IDEAS home Printed from https://ideas.repec.org/a/cuf/journl/y2001v2i1p123-164.html
   My bibliography  Save this article

Testing for Independence between Two stationary Time Series via the Empirical Characteristic Function

Author

Listed:
  • Yongmiao Hong

    (Department of Economics and Department of Statistical Science, Cornell University)

Abstract

This paper proposes an asymptotic one-sided N(0, 1) test for independence between two stationary time series using the empirical characteristic function. Unlike the tests based on the cross-correlation function (e.g. Haugh, 1976; Hong, 1996; Koch & Yang 1986), the proposed test has power against all pairwise cross-dependencies, including those with zero cross-correlation. By differentiating the empirical characteristic function at the origin, the present approach yields a modified version of Hong¡¯s (1996) test, which in turn generalizes Haugh¡¯s (1976) test. Other new tests can be derived by further differentiating the empirical characteristic function properly. A simulation study compares the new test with those of Haugh (1976), Hong (1996) and Koch & Yang (1986) in finite samples; the results show that the new test has reasonable sizes and good powers against linear and nonlinear cross-dependencies.

Suggested Citation

  • Yongmiao Hong, 2001. "Testing for Independence between Two stationary Time Series via the Empirical Characteristic Function," Annals of Economics and Finance, Society for AEF, vol. 2(1), pages 123-164, May.
    • Handle: RePEc:cuf:journl:y:2001:v:2:i:1:p:123-164
    as

    Download full text from publisher

    File URL: http://aeconf.com/Articles/May2001/aef020107.pdf
    Download Restriction: no
    File URL: http://down.aefweb.net/AefArticles/aef020107.pdf
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Guochang Wang & Wai Keung Li & Ke Zhu, 2018. "New HSIC-based tests for independence between two stationary multivariate time series," Papers 1804.09866, arXiv.org.
    2. Chu, Ba, 2023. "A distance-based test of independence between two multivariate time series," Journal of Multivariate Analysis, Elsevier, vol. 195(C).

    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:cuf:journl:y:2001:v:2:i:1:p:123-164. 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: Qiang Gao (email available below). General contact details of provider: https://edirc.repec.org/data/emcufcn.html .

    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.