STRONG CONVERGENCE OF NUMERICAL METHODS FOR NONLINEAR STOCHASTIC DIFFERENTIAL EQUATIONS WITH JUMPS

X. Mao and Lukasz Szpruch [3] proved strong con- vergence of stochastic differential equations (SDEs) under less re- strictive conditions. As an application of this general theory that they showed the diffusion coeficient is globally Lipschitz, but the drift coeficient satisfies only a one-sided Lipschitz condition the numerical methods are strong convergence; In this paper we ex- tend this conditions to the (SDEs) with jumps, where presented by D. Higham and Peter E. Kloeden [1] for (SDEs) with Poisson- driven jumps and apply this condition for split-step backward Eu- ler(SSBE) method