The truncated EM method for stochastic differential equations with Poisson jumps
This work provides theoretical convergence guarantees for numerical methods applied to SDEs with jumps under relaxed conditions, addressing a gap in the literature for super-linear coefficients.
The paper establishes finite-time strong convergence rates for the truncated Euler-Maruyama method applied to stochastic differential equations with Poisson jumps under super-linear growth conditions, showing optimal rates close to 1/(1+γ) for r≥2 and not greater than 1/4 for 0<r<2, and demonstrating preservation of mean-square exponential stability and asymptotic boundedness.
In this paper, we use the truncated EM method to study the finite time strong convergence for the SDEs with Poisson jumps under the Khasminskii-type condition. We establish the finite time $ \mathcal L ^r (r \ge 2) $ convergence rate when the drift and diffusion coefficients satisfy super-linear condition and the jump coefficient satisfies the linear growth condition. The result shows that the optimal $\mathcal L ^r$-convergence rate is close to $ 1/ (1 + γ)$, where $γ$ is the super-linear growth constant. This is significantly different from the result on SDEs without jumps. When all the three coefficients of SDEs are allowing to grow super-linearly, the $ \mathcal L^r (0<r<2)$ strong convergence results are also investigated and the optimal strong convergence rate is shown to be not greater than $1/4$. Moreover, we prove that the truncated EM method preserve nicely the mean square exponentially stability and asymptotic boundedness of the underlying SDEs with Piosson jumps. Several examples are given to illustrate our results.