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LAN property for an ergodic Ornstein–Uhlenbeck process with Poisson jumps

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  • Ngoc Khue Tran

Abstract

In this article, we consider an ergodic Ornstein–Uhlenbeck process with jumps driven by a Brownian motion and a compensated Poisson process, whose drift and diffusion coefficients as well as its jump intensity depend on unknown parameters. Considering the process discretely observed at high frequency, we derive the local asymptotic normality property. To obtain this result, Malliavin calculus and Girsanov’s theorem are applied to write the log-likelihood ratio in terms of sums of conditional expectations, for which a central limit theorem for triangular arrays can be applied.

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  • Ngoc Khue Tran, 2017. "LAN property for an ergodic Ornstein–Uhlenbeck process with Poisson jumps," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(16), pages 7942-7968, August.
  • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:16:p:7942-7968
    DOI: 10.1080/03610926.2016.1167908
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    Cited by:

    1. Jakobsen, Nina Munkholt & Sørensen, Michael, 2019. "Estimating functions for jump–diffusions," Stochastic Processes and their Applications, Elsevier, vol. 129(9), pages 3282-3318.
    2. Mohamed Ben Alaya & Ahmed Kebaier & Ngoc Khue Tran, 2020. "Local asymptotic properties for Cox‐Ingersoll‐Ross process with discrete observations," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(4), pages 1401-1464, December.
    3. Kevin W. Lu, 2022. "Calibration for multivariate Lévy-driven Ornstein-Uhlenbeck processes with applications to weak subordination," Statistical Inference for Stochastic Processes, Springer, vol. 25(2), pages 365-396, July.
    4. Alexander Gushchin & Ilya Pavlyukevich & Marian Ritsch, 2020. "Drift estimation for a Lévy-driven Ornstein–Uhlenbeck process with heavy tails," Statistical Inference for Stochastic Processes, Springer, vol. 23(3), pages 553-570, October.

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