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On the Approximation of the SABR Model: A Probabilistic Approach

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  • Joanne E. Kennedy
  • Subhankar Mitra
  • Duy Pham

Abstract

In this article, we derive a probabilistic approximation for three different versions of the SABR model: Normal, Log-Normal and a displaced diffusion version for the general case. Specifically, we focus on capturing the terminal distribution of the underlying process (conditional on the terminal volatility) to arrive at the implied volatilities of the corresponding European options for all strikes and maturities. Our resulting method allows us to work with a variety of parameters that cover the long-dated options and highly stress market condition. This is a different feature from other current approaches that rely on the assumption of very small total volatility and usually fail for longer than 10 years maturity or large volatility of volatility (Volvol).

Suggested Citation

  • 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.
    • Handle: RePEc:taf:apmtfi:v:19:y:2012:i:6:p:553-586
    DOI: 10.1080/1350486X.2011.646523
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    Cited by:

    1. 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.
    2. Jaehyuk Choi & Lilian Hu & Yue Kuen Kwok, 2024. "Efficient simulation of the SABR model," Papers 2408.01898, arXiv.org.

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