Subsampling the distribution of diverging statistics with applications to finance

Patrice Bertail, Christian Haefke, Dimitris N. Politis, Halbert White

    Research output: Contribution to journalArticle

    Abstract

    In this paper we propose a subsampling estimator for the distribution of statistics diverging at either known or unknown rates when the underlying time series is strictly stationary and strong mixing. Based on our results we provide a detailed discussion of how to estimate extreme order statistics with dependent data and present two applications to assessing financial market risk. Our method performs well in estimating Value at Risk and provides a superior alternative to Hill's estimator in operationalizing Safety First portfolio selection.

    Original languageEnglish (US)
    Pages (from-to)295-326
    Number of pages32
    JournalJournal of Econometrics
    Volume120
    Issue number2
    DOIs
    StatePublished - Jun 1 2004

    Fingerprint

    Hill Estimator
    Extreme Order Statistics
    Strong Mixing
    Subsampling
    Value at Risk
    Portfolio Selection
    Dependent Data
    Finance
    Financial Markets
    Strictly
    Time series
    Safety
    Statistics
    Estimator
    Unknown
    Alternatives
    Estimate
    Safety-first
    Market risk
    Order statistics

    Keywords

    • Extreme value statistics
    • Portfolio selection
    • Resampling methods
    • Value at Risk

    ASJC Scopus subject areas

    • Economics and Econometrics
    • Applied Mathematics
    • History and Philosophy of Science

    Cite this

    Subsampling the distribution of diverging statistics with applications to finance. / Bertail, Patrice; Haefke, Christian; Politis, Dimitris N.; White, Halbert.

    In: Journal of Econometrics, Vol. 120, No. 2, 01.06.2004, p. 295-326.

    Research output: Contribution to journalArticle

    Bertail, Patrice ; Haefke, Christian ; Politis, Dimitris N. ; White, Halbert. / Subsampling the distribution of diverging statistics with applications to finance. In: Journal of Econometrics. 2004 ; Vol. 120, No. 2. pp. 295-326.
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