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SINH-acceleration: efficient evaluation of probability distributions, option pricing, and Monte-Carlo simulations

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  • Svetlana Boyarchenko
  • Sergei Levendorskiu{i}

Abstract

Characteristic functions of several popular classes of distributions and processes admit analytic continuation into unions of strips and open coni around $\mathbb{R}\subset \mathbb{C}$. The Fourier transform techniques reduces calculation of probability distributions and option prices to evaluation of integrals whose integrands are analytic in domains enjoying these properties. In the paper, we suggest to use changes of variables of the form $\xi=\sqrt{-1}\omega_1+b\sinh (\sqrt{-1}\omega+y)$ and the simplified trapezoid rule to evaluate the integrals accurately and fast. We formulate the general scheme, and apply the scheme for calculation probability distributions and pricing European options in L\'evy models, the Heston model, the CIR model, and a L\'evy model with the CIR-subordinator. We outline applications to fast and accurate calibration procedures and Monte Carlo simulations in L\'evy models, regime switching L\'evy models that can account for stochastic drift, volatility and skewness, and the Heston model. For calculation of quantiles in the tails using the Newton or bisection method, it suffices to precalculate several hundred of values of the characteristic exponent at points of an appropriate grid ({\em conformal principal components}) and use these values in formulas for cpdf and pdf.

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  • Svetlana Boyarchenko & Sergei Levendorskiu{i}, 2018. "SINH-acceleration: efficient evaluation of probability distributions, option pricing, and Monte-Carlo simulations," Papers 1808.05295, arXiv.org.
  • Handle: RePEc:arx:papers:1808.05295
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    Cited by:

    1. Svetlana Boyarchenko & Sergei Levendorskiä¬ & J. Lars Kyrkby & Zhenyu Cui, 2021. "Sinh-Acceleration For B-Spline Projection With Option Pricing Applications," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 24(08), pages 1-50, December.
    2. Svetlana Boyarchenko & Sergei Levendorskiĭ, 2020. "Static and semistatic hedging as contrarian or conformist bets," Mathematical Finance, Wiley Blackwell, vol. 30(3), pages 921-960, July.
    3. Svetlana Boyarchenko & Sergei Levendorskiu{i}, 2022. "Efficient evaluation of expectations of functions of a stable L\'evy process and its extremum," Papers 2209.12349, arXiv.org.
    4. Svetlana Boyarchenko & Sergei Levendorskiu{i}, 2022. "Efficient inverse $Z$-transform and pricing barrier and lookback options with discrete monitoring," Papers 2207.02858, arXiv.org, revised Jul 2022.
    5. Svetlana Boyarchenko & Sergei Levendorskiu{i}, 2022. "L\'evy models amenable to efficient calculations," Papers 2207.02359, arXiv.org.
    6. Svetlana Boyarchenko & Sergei Levendorskiu{i}, 2019. "Gauge transformations in the dual space, and pricing and estimation in the long run in affine jump-diffusion models," Papers 1912.06948, arXiv.org, revised Dec 2019.
    7. Sergei Levendorskiĭ, 2022. "Operators and Boundary Problems in Finance, Economics and Insurance: Peculiarities, Efficient Methods and Outstanding Problems," Mathematics, MDPI, vol. 10(7), pages 1-36, March.
    8. Michele Azzone & Roberto Baviera, 2023. "A fast Monte Carlo scheme for additive processes and option pricing," Computational Management Science, Springer, vol. 20(1), pages 1-34, December.

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