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Approximate formulas for expectations of functionals of solutions to stochastic differential equations

Author

Listed:
  • Egorov A.

    (Belarus Academy of Sciences, Surganova St. 11, Minsk 220072, Belarus. E-mail: egorov@im.bas-net.by)

  • Sabelfeld K.

    (Institute of Computational Mathematics and Mathematical Geophysics, Academy of Sciences, Siberian Branch, Lavrentjeva 6, 630090 Novosibirsk, Russia. E-mail: karl@osmf.sscc.ru)

Abstract

Approximate formulas for evaluation of mathematical expectations of nonlinear functionals of solutions to Ito's stochastic differential equation are constructed. The general approach is based on quadrature formulas which are exact for functional polynomials.

Suggested Citation

  • Egorov A. & Sabelfeld K., 2010. "Approximate formulas for expectations of functionals of solutions to stochastic differential equations," Monte Carlo Methods and Applications, De Gruyter, vol. 16(2), pages 95-127, January.
    • Handle: RePEc:bpj:mcmeap:v:16:y:2010:i:2:p:95-127:n:1
    DOI: 10.1515/mcma.2010.003
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    References listed on IDEAS

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    1. Egorov A. D. & Zherelo A. V., 2004. "Approximations of functional integrals with respect to measures generated by solutions of stochastic differential equations," Monte Carlo Methods and Applications, De Gruyter, vol. 10(3-4), pages 257-264, December.
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    Cited by:

    1. Egorov Alexander & Malyutin Victor, 2017. "A method for the calculation of characteristics for the solution to stochastic differential equations," Monte Carlo Methods and Applications, De Gruyter, vol. 23(3), pages 149-157, September.
    2. Zherelo Anatoly, 2013. "On convergence of the method based on approximately exact formulas for functional polynomials for calculation of expectations of functionals to solutions of stochastic differential equations," Monte Carlo Methods and Applications, De Gruyter, vol. 19(3), pages 183-199, October.

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    2. Egorov Alexander & Malyutin Victor, 2017. "A method for the calculation of characteristics for the solution to stochastic differential equations," Monte Carlo Methods and Applications, De Gruyter, vol. 23(3), pages 149-157, September.

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