Document Type : Research Article
Authors
1 Department of applied mathematics Ferdowsi university of Mashhad Mashhad, Iran
2 Department of Applied Mathematics, Ferdowsi University of Mashhad, Mashhad, Iran
3 Department of Statistics, Ferdowsi University of Mashhad, Mashhad,
Abstract
In this paper, we analyze the strong convergence and stability of the Compensated Splite-step $theta$ (CSS$theta$) and Forward-Backward Euler-Maruyama (FBEM) methods for Numerical solutions of Stochastic Differential Equations with jumps (SDEwJs),
where $sqrt{2}-1leqthetaleq 1$. The drift term $f$ has a one-sided Lipschitz condition, the diffusion term $g$ and jump term $h$ satisfy global Lipschitz condition.
Furthermore, we discuss about the stability of SDEwJs with constant coefficients and present new useful relations between their coefficients. Finally we examine the correctness and efficiency of theorems with some examples.
In this paper, we analyze the strong convergence and stability of the Compensated Splite-step $theta$ (CSS$theta$) and Forward-Backward Euler-Maruyama (FBEM) methods for Numerical solutions of Stochastic Differential Equations with jumps (SDEwJs),
where $sqrt{2}-1leqthetaleq 1$. The drift term $f$ has a one-sided Lipschitz condition, the diffusion term $g$ and jump term $h$ satisfy global Lipschitz condition.
Furthermore, we discuss about the stability of SDEwJs with constant coefficients and present new useful relations between their coefficients. Finally we examine the correctness and efficiency of theorems with some examples.
Keywords
[2] D. J. Higham and P. E. Kloeden, Numerical methods for nonlinear stochastic differential equations with jumps, Numer. Math. 101(2005), pp.101-119.
[3] D. J. Higham and P. E. Kloeden, Convergence and stability of implicit methods for jump diffusion system, Int. J. Numer. Anal. Model, 3(2006), pp. 125-140.
[4] D. J. Higham and P. E. Kloeden, Strong convergence rates for backward Euleron a class of nonlinear jump-diffusion problems, J. Comput. and Appl. Math., 205(2007), pp. 949-956.
[5] M. Hutzenthaler, A. Jentzen and P.E. Kloeden. Strong convergence of an explicit numerical method for SDEs with non-globally lipschitz continuous coefficients. to appear in The Annals of Applied Probability, 22(2012), pp. 1611-1641.
[6] M. Hutzenthaler, A. Jentzen, and P.E. Kloeden. Strong and weak divergence in nite time of Eulers method for stochastic differential equations with non-globally Lipschitz continuous coefficients. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Science, 467(2013), pp. 1563-2011.
[7] X. Mao, Stochastic Differential Equations and Applications, Horwood Pub Ltd, 2007.
[8] X. Mao and L. Szpruch, Strong convergence and stability of implicit numerical methods for stochastic differential equations with non-globally Lipschitz continuous coefficients, J. Comput. and Appl. Math., 238 (2012), pp. 14-28.
[9] W. Mao, S. You and X. Mao, On the asymptotic stability and numerical analysis of solutions to nonlinear stochastic differential equations with jumps, J. Comput. and Appl. Math., 301 (2016), pp. 1-15.
[10] E. Platen and N. Bruti-Liberati, Numerical Solution of Stochastic Differential Equations with Jumps in Finance, Springer-Verlag, Berlin, 2010.
[11] J. Tan, Z. Mu and Y. Guo, Convergence and stability of the compensated split-step θ method for stochastic differential equations with jumps, Advances in Difference Equations, 2014 (2014), pp. 1-19.
[12] L. Ronghua, W. K. Pangb and W. Qinghe,Numerical analysis for stochastic age dependent population equations with Poisson jumps,J. Math. Anal. Appl. 327,12141224(2007).
[13] X. Wang and S. Gan, Compensated stochastic theta methods for stochastic differential equations with jumps, Appl. Numer. Math., 60 (2010), pp. 877-887.