
    2. Carsten H. Chong & Viktor Todorov, 2023. "Asymptotic Expansions for High-Frequency Option Data," Papers 2304.12450, arXiv.org.

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