Refine search
Actions for selected content:
1 results
Euler–Maruyama approximation for stable stochastic differential equations with Markovian switching and related asymptotics
- Part of
-
- Journal:
- Journal of Applied Probability / Volume 63 / Issue 3 / September 2026
- Published online by Cambridge University Press:
- 05 February 2026, pp. 890-918
- Print publication:
- September 2026
-
- Article
-
- You have access
- HTML
- Export citation
-
We investigate the EM approximation for
$\mathbb{R}^d$-valued ergodic stochastic differential equations (SDEs) driven by rotationally invariant 
$\alpha$-stable processes (
$\alpha\in(1,2)$) with Markovian switching. The coefficient g violates the dissipative condition for certain states of the switching process. Using the Lindeberg principle, we establish quantitative error bounds between the original process 
$(X_t,R_t)_{t\geqslant 0}$ and its Euler–Maruyama (EM) scheme under a specially designed metric. Furthermore, we derive both a central limit theorem and a moderate derivation principle for the empirical measures of both the SDE and its EM scheme. The theoretical results are subsequently validated through a concrete example.
