Faculty of Business Administration
New HSIC-based tests for independence between two stationary multivariate time series
Prof. Guochang Wang
College of Economics
Jinan University, Guangzhou
This paper proposes some novel one-sided omnibus tests for independence between two multivariate stationary time series. These new tests apply the Hilbert-Schmidt independence criterion (HSIC) to test the independence between the innovations of both time series. Under regular conditions, the limiting null distributions of our HSIC-based tests are established. Next, our HSIC-based tests are shown to be consistent. Moreover, a residual bootstrap method is used to obtain the critical values for our HSIC-based tests, and its validity is justified. Compared with the existing cross-correlation-based tests for linear dependence, our tests examine the general (including both linear and non-linear) dependence to give investigators more complete information on the causal relationship between two multivariate time series. The merits of our tests are illustrated by some simulation results and a real example.
Date: 19 Dec 2019 (Thu)
Prof. Guochang Wang is currently associate professor in College of Economics at Jinan University . He received his Bachelor degree in School of Mathematics and Statistics from Northeast Normal University in 2006, and his Ph.D. in School of Mathematics and Statistics from Northeast Normal University in 2012, respectively. His recent research interests include Functional data analysis, High-dimensional Statistics, and Time series. His publications appear on a wide variety of journals such as Journal of Econometrics, Statistica Sinica, Scandinavian Journal of Statistics,Statistics in Medicine, etc.
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