Local linear estimators for reflected diffusions

Dingwen Zhang

Journal of Nonparametric Statistics, 2025, vol. 37, issue 4, 1112-1130

Abstract: In this paper, we investigate the nonparametric local linear estimator for the drift function of reflected stochastic differential equations based on the discretely observed process. Under certain regularity conditions, we prove the strong consistency and establish the asymptotic normality for our proposed estimator. We also propose the optimal bandwidth selector for the estimator and show that the estimator does not have a boundary effect. Simulation results demonstrate that our method is superior to the method proposed by Cholaquidis et al. [Stat. Sin. 2021, 31: 29–51]. We apply the EUR/USD currency exchange rate data to illustrate our theoretical results.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/10485252.2024.2426099 (text/html)
Access to full text is restricted to subscribers.

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:taf:gnstxx:v:37:y:2025:i:4:p:1112-1130

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/GNST20

DOI: 10.1080/10485252.2024.2426099

Access Statistics for this article

Journal of Nonparametric Statistics is currently edited by Jun Shao

More articles in Journal of Nonparametric Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().