# Parameter estimation for reflected OU processes

arXiv: https://arxiv.org/abs/2205.00670 · HTML: https://mlsanity.com/paper/2205.00670/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 May 2022.

## Built on by (most cited first, 1 of 1)

- [A Comparison of Traditional and Deep Learning Methods for Parameter Estimation of the Ornstein-Uhlenbeck Process](https://mlsanity.com/paper/2404.11526/) (2024)

## Abstract (arXiv)

In this paper, we investigate the parameter estimation problem for reflected OU processes. Both the estimates based on continuously observed processes and discretely observed processes are considered. The explicit formulas for the estimators are derived using the least squares method. Under some regular conditions, we obtain the consistency and establish the asymptotic normality for the estimators. Numerical results show that the proposed estimators perform well with moderate sample sizes.