Semiparametric EGARCH model with the case study of China stock market

Hu Yang and Xingcui Wu

Economic Modelling, 2011, vol. 28, issue 3, 761-766

Abstract: In this paper, we propose a new semiparametric method for GARCH model by combining the EGARCH (1,1) model and local polynomial regression. Based on the idea of two-stage estimate, a link function is estimated by the local polynomial and then the parameters are obtained via the weighted least square method. Finally we apply this method to the Shanghai Composite Index in the China stock market and compared the results with these of EGARCH.

Keywords: Markov; Mixing; Local Polynomial Estimate; Semiparametric method; Asymptotic normality; Stock market (search for similar items in EconPapers)
JEL-codes: C13 C14 C53 (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:28:y:2011:i:3:p:761-766

DOI: 10.1016/j.econmod.2010.10.015

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