Asymptotic behaviour of the improved trajectory fitting estimation for reflected Ornstein-Uhlenbeck process with large drift

In this paper, we consider the problem of parameter estimation for reflected Ornstein-Uhlenbeck process with large drift. The classical trajectory fitting estimator is inconsistent when the drift coefficient θ < 0, whereas it is consistent when θ ≥ 0. To overcome this limitation, we introduce an improved trajectory fitting estimator, which remains consistent for all θ ∈ ℝ. The consistency and asymptotic distribution of the improved trajectory fitting estimator are established under various combinations of the sign of θ. Computer simulations are performed to illustrate our theory.

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Publication Details

Journal
Stochastics and Dynamics
Published
2026-10-13
DOI
https://doi.org/10.1142/s0219493726500310
Primary Topic
Stochastic processes and financial applications
Type
article
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article

Asymptotic behaviour of the improved trajectory fitting estimation for reflected Ornstein-Uhlenbeck process with large drift

Xiaotai Wu, Xuekang Zhang, Haofei Liu
Stochastics and Dynamics
Stochastic processes and financial applications
article

Asymptotic behaviour of the improved trajectory fitting estimation for reflected Ornstein-Uhlenbeck process with large drift

Xiaotai Wu, Xuekang Zhang, Haofei Liu
article en

Abstract

In this paper, we consider the problem of parameter estimation for reflected Ornstein-Uhlenbeck process with large drift. The classical trajectory fitting estimator is inconsistent when the drift coefficient θ < 0, whereas it is consistent when θ ≥ 0. To overcome this limitation, we introduce an improved trajectory fitting estimator, which remains consistent for all θ ∈ ℝ. The consistency and asymptotic distribution of the improved trajectory fitting estimator are established under various combinations of the sign of θ. Computer simulations are performed to illustrate our theory.

Stochastics and Dynamics
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Stochastic processes and financial applications
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