IDEAS home Printed from https://ideas.repec.org/a/taf/emetrv/v36y2017i6-9p1039-1056.html
   My bibliography  Save this article

Distribution of the mean reversion estimator in the Ornstein–Uhlenbeck process

Author

Listed:
  • Yong Bao
  • Aman Ullah
  • Yun Wang

Abstract

We derive the exact distribution of the maximum likelihood estimator of the mean reversion parameter (κ) in the Ornstein–Uhlenbeck process using numerical integration through analytical evaluation of a joint characteristic function. Different scenarios are considered: known or unknown drift term, fixed or random start-up value, and zero or positive κ. Monte Carlo results demonstrate the remarkably reliable performance of our exact approach across all the scenarios. In comparison, misleading results may arise under the asymptotic distributions, including the advocated infill asymptotic distribution, which performs poorly in the tails when there is no intercept in the regression and the starting value of the process is nonzero.

Suggested Citation

  • Yong Bao & Aman Ullah & Yun Wang, 2017. "Distribution of the mean reversion estimator in the Ornstein–Uhlenbeck process," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 1039-1056, October.
  • Handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:1039-1056
    DOI: 10.1080/07474938.2017.1307977
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/07474938.2017.1307977
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/07474938.2017.1307977?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zi‐Yi Guo, 2021. "Out‐of‐sample performance of bias‐corrected estimators for diffusion processes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 243-268, March.
    2. Yong Bao & Xiaotian Liu & Aman Ullah, 2020. "On the Exact Statistical Distribution of Econometric Estimators and Test Statistics," Working Papers 202014, University of California at Riverside, Department of Economics, revised Jun 2020.
    3. Yiu Lim Lui & Weilin Xiao & Jun Yu, 2022. "The Grid Bootstrap for Continuous Time Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1390-1402, June.
    4. Emma M. Iglesias & Garry D. A. Phillips, 2020. "Further Results on Pseudo‐Maximum Likelihood Estimation and Testing in the Constant Elasticity of Variance Continuous Time Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(2), pages 357-364, March.
    5. Jianghao Chu & Tae-Hwy Lee & Aman Ullah & Haifeng Xu, 2020. "Exact Distribution of the F-statistic under Heteroskedasticity of Unknown Form for Improved Inference," Working Papers 202027, University of California at Riverside, Department of Economics.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:emetrv:v:36:y:2017:i:6-9:p:1039-1056. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: http://www.tandfonline.com/LECR20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.