Estimation of ergodic square-root diffusion under high-frequency sampling
Statistics Theory
2022-06-24 v3 Probability
Statistics Theory
Abstract
Gaussian quasi-likelihood estimation of the parameter in the square-root diffusion process is studied under high frequency sampling. Different from the previous study of Overbeck and Ryd\'{e}n(1998) under low-frequency sampling, high-frequency of data provides 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 in order to conduct not only an asymptotically efficient estimation of the drift parameters, but also high-precision estimator of the diffusion parameter. Simulation experiments are given to illustrate the results.
Cite
@article{arxiv.2103.15457,
title = {Estimation of ergodic square-root diffusion under high-frequency sampling},
author = {Yuzhong Cheng and Nicole Hufnagel and Hiroki Masuda},
journal= {arXiv preprint arXiv:2103.15457},
year = {2022}
}
Comments
Figure 3 is exchanged. Previously, the simulations from Figure 2 were also shown here