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Efficient simulation of the SABR model

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  • Jaehyuk Choi
  • Lilian Hu
  • Yue Kuen Kwok

Abstract

We propose an efficient and reliable simulation scheme for the stochastic-alpha-beta-rho (SABR) model. The two challenges of the SABR simulation lie in sampling (i) the integrated variance conditional on terminal volatility and (ii) the terminal price conditional on terminal volatility and integrated variance. For the first sampling procedure, we analytically derive the first four moments of the conditional average variance, and sample it from the moment-matched shifted lognormal approximation. For the second sampling procedure, we approximate the conditional terminal price as a constant-elasticity-of-variance (CEV) distribution. Our CEV approximation preserves the martingale condition and precludes arbitrage, which is a key advantage over Islah's approximation used in most SABR simulation schemes in the literature. Then, we adopt the exact sampling method of the CEV distribution based on the shifted-Poisson-mixture Gamma random variable. Our enhanced procedures avoid the tedious Laplace inversion algorithm for sampling integrated variance and non-efficient inverse transform sampling of the forward price in some of the earlier simulation schemes. Numerical results demonstrate our simulation scheme to be highly efficient, accurate, and reliable.

Suggested Citation

  • Jaehyuk Choi & Lilian Hu & Yue Kuen Kwok, 2024. "Efficient simulation of the SABR model," Papers 2408.01898, arXiv.org.
    • Handle: RePEc:arx:papers:2408.01898
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    References listed on IDEAS

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    1. Choi, Jaehyuk & Wu, Lixin, 2021. "The equivalent constant-elasticity-of-variance (CEV) volatility of the stochastic-alpha-beta-rho (SABR) model," Journal of Economic Dynamics and Control, Elsevier, vol. 128(C).
    2. Fang, Fang & Oosterlee, Kees, 2008. "A Novel Pricing Method For European Options Based On Fourier-Cosine Series Expansions," MPRA Paper 9319, University Library of Munich, Germany.
    3. repec:bla:jfinan:v:44:y:1989:i:1:p:211-19 is not listed on IDEAS
    4. Archil Gulisashvili & Blanka Horvath & Antoine Jacquier, 2018. "Mass at zero in the uncorrelated SABR model and implied volatility asymptotics," Quantitative Finance, Taylor & Francis Journals, vol. 18(10), pages 1753-1765, October.
    5. Bin Chen & Cornelis W. Oosterlee & Hans Van Der Weide, 2012. "A Low-Bias Simulation Scheme For The Sabr Stochastic Volatility Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 15(02), pages 1-37.
    6. Jaehyuk Choi & Chenru Liu & Byoung Ki Seo, 2019. "Hyperbolic normal stochastic volatility model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(2), pages 186-204, February.
    7. Jaehyuk Choi & Lixin Wu, 2021. "A note on the option price and ‘Mass at zero in the uncorrelated SABR model and implied volatility asymptotics’," Quantitative Finance, Taylor & Francis Journals, vol. 21(7), pages 1083-1086, July.
    8. L. A. Grzelak & J. A. S. Witteveen & M. Suárez-Taboada & C. W. Oosterlee, 2019. "The stochastic collocation Monte Carlo sampler: highly efficient sampling from ‘expensive’ distributions," Quantitative Finance, Taylor & Francis Journals, vol. 19(2), pages 339-356, February.
    9. Cui, Zhenyu & Kirkby, J. Lars & Nguyen, Duy, 2021. "Efficient simulation of generalized SABR and stochastic local volatility models based on Markov chain approximations," European Journal of Operational Research, Elsevier, vol. 290(3), pages 1046-1062.
    10. Matthew Lorig & Stefano Pagliarani & Andrea Pascucci, 2017. "Explicit Implied Volatilities For Multifactor Local-Stochastic Volatility Models," Mathematical Finance, Wiley Blackwell, vol. 27(3), pages 926-960, July.
    11. Joanne E. Kennedy & Subhankar Mitra & Duy Pham, 2012. "On the Approximation of the SABR Model: A Probabilistic Approach," Applied Mathematical Finance, Taylor & Francis Journals, vol. 19(6), pages 553-586, December.
    12. Ning Cai & Yingda Song & Nan Chen, 2017. "Exact Simulation of the SABR Model," Operations Research, INFORMS, vol. 65(4), pages 931-951, August.
    13. Emanuel Derman & Iraj Kani, 1998. "Stochastic Implied Trees: Arbitrage Pricing with Stochastic Term and Strike Structure of Volatility," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 1(01), pages 61-110.
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