BIROn - Birkbeck Institutional Research Online

    Using the Bootstrap to test for symmetry under unknown dependence

    Psaradakis, Zacharias (2015) Using the Bootstrap to test for symmetry under unknown dependence. Journal of Business and Economic Statistics 34 (3), pp. 406-415. ISSN 0735-0015.

    jbes_2015.pdf - Author's Accepted Manuscript

    Download (304kB) | Preview


    This paper considers tests for symmetry of the one-dimensional marginal distribution of fractionally integrated processes. The tests are implemented by using an autoregressive sieve bootstrap approximation to the null sampling distribution of the relevant test statistics. The sieve bootstrap allows inference on symmetry to be carried out without knowledge of either the memory parameter of the data or of the appropriate norming factor for the test statistic and its asymptotic distribution. The small-sample properties of the proposed method are examined by means of Monte Carlo experiments, and applications to real-world data are also presented.


    Item Type: Article
    Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis, available online:
    School: Birkbeck Faculties and Schools > Faculty of Business and Law > Birkbeck Business School
    Depositing User: Zacharias Psaradakis
    Date Deposited: 27 Nov 2015 13:45
    Last Modified: 02 Aug 2023 17:17


    Activity Overview
    6 month trend
    6 month trend

    Additional statistics are available via IRStats2.

    Archive Staff Only (login required)

    Edit/View Item Edit/View Item