Abstract
In this article, we are interested in least squares estimator for a class of path-dependent McKean-Vlasov stochastic differential equations (SDEs). More precisely, we investigate the consistency and asymptotic distribution of the least squares estimator for the unknown parameters involved by establishing an appropriate contrast function. Comparing to the existing results in the literature, the innovations of this article lie in three aspects: (i) We adopt a tamed Euler-Maruyama algorithm to establish the contrast function under the monotone condition, under which the Euler-Maruyama scheme no longer works; (ii) We take the advantage of linear interpolation with respect to the discrete-time observations to approximate the functional solution; (iii) Our model is more applicable and practice as we are dealing with SDEs with irregular coefficients (for example, Holder continuous) and path-distribution dependent.
| Original language | English |
|---|---|
| Pages (from-to) | 691-716 |
| Journal | Acta Mathematica Scientia |
| Volume | 39 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 1 May 2019 |
| Externally published | Yes |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].Research Keywords
- 60G52
- 60J75
- 62F12
- 62M05
- asymptotic distribution
- consistency
- least squares estimator
- McKean-Vlasov stochastic differential equation
- tamed Euler-Maruyama scheme
- weak monotonicity