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A large deviation result for maximum likelihood estimator of non-homogeneous Ornstein–Uhlenbeck processes

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  • Zhao, Shoujiang
  • Liu, Qiaojing

Abstract

We establish the large deviation principle for maximum likelihood estimator of some diffusion process. We overcome the difficulty of non-steepness and obtain large deviations in the case of non-Gaussian limit distribution by local large deviation principle and exponential tightness.

Suggested Citation

  • Zhao, Shoujiang & Liu, Qiaojing, 2020. "A large deviation result for maximum likelihood estimator of non-homogeneous Ornstein–Uhlenbeck processes," Statistics & Probability Letters, Elsevier, vol. 162(C).
    • Handle: RePEc:eee:stapro:v:162:y:2020:i:c:s0167715220300560
    DOI: 10.1016/j.spl.2020.108753
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    References listed on IDEAS

    as
    1. Zhao, Shoujiang & Liu, Qiaojing & Chen, Ting, 2018. "On the large deviation principle for maximum likelihood estimator of α-Brownian bridge," Statistics & Probability Letters, Elsevier, vol. 138(C), pages 143-150.
    2. Bercu, Bernard & Richou, Adrien, 2017. "Large deviations for the Ornstein–Uhlenbeck process without tears," Statistics & Probability Letters, Elsevier, vol. 123(C), pages 45-55.
    Full references (including those not matched with items on IDEAS)

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