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Target volatility option pricing in lognormal fractional SABR model

Author

Listed:
  • Elisa Alos
  • Rupak Chatterjee
  • Sebastian Tudor
  • Tai-Ho Wang

Abstract

We examine in this article the pricing of target volatility options in the lognormal fractional SABR model. A decomposition formula by Ito's calculus yields a theoretical replicating strategy for the target volatility option, assuming the accessibilities of all variance swaps and swaptions. The same formula also suggests an approximation formula for the price of target volatility option in small time by the technique of freezing the coefficient. Alternatively, we also derive closed formed expressions for a small volatility of volatility expansion of the price of target volatility option. Numerical experiments show accuracy of the approximations in a reasonably wide range of parameters.

Suggested Citation

  • Elisa Alos & Rupak Chatterjee & Sebastian Tudor & Tai-Ho Wang, 2018. "Target volatility option pricing in lognormal fractional SABR model," Papers 1801.08215, arXiv.org.
  • Handle: RePEc:arx:papers:1801.08215
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    References listed on IDEAS

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    1. Jim Gatheral & Thibault Jaisson & Mathieu Rosenbaum, 2014. "Volatility is rough," Papers 1410.3394, arXiv.org.
    2. Giuseppe Di Graziano & Lorenzo Torricelli, 2012. "Target Volatility Option Pricing," World Scientific Book Chapters, in: Matheus R Grasselli & Lane P Hughston (ed.), Finance at Fields, chapter 8, pages 207-223, World Scientific Publishing Co. Pte. Ltd..
    3. Martino Grasselli & Jacinto Marabel Romo, 2016. "Stochastic Skew and Target Volatility Options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(2), pages 174-193, February.
    4. Elisa Alòs & Jorge León & Josep Vives, 2007. "On the short-time behavior of the implied volatility for jump-diffusion models with stochastic volatility," Finance and Stochastics, Springer, vol. 11(4), pages 571-589, October.
    5. Giuseppe Di Graziano & Lorenzo Torricelli, 2012. "Target Volatility Option Pricing," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 15(01), pages 1-17.
    6. Jiro Akahori & Xiaoming Song & Tai-Ho Wang, 2017. "Probability density of lognormal fractional SABR model," Papers 1702.08081, arXiv.org, revised Jan 2019.
    7. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2015. "Hybrid scheme for Brownian semistationary processes," Papers 1507.03004, arXiv.org, revised May 2017.
    8. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2017. "Hybrid scheme for Brownian semistationary processes," Finance and Stochastics, Springer, vol. 21(4), pages 931-965, October.
    9. Ryan McCrickerd & Mikko S. Pakkanen, 2017. "Turbocharging Monte Carlo pricing for the rough Bergomi model," Papers 1708.02563, arXiv.org, revised Mar 2018.
    10. Lorenzo Torricelli, 2013. "Pricing Joint Claims On An Asset And Its Realized Variance In Stochastic Volatility Models," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 16(01), pages 1-18.
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