Multivariate linear and nonlinear causality tests

Zhidong Bai, Wing Keung WONG*, Bingzhi Zhang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

51 Citations (Scopus)

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
DOIs
Publication statusPublished - Sep 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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