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On the tail index inference for heavy-tailed GARCH-type innovations

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  • Moosup Kim
  • Sangyeol Lee

Abstract

In this study, we investigate the smoothing Hill plot and change point test for the tail index of power-transformed and threshold generalized autoregressive conditional heteroscedasticity (PTTGARCH) and autoregressive and moving average (ARMA)–GARCH innovations. It is shown that their asymptotic properties are the same as those in the i.i.d. sample case. For illustration, we provide a simulation study and real data analysis. Copyright The Institute of Statistical Mathematics, Tokyo 2016

Suggested Citation

  • Moosup Kim & Sangyeol Lee, 2016. "On the tail index inference for heavy-tailed GARCH-type innovations," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 68(2), pages 237-267, April.
    • Handle: RePEc:spr:aistmt:v:68:y:2016:i:2:p:237-267
    DOI: 10.1007/s10463-014-0495-4
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    References listed on IDEAS

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    Cited by:

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    2. Yongqing Guo & Xiaoyuan Wang & Qing Xu & Feifei Liu & Yaqi Liu & Yuanyuan Xia, 2019. "Change-Point Analysis of Eye Movement Characteristics for Female Drivers in Anxiety," IJERPH, MDPI, vol. 16(7), pages 1-17, April.
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