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Robust closed-form estimators for the integer-valued GARCH (1,1) model

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  • Li, Qi
  • Lian, Heng
  • Zhu, Fukang

Abstract

A closed-form estimator and its several robust versions for the integer-valued GARCH(1, 1) model are proposed. These estimators are easy to implement and do not require the use of any numerical optimization procedure. Consistency and asymptotic normality for the non-robust closed-form estimator is established. The robustification of the closed-form estimator is done by replacing the sample mean and autocorrelations by robust estimators of them, respectively. The performances of these closed-form estimators are investigated and compared via simulations. New estimators are applied to 5 stock-market data sets with different periods and time intervals, and their prediction performances are assessed by in-sample prediction, out-of-sample prediction and scoring rules. Other possible proposals related to the closed-form estimators are also discussed.

Suggested Citation

  • Li, Qi & Lian, Heng & Zhu, Fukang, 2016. "Robust closed-form estimators for the integer-valued GARCH (1,1) model," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 209-225.
    • Handle: RePEc:eee:csdana:v:101:y:2016:i:c:p:209-225
    DOI: 10.1016/j.csda.2016.03.006
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    Cited by:

    1. Huiyu Mao & Fukang Zhu & Yan Cui, 2020. "A generalized mixture integer-valued GARCH model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(3), pages 527-552, September.
    2. Qi Li & Fukang Zhu, 2020. "Mean targeting estimator for the integer-valued GARCH(1, 1) model," Statistical Papers, Springer, vol. 61(2), pages 659-679, April.
    3. Mengya Liu & Qi Li & Fukang Zhu, 2020. "Self-excited hysteretic negative binomial autoregression," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(3), pages 385-415, September.

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