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Block bootstrap testing for changes in persistence with heavy-tailed innovations

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  • Ruibing Qin
  • Yang Liu

Abstract

This article considers the detection of changes in persistence in heavy-tailed series. We adopt a Dickey–Fuller-type ratio statistic and derive its null asymptotic distribution of test statistic. We find that the asymptotic distribution depends on the stable index, which is often typically unknown and difficult to estimate. Therefore, the block bootstrap method is proposed to detect changes without estimating κ. The empirical sizes and power values are investigated to show that the block bootstrap test is valid. Finally, the validity of the method is demonstrated by analyzing the exchange rate of RMB and US dollars.

Suggested Citation

  • Ruibing Qin & Yang Liu, 2018. "Block bootstrap testing for changes in persistence with heavy-tailed innovations," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 47(5), pages 1104-1116, March.
    • Handle: RePEc:taf:lstaxx:v:47:y:2018:i:5:p:1104-1116
    DOI: 10.1080/03610926.2017.1316398
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    Cited by:

    1. Si Zhang & Hao Jin & Menglin Su, 2024. "Modified Block Bootstrap Testing for Persistence Change in Infinite Variance Observations," Mathematics, MDPI, vol. 12(2), pages 1-25, January.

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