Projects per year
This paper develops strong convergence of the Euler-Maruyama (EM) schemes for approximating McKean-Vlasov stochastic differential equations (SDEs). In contrast to the existing work, a novel feature is the use of a much weaker condition-local Lipschitzian in the state variable but under uniform linear growth assumption. To obtain the desired approximation, the paper first establishes the existence and uniqueness of solutions of the original McKean-Vlasov SDE using an Euler-like sequence of interpolations and partition of the sample space. Then, the paper returns to the analysis of the EM scheme for approximating solutions of McKean-Vlasov SDEs. A strong convergence theorem is established. Moreover, the convergence rates under global conditions are obtained.
|Journal||IMA Journal of Numerical Analysis|
|Publication status||Accepted/In press - 21 Dec 2021|
- McKean-Vlasov SDE
- one-sided local Lipschitz condition
- local Lipschitz condition
- interpolated Euler-like sequence
- Euler-Maruyama scheme
FingerprintDive into the research topics of 'Strong convergence of Euler-Maruyama schemes for McKean-Vlasov stochastic differential equations under local Lipschitz conditions of state variables'. Together they form a unique fingerprint.
1/01/22 → 31/12/23
Project: Knowledge Exchange
Ergodicity and invariant measures of stochastic delay systems driven by various noises and their applications (Prof. Fuke Wu)
16/03/17 → 15/06/20
Project: Research Fellowship