Corpus ID: 212675289

Numerical smoothing and hierarchical approximations for efficient option pricing and density estimation

@article{Bayer2020NumericalSA,
  title={Numerical smoothing and hierarchical approximations for efficient option pricing and density estimation},
  author={Christian Bayer and Chiheb Ben Hammouda and R. Tempone},
  journal={arXiv: Computational Finance},
  year={2020}
}
  • Christian Bayer, Chiheb Ben Hammouda, R. Tempone
  • Published 2020
  • Mathematics, Economics
  • arXiv: Computational Finance
  • When approximating the expectation of a functional of a certain stochastic process, the efficiency and performance of deterministic quadrature methods, and hierarchical variance reduction methods such as multilevel Monte Carlo (MLMC), is highly deteriorated in different ways by the low regularity of the integrand with respect to the input parameters. To overcome this issue, a smoothing procedure is needed to uncover the available regularity and improve the performance of the aforementioned… CONTINUE READING
    3 Citations

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