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Testing for the change of the mean-reverting parameter of an autoregressive model with stationary Gaussian noise

Author

Listed:
  • Alexandre Brouste

    (Le Mans Université)

  • Chunhao Cai

    (Shanghai University of Finance and Economics)

  • Marius Soltane

    (Le Mans Université)

  • Longmin Wang

    (Nankai University)

Abstract

The likelihood ratio test for a change in the mean-reverting parameter of a first order autoregressive model with stationary Gaussian noise is considered. The test statistic converges in distribution to the Gumbel extreme value distribution under the null hypothesis of no change-point for a large class of covariance structures including long-memory processes as the fractional Gaussian noise.

Suggested Citation

  • Alexandre Brouste & Chunhao Cai & Marius Soltane & Longmin Wang, 2020. "Testing for the change of the mean-reverting parameter of an autoregressive model with stationary Gaussian noise," Statistical Inference for Stochastic Processes, Springer, vol. 23(2), pages 301-318, July.
    • Handle: RePEc:spr:sistpr:v:23:y:2020:i:2:d:10.1007_s11203-020-09217-1
    DOI: 10.1007/s11203-020-09217-1
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    References listed on IDEAS

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    1. Jim Gatheral & Thibault Jaisson & Mathieu Rosenbaum, 2018. "Volatility is rough," Quantitative Finance, Taylor & Francis Journals, vol. 18(6), pages 933-949, June.
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    Cited by:

    1. Milheiro-Oliveira, Paula, 2022. "An alternative sequential method for the state estimation of a partially observed SETAR(1) process," Statistics & Probability Letters, Elsevier, vol. 184(C).

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