Multivariate linear and nonlinear causality tests

Authors:
Zhidong Bai;Wing-Keung Wong;Bingzhi Zhang
Affiliations:
School of Mathematics and Statistics, Northeast Normal University, China and Department of Statistics and Applied Probability, 3 National University of Singapore, Singapore;Department of Economics and Institute for Computational Mathematics, Hong Kong Baptist University, Hong Kong, China;Department of BioStatistics, Columbia University, United States
Venue:
Mathematics and Computers in Simulation
Year:
2010

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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.