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Joint Modelling and Calibration of SPX and VIX by Optimal Transport

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  • Ivan Guo
  • Gregoire Loeper
  • Jan Obloj
  • Shiyi Wang

Abstract

This paper addresses the joint calibration problem of SPX options and VIX options or futures. We show that the problem can be formulated as a semimartingale optimal transport problem under a finite number of discrete constraints, in the spirit of [arXiv:1906.06478]. We introduce a PDE formulation along with its dual counterpart. The solution, a calibrated diffusion process, can be represented via the solutions of Hamilton-Jacobi-Bellman equations arising from the dual formulation. The method is tested on both simulated data and market data. Numerical examples show that the model can be accurately calibrated to SPX options, VIX options and VIX futures simultaneously.

Suggested Citation

  • Ivan Guo & Gregoire Loeper & Jan Obloj & Shiyi Wang, 2020. "Joint Modelling and Calibration of SPX and VIX by Optimal Transport," Papers 2004.02198, arXiv.org, revised Sep 2021.
  • Handle: RePEc:arx:papers:2004.02198
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    References listed on IDEAS

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    1. Jan Baldeaux & Alexander Badran, 2014. "Consistent Modelling of VIX and Equity Derivatives Using a 3/2 plus Jumps Model," Applied Mathematical Finance, Taylor & Francis Journals, vol. 21(4), pages 299-312, September.
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    8. Ivan Guo & Gregoire Loeper, 2018. "Pricing Bounds for Volatility Derivatives via Duality and Least Squares Monte Carlo," Journal of Optimization Theory and Applications, Springer, vol. 179(2), pages 598-617, November.
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    11. Ivan Guo & Gregoire Loeper & Shiyi Wang, 2019. "Calibration of Local-Stochastic Volatility Models by Optimal Transport," Papers 1906.06478, arXiv.org, revised Jul 2021.
    12. J.-P. Fouque & Y. F. Saporito, 2018. "Heston stochastic vol-of-vol model for joint calibration of VIX and S&P 500 options," Quantitative Finance, Taylor & Francis Journals, vol. 18(6), pages 1003-1016, June.
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