Least squares estimators for reflected Ornstein–Uhlenbeck processes

Han Yuecaia and Zhang Dingwen

Communications in Statistics - Theory and Methods, 2024, vol. 53, issue 21, 7746-7759

Abstract: In this article, we investigate the parameter estimation problem for reflected Ornstein–Uhlenbeck processes with mean reversion. Both estimates based on either continuously or discretely observed processes are considered. The explicit formulas for the estimators are derived using the least squares method. Under regular conditions, we obtain the strong consistency and establish the asymptotic normality for the estimators. Simulation results demonstrate that the performance of our proposed estimators for the drift parameters is superior to the moment estimators. The currency exchange rate data is used to illustrate the theoretical results.

Date: 2024
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DOI: 10.1080/03610926.2023.2273204

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