Estimation of ergodic square-root diffusion under high-frequency sampling

Yuzhong Cheng, Nicole Hufnagel and Hiroki Masuda

Econometrics and Statistics, 2024, vol. 32, issue C, 73-87

Abstract: Gaussian quasi-likelihood estimation of the parameter in the square-root diffusion process is studied under high-frequency sampling. Different from previous studies under low-frequency sampling, high-frequency of data leads to a very simple form of the asymptotic covariance matrix. Through easy-to-compute preliminary contrast functions, a practical two-stage manner without numerical optimization is formulated to conduct not only an asymptotically efficient estimation of the drift parameters but also a high-precision estimator of the diffusion parameter. Simulation experiments are given to illustrate the results.

Keywords: CIR process; Parameter estimation; Gaussian quasi-likelihood; High-frequency data (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecosta:v:32:y:2024:i:c:p:73-87

DOI: 10.1016/j.ecosta.2022.05.003

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