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Garch Model Test Using High-Frequency Data

Author

Listed:
  • Chunliang Deng

    (School of Economics and Statistics, Guangzhou University, Guangzhou 510006, China
    School of Mathematics, Jiaying University, Meizhou 514015, China)

  • Xingfa Zhang

    (School of Economics and Statistics, Guangzhou University, Guangzhou 510006, China)

  • Yuan Li

    (School of Economics and Statistics, Guangzhou University, Guangzhou 510006, China)

  • Qiang Xiong

    (School of Economics and Statistics, Guangzhou University, Guangzhou 510006, China)

Abstract

This work is devoted to the study of the parameter test for the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model. Based on the daily GARCH model, using the parameter estimator obtained by intraday high-frequency data, the adjusted Likelihood Ratio test statistic and Wald test statistic are provided. Asymptotic distributions of the two adjusted test statistics are deducted and a way to select the optimal sampling frequency is also discussed. Simulation studies show that the proposed test statistics have better size and power than traditional ones (without using intraday high-frequency data). An empirical study is given to illustrate the potential applications of the proposed tests. The results show the idea of this article is of certain superiority and it can be extended to other GARCH type models.

Suggested Citation

  • Chunliang Deng & Xingfa Zhang & Yuan Li & Qiang Xiong, 2020. "Garch Model Test Using High-Frequency Data," Mathematics, MDPI, vol. 8(11), pages 1-17, November.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:11:p:1922-:d:438733
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    References listed on IDEAS

    as
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