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A novel Monte Carlo approach to hybrid local volatility models

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  • Anthonie W. van der Stoep
  • Lech A. Grzelak
  • Cornelis W. Oosterlee

Abstract

We present in a Monte Carlo simulation framework, a novel approach for the evaluation of hybrid local volatility [Risk, 1994, 7, 18–20], [Int. J. Theor. Appl. Finance, 1998, 1, 61–110] models. In particular, we consider the stochastic local volatility model—see e.g. Lipton et al. [Quant. Finance, 2014, 14, 1899–1922], Piterbarg [Risk, 2007, April, 84–89], Tataru and Fisher [Quantitative Development Group, Bloomberg Version 1, 2010], Lipton [Risk, 2002, 15, 61–66]—and the local volatility model incorporating stochastic interest rates—see e.g. Atlan [ArXiV preprint math/0604316, 2006], Piterbarg [Risk, 2006, 19, 66–71], Deelstra and Rayée [Appl. Math. Finance, 2012, 1–23], Ren et al. [Risk, 2007, 20, 138–143]. For both model classes a particular (conditional) expectation needs to be evaluated which cannot be extracted from the market and is expensive to compute. We establish accurate and ‘cheap to evaluate’ approximations for the expectations by means of the stochastic collocation method [SIAM J. Numer. Anal., 2007, 45, 1005–1034], [SIAM J. Sci. Comput., 2005, 27, 1118–1139], [Math. Models Methods Appl. Sci., 2012, 22, 1–33], [SIAM J. Numer. Anal., 2008, 46, 2309–2345], [J. Biomech. Eng., 2011, 133, 031001], which was recently applied in the financial context [Available at SSRN 2529691, 2014], [J. Comput. Finance, 2016, 20, 1–19], combined with standard regression techniques. Monte Carlo pricing experiments confirm that our method is highly accurate and fast.

Suggested Citation

  • Anthonie W. van der Stoep & Lech A. Grzelak & Cornelis W. Oosterlee, 2017. "A novel Monte Carlo approach to hybrid local volatility models," Quantitative Finance, Taylor & Francis Journals, vol. 17(9), pages 1347-1366, September.
  • Handle: RePEc:taf:quantf:v:17:y:2017:i:9:p:1347-1366
    DOI: 10.1080/14697688.2017.1280613
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    Cited by:

    1. Yang, Ben-Zhang & Yue, Jia & Wang, Ming-Hui & Huang, Nan-Jing, 2019. "Volatility swaps valuation under stochastic volatility with jumps and stochastic intensity," Applied Mathematics and Computation, Elsevier, vol. 355(C), pages 73-84.
    2. T. van der Zwaard & L. A. Grzelak & C. W. Oosterlee, 2022. "Efficient Wrong-Way Risk Modelling for Funding Valuation Adjustments," Papers 2209.12222, arXiv.org, revised Jun 2024.

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