Abstract
This paper deals with the rate of convergence for the central limit theorem of estimators of the drift coefficient, denoted θ, for the Ornstein-Uhlenbeck process X: = { Xt, t≥ 0 } observed at high frequency. We provide an approximate minimum contrast estimator and an approximate maximum likelihood estimator of θ, namely θ˜n:=1/(2n∑i=1nXti2), and θˆn:=−∑i=1nXti−1(Xti−Xti−1)/(Δn∑i=1nXti−12), respectively, where ti= iΔ n, i= 0 , 1 , … , n, Δ n→ 0. We provide Wasserstein bounds in the central limit theorem for θ˜ n and θˆ n.
| Original language | English |
|---|---|
| Article number | 62 |
| Journal | Journal of Inequalities and Applications |
| Volume | 2023 |
| Issue number | 1 |
| DOIs | |
| State | Published - 2023 |
Keywords
- High frequency data
- Ornstein-Uhlenbeck process
- Parameter estimation
- Rate of normal convergence of the estimators
Funding Agency
- Kuwait Foundation for the Advancement of Sciences
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