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

Caiya Zhang, Kaihong Xu and Lianfen Qian ()
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Caiya Zhang: Zhejiang University City College
Kaihong Xu: Zhejiang University City College
Lianfen Qian: Florida Atlantic University

Statistical Papers, 2020, vol. 61, issue 6, No 4, 2313-2330

Abstract: 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).

Keywords: RealGARCH model; Quasi-maximum likelihood estimator; Consistency and asymptotic normality (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s00362-018-1051-8

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