Work

Improved Berry-Esseen bounds for parameter estimation of a fractional Ornstein-Uhlenbeck process observed at high frequency

Year: 2026

Type: article

Abstract: This paper deals with parameter estimation of the drift coefficient, denoted θ , for a fractional Ornstein-Uhlenbeck process observed at high frequency. Specifically, we provide an estimator of θ , namely $\widetilde{\theta }_{n}$ , using the second moment method. We develop some novel estimates to derive an explicit Berry–Esseen bound in the Wasserstein distance for the normal approximation of $\widetilde{\theta }_{n}$ . Moreover, we prove that our estimate is strictly sharper than the one obtained in Douissi et al. (Electron. J. Stat. 16(1):636–670, 2022 ).

Source: Advances in Continuous and Discrete Models

DOI: 10.1186/s13662-026-04060-9

Authors: Fares Alazemi, Khalifa Es-Sebaiy, Mishari Al-Foraih

Institution: Kuwait University

Language: English

Topic: Stochastic processes and financial applications

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $1,890

Funder: Kuwait University