文章基本信息

标题：New Approach in Dealing with the Non-Negativity of the Conditional Variance in the Estimation of GARCH Model
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作者：Abdeljalil Settar ; Nadia Idrissi Fatmi ; Mohammed Badaoui 等
期刊名称：Central European Journal of Economic Modelling and Econometrics
印刷版ISSN：2080-0886
电子版ISSN：2080-119X
出版年度：2021
期号：1
页码：55-74
DOI：10.24425/cejeme.2021.137355
语种：English
出版社：Polska Akademia Nauk
摘要：In this paper, we propose a robust estimation of the conditional variance of the GARCH(1,1) model with respect to the non-negativity constraint against parameter sign.Conditions of second order stationary as well as the existence of moments are given for the new relaxed GARCH(1,1) model whose conditional variance is estimated deriving firstly the unconstrained estimation of the conditional variance from the GARCH(1,1) state space model, then, the robustification is implemented by the Kalman filter outcomes via density function truncation method.The GARCH(1,1) parameters are subsequently estimated by the quasi-maximum likelihood, using the simultaneous perturbation stochastic approximation, based, first, on the Gaussian distribution and, second, on the Student-t distribution.The proposed approach seems to be efficient in improving the accuracy of the quasi-maximum likelihood estimation of GARCH model parameters, in particular, with a prior boundedness information on volatility.
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