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Euler scheme for reflected stochastic differential equations

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  • Lépingle, D.

Abstract

Using some exponential variables in the time discretization of some reflected stochastic differential equations yields the same rate of convergence as in the usual Euler-Maruyama scheme.

Suggested Citation

  • Lépingle, D., 1995. "Euler scheme for reflected stochastic differential equations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 38(1), pages 119-126.
    • Handle: RePEc:eee:matcom:v:38:y:1995:i:1:p:119-126
    DOI: 10.1016/0378-4754(93)E0074-F
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    Cited by:

    1. Bo, Lijun & Yang, Xuewei, 2012. "Sequential maximum likelihood estimation for reflected generalized Ornstein–Uhlenbeck processes," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1374-1382.
    2. Fusai, Gianluca & Luciano, Elisa, 2001. "Dynamic value at risk under optimal and suboptimal portfolio policies," European Journal of Operational Research, Elsevier, vol. 135(2), pages 249-269, December.
    3. Wu, Shujin & Han, Dong, 2007. "Algorithmic analysis of Euler scheme for a class of stochastic differential equations with jumps," Statistics & Probability Letters, Elsevier, vol. 77(2), pages 211-219, January.
    4. Costantini, C., 1999. "Variance reduction by antithetic random numbers of Monte Carlo methods for unrestricted and reflecting diffusions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 51(1), pages 1-17.
    5. Hausenblas Erika, 2000. "A Numerical Scheme using Excursion Theory for Simulating Stochastic Differential Equations with Reflection and Local Time at a Boundary," Monte Carlo Methods and Applications, De Gruyter, vol. 6(2), pages 81-104, December.

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