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Parameter estimation for Cox–Ingersoll–Ross process with two-sided reflections

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  • Shi, Yiwei
  • Shu, Huisheng
  • Wang, Chunyang
  • Zhang, Xuekang

Abstract

In this paper, the least squares estimator (LSE) for the Cox–Ingersoll–Ross process with two-sided reflections is investigated on the basis of continuous observations. The strong consistency and asymptotic normality of LSE are derived. Computer simulations and empirical analysis are performed to illustrate our theory. Moreover, we also express the regulators using local time process.

Suggested Citation

  • Shi, Yiwei & Shu, Huisheng & Wang, Chunyang & Zhang, Xuekang, 2025. "Parameter estimation for Cox–Ingersoll–Ross process with two-sided reflections," Statistics & Probability Letters, Elsevier, vol. 221(C).
  • Handle: RePEc:eee:stapro:v:221:y:2025:i:c:s0167715224003213
    DOI: 10.1016/j.spl.2024.110352
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    References listed on IDEAS

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    1. Zhang, Xuekang & Yi, Haoran & Shu, Huisheng, 2020. "Parameter estimation for non-stationary reflected Ornstein–Uhlenbeck processes driven by α-stable noises," Statistics & Probability Letters, Elsevier, vol. 156(C).
    2. Qingpei Zang & Lixin Zhang, 2019. "Asymptotic Behaviour of the Trajectory Fitting Estimator for Reflected Ornstein–Uhlenbeck Processes," Journal of Theoretical Probability, Springer, vol. 32(1), pages 183-201, March.
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    6. Liu Chang & Shouting Chen & Ailin Zhu, 2015. "Properties of the Cox–Ingersoll–Ross Interest Rate Processes with Two-sided Reflections," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 44(4), pages 657-670, February.
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    9. Yaozhong Hu & Chihoon Lee & Myung Lee & Jian Song, 2015. "Parameter estimation for reflected Ornstein–Uhlenbeck processes with discrete observations," Statistical Inference for Stochastic Processes, Springer, vol. 18(3), pages 279-291, October.
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    Cited by:

    1. Yuliya Mishura & Andrey Pilipenko & Kostiantyn Ralchenko, 2025. "Gatheral double stochastic volatility model with Skorokhod reflection," Papers 2505.09184, arXiv.org.

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