A Note on Causality Tests

Zhidong Bai; Wing Keung Wong; Bingzhi Zhang

doi:10.6148/IJITAS.2010.0302.06

A Note on Causality Tests

Zhidong Bai, Wing Keung Wong, Bingzhi Zhang

Research output: Contribution to journal › Journal article › peer-review

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 (1994) develop a nonlinear Granger causality test in a bivariate setting to investigate the nonlinear causality between stock prices and trading volume. In this paper, we first discuss linear causality tests in multivariate settings and thereafter develop a non-linear causality test in multivariate settings.

Original language	English
Pages (from-to)	203-220
Number of pages	18
Journal	International Journal of Intelligent Technologies and Applied Statistics
Volume	3
Issue number	2
DOIs	https://doi.org/10.6148/IJITAS.2010.0302.06
Publication status	Published - Jun 2010

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title = "A Note on Causality Tests",

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 (1994) develop a nonlinear Granger causality test in a bivariate setting to investigate the nonlinear causality between stock prices and trading volume. In this paper, we first discuss linear causality tests in multivariate settings and thereafter develop a non-linear causality test in multivariate settings.",

author = "Zhidong Bai and Wong, {Wing Keung} and Bingzhi Zhang",

note = "This research is partially supported by Northeast Normal University, the National University of Singapore, Hong Kong Baptist University, and Columbia University. JEL Classification: C01, C12, G10 ",

year = "2010",

month = jun,

doi = "10.6148/IJITAS.2010.0302.06",

language = "English",

volume = "3",

pages = "203--220",

journal = "International Journal of Intelligent Technologies and Applied Statistics",

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AU - Bai, Zhidong

AU - Wong, Wing Keung

AU - Zhang, Bingzhi

N1 - This research is partially supported by Northeast Normal University, the National University of Singapore, Hong Kong Baptist University, and Columbia University. JEL Classification: C01, C12, G10

PY - 2010/6

Y1 - 2010/6

N2 - 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 (1994) develop a nonlinear Granger causality test in a bivariate setting to investigate the nonlinear causality between stock prices and trading volume. In this paper, we first discuss linear causality tests in multivariate settings and thereafter develop a non-linear causality test in multivariate settings.

AB - 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 (1994) develop a nonlinear Granger causality test in a bivariate setting to investigate the nonlinear causality between stock prices and trading volume. In this paper, we first discuss linear causality tests in multivariate settings and thereafter develop a non-linear causality test in multivariate settings.

U2 - 10.6148/IJITAS.2010.0302.06

DO - 10.6148/IJITAS.2010.0302.06

M3 - Journal article

SN - 1998-5010

VL - 3

SP - 203

EP - 220

JO - International Journal of Intelligent Technologies and Applied Statistics

JF - International Journal of Intelligent Technologies and Applied Statistics

IS - 2

ER -

A Note on Causality Tests

Abstract

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