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Convergence of the Euler–Maruyama method for stochastic differential equations with Markovian switching

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  • Yuan, Chenggui
  • Mao, Xuerong

Abstract

Stochastic differential equations with Markovian switching (SDEwMSs), one of the important classes of hybrid systems, have been used to model many physical systems that are subject to frequent unpredictable structural changes. The research in this area has been both theoretical and applied. Most of SDEwMSs do not have explicit solutions so it is important to have numerical solutions. It is surprising that there are not any numerical methods established for SDEwMSs yet, although the numerical methods for stochastic differential equations (SDEs) have been well studied. The main aim of this paper is to develop a numerical scheme for SDEwMSs and estimate the error between the numerical and exact solutions. This is the first paper in this direction and the emphasis lies on the error analysis.

Suggested Citation

  • Yuan, Chenggui & Mao, Xuerong, 2004. "Convergence of the Euler–Maruyama method for stochastic differential equations with Markovian switching," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 64(2), pages 223-235.
    • Handle: RePEc:eee:matcom:v:64:y:2004:i:2:p:223-235
    DOI: 10.1016/j.matcom.2003.09.001
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    References listed on IDEAS

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    1. Küchler, Uwe & Platen, Eckhard, 2000. "Strong discrete time approximation of stochastic differential equations with time delay," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 54(1), pages 189-205.
    2. O. L. V. Costa & E. K. Boukas, 1998. "Necessary and Sufficient Condition for Robust Stability and Stabilizability of Continuous-Time Linear Systems with Markovian Jumps," Journal of Optimization Theory and Applications, Springer, vol. 99(2), pages 359-379, November.
    3. Mao, Xuerong, 1999. "Stability of stochastic differential equations with Markovian switching," Stochastic Processes and their Applications, Elsevier, vol. 79(1), pages 45-67, January.
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    Cited by:

    1. Cañada, Héctor & Romera, Rosario, 2009. "Controlled diffusion processes with markovian switchings for modeling dynamical engineering systems," DES - Working Papers. Statistics and Econometrics. WS ws093714, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Yang Li & Taitao Feng & Yaolei Wang & Yifei Xin, 2021. "A High Order Accurate and Effective Scheme for Solving Markovian Switching Stochastic Models," Mathematics, MDPI, vol. 9(6), pages 1-15, March.
    3. Zhang, Zhenzhong & Zhou, Tiandao & Jin, Xinghu & Tong, Jinying, 2020. "Convergence of the Euler–Maruyama method for CIR model with Markovian switching," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 177(C), pages 192-210.
    4. Romuald Hervé Momeya & Manuel Morales, 2016. "On the Price of Risk of the Underlying Markov Chain in a Regime-Switching Exponential Lévy Model," Methodology and Computing in Applied Probability, Springer, vol. 18(1), pages 107-135, March.
    5. Gao, Xiangyu & Liu, Yi & Wang, Yanxia & Yang, Hongfu & Yang, Maosong, 2021. "Tamed-Euler method for nonlinear switching diffusion systems with locally Hölder diffusion coefficients," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    6. Fan, Zhencheng, 2017. "Convergence of numerical solutions to stochastic differential equations with Markovian switching," Applied Mathematics and Computation, Elsevier, vol. 315(C), pages 176-187.
    7. Ouyang, Mengqian & Li, Xiaoyue, 2015. "Permanence and asymptotical behavior of stochastic prey–predator system with Markovian switching," Applied Mathematics and Computation, Elsevier, vol. 266(C), pages 539-559.
    8. Cañada, Héctor & Romera, Rosario, 2012. "Controlled diffusion processes with Markovian switchings for modeling dynamical engineering systems," European Journal of Operational Research, Elsevier, vol. 221(3), pages 614-624.
    9. Xinghu Jin & Tian Shen & Zhonggen Su & Yuzhen Tan, 2025. "The Euler-Maruyama Approximation of State-Dependent Regime Switching Diffusions," Journal of Theoretical Probability, Springer, vol. 38(1), pages 1-40, March.
    10. Xinghu Jin & Tian Shen & Zhonggen Su, 2023. "Using Stein’s Method to Analyze Euler–Maruyama Approximations of Regime-Switching Jump Diffusion Processes," Journal of Theoretical Probability, Springer, vol. 36(3), pages 1797-1828, September.
    11. Zhao, Jingjun & Yi, Yulian & Xu, Yang, 2021. "Strong convergence of explicit schemes for highly nonlinear stochastic differential equations with Markovian switching," Applied Mathematics and Computation, Elsevier, vol. 398(C).

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