Semiparametric EGARCH model with the case study of China stock market

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.

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Year of publication:	2011
Authors:	Yang, Hu ; Wu, Xingcui
Published in:	Economic Modelling. - Elsevier, ISSN 0264-9993. - Vol. 28.2011, 3, p. 761-766
Publisher:	Elsevier
Subject:	Markov \| Mixing \| Local Polynomial Estimate \| Semiparametric method \| Asymptotic normality \| Stock market

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Type of publication:	Article
Classification:	C13 - Estimation ; C14 - Semiparametric and Nonparametric Methods ; C53 - Forecasting and Other Model Applications
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010573294