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Stationary Heston model: Calibration and Pricing of exotics using Product Recursive Quantization

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  • Vincent Lemaire
  • Thibaut Montes
  • Gilles Pag`es

Abstract

A major drawback of the Standard Heston model is that its implied volatility surface does not produce a steep enough smile when looking at short maturities. For that reason, we introduce the Stationary Heston model where we replace the deterministic initial condition of the volatility by its invariant measure and show, based on calibrated parameters, that this model produce a steeper smile for short maturities than the Standard Heston model. We also present numerical solution based on Product Recursive Quantization for the evaluation of exotic options (Bermudan and Barrier options).

Suggested Citation

  • Vincent Lemaire & Thibaut Montes & Gilles Pag`es, 2020. "Stationary Heston model: Calibration and Pricing of exotics using Product Recursive Quantization," Papers 2001.03101, arXiv.org, revised Jul 2020.
  • Handle: RePEc:arx:papers:2001.03101
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    References listed on IDEAS

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    1. Gilles Pag`es & Fabien Panloup, 2007. "Approximation of the distribution of a stationary Markov process with application to option pricing," Papers 0704.0335, arXiv.org, revised Sep 2009.
    2. John C. Cox & Jonathan E. Ingersoll Jr. & Stephen A. Ross, 2005. "A Theory Of The Term Structure Of Interest Rates," World Scientific Book Chapters, in: Sudipto Bhattacharya & George M Constantinides (ed.), Theory Of Valuation, chapter 5, pages 129-164, World Scientific Publishing Co. Pte. Ltd..
    3. T. A. McWalter & R. Rudd & J. Kienitz & E. Platen, 2018. "Recursive marginal quantization of higher-order schemes," Quantitative Finance, Taylor & Francis Journals, vol. 18(4), pages 693-706, April.
    4. Gilles Pagès & Abass Sagna, 2015. "Recursive Marginal Quantization of the Euler Scheme of a Diffusion Process," Applied Mathematical Finance, Taylor & Francis Journals, vol. 22(5), pages 463-498, November.
    5. 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.
    6. Ralph Rudd & Thomas A. McWalter & Joerg Kienitz & Eckhard Platen, 2017. "Fast Quantization of Stochastic Volatility Models," Papers 1704.06388, arXiv.org.
    7. Abass Sagna, 2010. "Pricing of barrier options by marginal functional quantization," Papers 1012.1037, arXiv.org.
    8. Giorgia Callegaro & Lucio Fiorin & Martino Grasselli, 2017. "Pricing via recursive quantization in stochastic volatility models," Quantitative Finance, Taylor & Francis Journals, vol. 17(6), pages 855-872, June.
    9. Vlad Bally & Gilles Pagès & Jacques Printems, 2005. "A Quantization Tree Method For Pricing And Hedging Multidimensional American Options," Mathematical Finance, Wiley Blackwell, vol. 15(1), pages 119-168, January.
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    Cited by:

    1. Ben Boukai, 2021. "On the RND under Heston's stochastic volatility model," Papers 2101.03626, arXiv.org.
    2. Daeyung Gim & Hyungbin Park, 2021. "A deep learning algorithm for optimal investment strategies," Papers 2101.12387, arXiv.org.
    3. Ben Boukai, 2021. "The Generalized Gamma distribution as a useful RND under Heston's stochastic volatility model," Papers 2108.07937, arXiv.org, revised Aug 2021.

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