IDEAS home Printed from https://ideas.repec.org/a/taf/emetrv/v37y2018i10p1051-1066.html
   My bibliography  Save this article

The estimation for Lévy processes in high frequency data

Author

Listed:
  • Jing Zheng
  • Wentao Gu
  • Baolin Xu
  • Zongwu Cai

Abstract

In this article, a generalized Lévy model is proposed and its parameters are estimated in high-frequency data settings. An infinitesimal generator of Lévy processes is used to study the asymptotic properties of the drift and volatility estimators. They are consistent asymptotically and are independent of other parameters making them better than those in Chen et al. (2010). The estimators proposed here also have fast convergence rates and are simple to implement.

Suggested Citation

  • Jing Zheng & Wentao Gu & Baolin Xu & Zongwu Cai, 2018. "The estimation for Lévy processes in high frequency data," Econometric Reviews, Taylor & Francis Journals, vol. 37(10), pages 1051-1066, November.
    • Handle: RePEc:taf:emetrv:v:37:y:2018:i:10:p:1051-1066
    DOI: 10.1080/07474938.2016.1188876
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/07474938.2016.1188876
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/07474938.2016.1188876?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. Gu, Wentao & Peng, Yiqing, 2019. "Forecasting the market return direction based on a time-varying probability density model," Technological Forecasting and Social Change, Elsevier, vol. 148(C).

    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:37:y:2018:i:10:p:1051-1066. 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.