Multivariate linear and nonlinear causality tests

Zhidong Bai, Wing-Keung Wong*, Bingzhi Zhang

*Corresponding author for this work

    Research output: Contribution to journalJournal articlepeer-review

    78 Citations (Scopus)
    120 Downloads (Pure)

    Abstract

    The traditional linear Granger test has been widely used to examine the linear causality among several time series in bivariate settings as well as multivariate settings. Hiemstra and Jones [19] develop a nonlinear Granger causality test in bivariate settings to investigate the nonlinear causality between stock prices and trading volume. This paper extends their work by developing a nonlinear causality test in multivariate settings.

    Original languageEnglish
    Pages (from-to)5-17
    Number of pages13
    JournalMathematics and Computers in Simulation
    Volume81
    Issue number1
    Early online date13 Jul 2010
    DOIs
    Publication statusPublished - Sept 2010

    Scopus Subject Areas

    • Theoretical Computer Science
    • Computer Science(all)
    • Numerical Analysis
    • Modelling and Simulation
    • Applied Mathematics

    User-Defined Keywords

    • Linear Granger causality
    • Nonlinear Granger causality
    • U-statistics

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