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The law of the Euler scheme for stochastic differential equations
4 references·16 citing·33 second hop
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this work references cited by second hop

References

  • 2016Numerical solution of stochastic differential equations5,001 cited
  • 1983Stochastic Differential Equations and Diffusion Processes3,836 cited
  • 2006The Malliavin Calculus and Related Topics2,470 cited
  • 1995The Malliavin Calculus and Related Topics1,545 cited

Cited by

  • 2002Simulated likelihood estimation of diffusions with an application to exchange rate dynamics in incomplete markets275 cited
  • 2005On the discretization schemes for the CIR (and Bessel squared) processes246 cited
  • 1997The Euler scheme for Lévy driven stochastic differential equations244 cited
  • 2007Improved Multilevel Monte Carlo Convergence using the Milstein Scheme205 cited
  • 2000Weak approximation of killed diffusion using Euler schemes188 cited
  • 2009High order discretization schemes for the CIR process: Application to affine term structure and Heston models169 cited
  • 2005Statistical Romberg extrapolation: A new variance reduction method and applications to option pricing134 cited
  • 2010Weak approximation of stochastic partial differential equations: the nonlinear case129 cited
  • 2006Error expansion for the discretization of backward stochastic differential equations108 cited
  • 2007Minimum variance importance samplingviaPopulation Monte Carlo93 cited

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  • 2004Estimation of Continuous-Time Markov Processes Sampled at Random Time Intervals93 cited
  • 2005Sensitivity Analysis Using Itô--Malliavin Calculus and Martingales, and Application to Stochastic Optimal Control93 cited
  • 2009Multilevel quasi-Monte Carlo path simulation92 cited
  • 2002The Euler scheme with irregular coefficients91 cited
  • 2004Approximation of expectation of diffusion processes based on Lie algebra and Malliavin calculus90 cited
  • 2018Approximation of Expectation of Diffusion Process and Mathematical Finance90 cited