SINH-acceleration: efficient evaluation of probability distributions, option pricing, and Monte-Carlo simulations
Svetlana Boyarchenko, Sergei Levendorski\u{i}

TL;DR
This paper introduces a fast, accurate Fourier-based method using variable transformations and trapezoid rule for evaluating probability distributions and option prices across various financial models, enhancing calibration and simulation efficiency.
Contribution
It proposes a novel change of variables and numerical scheme for efficient integral evaluation in characteristic function-based models, applicable to multiple financial models including Lévy and Heston.
Findings
Achieves fast and accurate computation of distributions and option prices.
Enables efficient calibration and Monte Carlo simulations.
Provides a method for precise tail quantile calculations.
Abstract
Characteristic functions of several popular classes of distributions and processes admit analytic continuation into unions of strips and open coni around . 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 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…
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