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Brief introduction of Quasi-Monte Carlo Methods and their Applications

By Gunther Leobacher

In the first part, we briefly recall the theory of stochastic differential equations (SDEs) and present Maruyama's classical theorem on strong convergence of the Euler-Maruyama method, for which both drift and diffusion coefficient of the SDE need to be Lipschitz continuous.

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Citation data

  • DOI 10.24350/CIRM.V.19664303
  • Cite this video Leobacher, Gunther (02/11/2020). Brief introduction of Quasi-Monte Carlo Methods and their Applications. CIRM. Audiovisual resource. DOI: 10.24350/CIRM.V.19664303
  • URL https://dx.doi.org/10.24350/CIRM.V.19664303

Bibliography

  • Drmota, M.; Tichy, R.F.: Sequences, discrepancies and applications. Lecture Notes in Mathematics, 1651. Springer-Verlag, Berlin, 1997. - http://dx.doi.org/10.1007/BFb0093404
  • Kuipers, L.; Niederreiter, H.: Uniform distribution of sequences. Pure and Applied Mathematics. Wiley-Interscience, 1974.
  • Leobacher, G.; Pillichshammer, F.: Introduction to quasi-Monte Carlo integration and applications. Compact Textbooks in Mathematics. Birkhäuser, Cham, 2014. - http://dx.doi.org/10.1007/978-3-319-03425-6
  • Leobacher, Gunther; Szölgyenyi, Michaela A strong order 1/2 method for multidimensional SDEs with discontinuous drift.The Annals of Applied Probability, 2017, vol. 27, no 4, p. 2383-2418. - http://dx.doi.org/10.1214/16-AAP1262
  • Mao, X.: Stochastic differential equations and their applications. Series in Mathematics & Applications. Horwood Publishing Limited, Chichester, 1997 -

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