Least squares estimation for path-distribution dependent stochastic differential equations

Panpan Ren and Jiang-Lun Wu

Applied Mathematics and Computation, 2021, vol. 410, issue C

Abstract: We study a least squares estimator for an unknown parameter in the drift coefficient of a path-distribution dependent stochastic differential equation involving a small dispersion parameter ε>0. The estimator, based on n (where n∈N) discrete time observations of the stochastic differential equation, is shown to be convergent weakly to the true value as ε→0 and n→∞. This indicates that the least squares estimator obtained is consistent with the true value. Moreover, we obtain the rate of convergence and derive the asymptotic distribution of least squares estimator.

Keywords: Path-distribution dependent stochastic differential equation; Least squares estimator; Consistency; Asymptotic distribution (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300321005464
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:410:y:2021:i:c:s0096300321005464

DOI: 10.1016/j.amc.2021.126457

Access Statistics for this article

Applied Mathematics and Computation is currently edited by Theodore Simos

More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().