Startseite The truncated Euler–Maruyama method of one-dimensional stochastic differential equations involving the local time at point zero
Artikel
Lizenziert
Nicht lizenziert Erfordert eine Authentifizierung

The truncated Euler–Maruyama method of one-dimensional stochastic differential equations involving the local time at point zero

  • Kamal Hiderah EMAIL logo
Veröffentlicht/Copyright: 28. Februar 2023
Veröffentlichen auch Sie bei De Gruyter Brill

Abstract

Recently, Mao developed a new explicit method, called the truncated Euler–Maruyama method for nonlinear SDEs, and established the strong convergence theory under the local Lipschitz condition plus the Khasminskii-type condition. The key aim of this paper is to establish the rate of strong convergence of the truncated Euler–Maruyama method for one-dimensional stochastic differential equations involving that the local time at point zero under the drift coefficient satisfies a one-sided Lipschitz condition and plus some additional conditions.


Communicated by Stanislav Molchanov


Acknowledgements

We are thankful to the editor and to the anonymous referee for very careful reading and her/his valuable remarks and suggestions which led to the improvement of the article.

References

[1] R. Belfadli, S. Hamadène and Y. Ouknine, On one-dimensional stochastic differential equations involving the maximum process, Stoch. Dyn. 9 (2009), no. 2, 277–292. 10.1142/S0219493709002671Suche in Google Scholar

[2] M. Benabdallah, Y. Elkettani and K. Hiderah, Approximation of Euler–Maruyama for one-dimensional stochastic differential equations involving the local times of the unknown process, Monte Carlo Methods Appl. 22 (2016), no. 4, 307–322. 10.1515/mcma-2016-0115Suche in Google Scholar

[3] M. Benabdallah and K. Hiderah, The weak rate of convergence for the Euler–Maruyama approximation of one-dimensional stochastic differential equations involving the local times of the unknown process, preprint (2017), https://arxiv.org/abs/1701.00551v2. Suche in Google Scholar

[4] M. Benabdallah and K. Hiderah, Strong rate of convergence for the Euler–Maruyama approximation of one-dimensional stochastic differential equations involving the local time at point zero, Monte Carlo Methods Appl. 24 (2018), no. 4, 249–262. 10.1515/mcma-2018-2021Suche in Google Scholar

[5] P. Étoré and M. Martinez, Exact simulation of one-dimensional stochastic differential equations involving the local time at zero of the unknown process, Monte Carlo Methods Appl. 19 (2013), no. 1, 41–71. 10.1515/mcma-2013-0002Suche in Google Scholar

[6] P. Étoré and M. Martinez, Time inhomogeneous stochastic differential equations involving the local time of the unknown process, and associated parabolic operators, Stochastic Process. Appl. 128 (2018), no. 8, 2642–2687. 10.1016/j.spa.2017.09.018Suche in Google Scholar

[7] Q. Guo, W. Liu and X. Mao, A note on the partially truncated Euler–Maruyama method, Appl. Numer. Math. 130 (2018), 157–170. 10.1016/j.apnum.2018.04.004Suche in Google Scholar

[8] Q. Guo, W. Liu, X. Mao and R. Yue, The partially truncated Euler–Maruyama method and its stability and boundedness, Appl. Numer. Math. 115 (2017), 235–251. 10.1016/j.apnum.2017.01.010Suche in Google Scholar

[9] Q. Guo, X. Mao and R. Yue, The truncated Euler–Maruyama method for stochastic differential delay equations, Numer. Algorithms 78 (2018), no. 2, 599–624. 10.1007/s11075-017-0391-0Suche in Google Scholar

[10] K. Hiderah, Existence and pathwise uniqueness of solutions for stochastic differential equations involving the Local time at point zero, Stoch. Anal. Appl. (2021), 10.1080/07362994.2021.2011317. 10.1080/07362994.2021.2011317Suche in Google Scholar

[11] L. Hu, X. Li and X. Mao, Convergence rate and stability of the truncated Euler–Maruyama method for stochastic differential equations, J. Comput. Appl. Math. 337 (2018), 274–289. 10.1016/j.cam.2018.01.017Suche in Google Scholar

[12] M. Hutzenthaler, A. Jentzen and P. E. Kloeden, Strong convergence of an explicit numerical method for SDEs with nonglobally Lipschitz continuous coefficients, Ann. Appl. Probab. 22 (2012), no. 4, 1611–1641. 10.1214/11-AAP803Suche in Google Scholar

[13] J.-F. Le Gall, One-dimensional stochastic differential equations involving the local times of the unknown process, Stochastic Analysis and Applications (Swansea 1983), Lecture Notes in Math. 1095, Springer, Berlin (1984), 51–82. 10.1007/BFb0099122Suche in Google Scholar

[14] W. Liu and X. Mao, Strong convergence of the stopped Euler–Maruyama method for nonlinear stochastic differential equations, Appl. Math. Comput. 223 (2013), 389–400. 10.1016/j.amc.2013.08.023Suche in Google Scholar

[15] X. Mao, The truncated Euler–Maruyama method for stochastic differential equations, J. Comput. Appl. Math. 290 (2015), 370–384. 10.1016/j.cam.2015.06.002Suche in Google Scholar

[16] X. Mao, Convergence rates of the truncated Euler–Maruyama method for stochastic differential equations, J. Comput. Appl. Math. 296 (2016), 362–375. 10.1016/j.cam.2015.09.035Suche in Google Scholar

[17] D. Revuz and M. Yor, Continuous Martingales and Brownian Motion, Springer, Berlin, 2005. Suche in Google Scholar

[18] S. Sabanis, Euler approximations with varying coefficients: The case of superlinearly growing diffusion coefficients, Ann. Appl. Probab. 26 (2016), no. 4, 2083–2105. 10.1214/15-AAP1140Suche in Google Scholar

[19] X. Wang and S. Gan, The tamed Milstein method for commutative stochastic differential equations with non-globally Lipschitz continuous coefficients, J. Difference Equ. Appl. 19 (2013), no. 3, 466–490. 10.1080/10236198.2012.656617Suche in Google Scholar

[20] H. Yang, F. Wu, P. E. Kloeden and X. Mao, The truncated Euler–Maruyama method for stochastic differential equations with Hölder diffusion coefficients, J. Comput. Appl. Math. 366 (2020), Article ID 112379. 10.1016/j.cam.2019.112379Suche in Google Scholar

[21] W. Yue and T. Zhang, Absolute continuity of the laws of perturbed diffusion processes and perturbed reflected diffusion processes, J. Theoret. Probab. 28 (2015), no. 2, 587–618. 10.1007/s10959-013-0499-7Suche in Google Scholar

Received: 2022-01-09
Accepted: 2022-09-04
Published Online: 2023-02-28
Published in Print: 2023-06-01

© 2023 Walter de Gruyter GmbH, Berlin/Boston

Heruntergeladen am 28.9.2025 von https://www.degruyterbrill.com/document/doi/10.1515/rose-2023-2003/html
Button zum nach oben scrollen