Strong convergence rates for backward Euler on a class of nonlinear jump-diffusion problems
DOI10.1016/j.cam.2006.03.039zbMath1128.65007OpenAlexW2129849411MaRDI QIDQ885946
Desmond J. Higham, Peter E. Kloeden
Publication date: 14 June 2007
Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.cam.2006.03.039
stochastic differential equationconvergencePoisson processone-sided Lipschitz conditionIto lemmaimplicit Euler-Maruyama methods
Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Stability and convergence of numerical methods for ordinary differential equations (65L20) Ordinary differential equations and systems with randomness (34F05) Multistep, Runge-Kutta and extrapolation methods for ordinary differential equations (65L06) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical solutions to stochastic differential and integral equations (65C30)
Related Items
Cites Work
- A survey of numerical methods for stochastic differential equations
- Numerical methods for nonlinear stochastic differential equations with jumps
- The Order of Approximations for Solutions of Itô-Type Stochastic Differential Equations with Jumps
- In-Probability Approximation and Simulation of Nonlinear Jump-Diffusion Stochastic Differential Equations
- Exact solutions and doubly efficient approximations of jump-diffusion itô equations
- Strong Convergence of Euler-Type Methods for Nonlinear Stochastic Differential Equations
- Financial Modelling with Jump Processes
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item