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

Yuzhong Cheng, Nicole Hufnagel, Hiroki Masuda

    Research output: Contribution to journalArticlepeer-review

    1 Citation (Scopus)

    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.

    Original languageEnglish
    JournalEconometrics and Statistics
    DOIs
    Publication statusAccepted/In press - 2022

    All Science Journal Classification (ASJC) codes

    • Statistics and Probability
    • Economics and Econometrics
    • Statistics, Probability and Uncertainty

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