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Asymptotic properties of the QMLE in a log-linear RealGARCH model with Gaussian errors

Author

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  • Caiya Zhang

    (Zhejiang University City College)

  • Kaihong Xu

    (Zhejiang University City College)

  • Lianfen Qian

    (Florida Atlantic University)

Abstract

To incorporate the realized volatility in stock return, Hansen et al. (J Appl Econ 27:877–906, 2012) proposed a RealGARCH model and conjectured some theoretical properties about the quasi-maximum likelihood estimation (QMLE) for parameters in a log-linear RealGARCH model without rigorous proof. Under Gaussian errors, this paper derives the detailed proof of the theoretical results including consistency and asymptotic normality of the QMLE, hence it solves the conjectures in Hansen et al. (J Appl Econ 27:877–906, 2012).

Suggested Citation

  • Caiya Zhang & Kaihong Xu & Lianfen Qian, 2020. "Asymptotic properties of the QMLE in a log-linear RealGARCH model with Gaussian errors," Statistical Papers, Springer, vol. 61(6), pages 2313-2330, December.
    • Handle: RePEc:spr:stpapr:v:61:y:2020:i:6:d:10.1007_s00362-018-1051-8
    DOI: 10.1007/s00362-018-1051-8
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    References listed on IDEAS

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