Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.matcom.2010.06.008
Title: Multivariate linear and nonlinear causality tests
Authors: Bai, Z. 
Wong, W.-K.
Zhang, B.
Keywords: Linear Granger causality
Nonlinear Granger causality
U-statistics
Issue Date: Sep-2010
Source: Bai, Z., Wong, W.-K., Zhang, B. (2010-09). Multivariate linear and nonlinear causality tests. Mathematics and Computers in Simulation 81 (1) : 5-17. ScholarBank@NUS Repository. https://doi.org/10.1016/j.matcom.2010.06.008
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. © 2010 IMACS.
Source Title: Mathematics and Computers in Simulation
URI: http://scholarbank.nus.edu.sg/handle/10635/105233
ISSN: 03784754
DOI: 10.1016/j.matcom.2010.06.008
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