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Semiparametric EGARCH model with the case study of China stock market

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  • Yang, Hu
  • Wu, Xingcui

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.

Suggested Citation

  • Yang, Hu & Wu, Xingcui, 2011. "Semiparametric EGARCH model with the case study of China stock market," Economic Modelling, Elsevier, vol. 28(3), pages 761-766.
    • Handle: RePEc:eee:ecmode:v:28:y:2011:i:3:p:761-766
    DOI: 10.1016/j.econmod.2010.10.015
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    References listed on IDEAS

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    More about this item

    Keywords

    Markov; Mixing; Local Polynomial Estimate; Semiparametric method; Asymptotic normality; Stock market;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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