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2009•Jilin Normal University JournalRequires access

Parameters Estimation of a Asymmetric GARCH Model

Pan Bao-guo

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Abstract

The parameters estimation of the asymmetric GARCH Model is Usually carried out by quasi-maximum likehood estimator,the results about the consistency and asymptotic normality of the estimator have been found in many papers.A new estimation method of the model is proposed,which is called as a weighted quasi-maximum likelihood estimator.The consistency and asymptotic normality of the estimator of the asymmetric GARCH Model are proved under some conditions.

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What this paper is about

The parameters estimation of the asymmetric GARCH Model is Usually carried out by quasi-maximum likehood estimator,the results about the consistency and asymptotic normality of the estimator have been found in many papers.A new estimation method of the model is proposed,which is called as a weighted quasi-maximum likelihood estimator.The consistency and asymptotic normality of the estimator of the asymmetric GARCH Model are proved under some conditions.

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Available abstract

The parameters estimation of the asymmetric GARCH Model is Usually carried out by quasi-maximum likehood estimator,the results about the consistency and asymptotic normality of the estimator have been found in many papers.A new estimation method of the model is proposed,which is called as a weighted quasi-maximum likelihood estimator.The consistency and asymptotic normality of the estimator of the asymmetric GARCH Model are proved under some conditions.

Key concepts: Asymptotic distribution, Estimator, Mathematics, Consistency (knowledge bases), Strong consistency, Normality, Autoregressive conditional heteroskedasticity, Estimation

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