Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.matcom.2008.08.015
Title: Volatility dynamics of the US business cycle: A multivariate asymmetric GARCH approach
Authors: Ho, K.-Y.
Tsui, A.K. 
Zhang, Z.
Keywords: Constant correlations
Index of industrial production
Multivariate asymmetric GARCH
US business cycle non-linearities
Varying-correlations
Issue Date: 2009
Source: Ho, K.-Y., Tsui, A.K., Zhang, Z. (2009). Volatility dynamics of the US business cycle: A multivariate asymmetric GARCH approach. Mathematics and Computers in Simulation 79 (9) : 2856-2868. ScholarBank@NUS Repository. https://doi.org/10.1016/j.matcom.2008.08.015
Abstract: Most empirical investigations of the business cycles in the United States have excluded the dimension of asymmetric conditional volatility. This paper analyses the volatility dynamics of the US business cycle by comparing the performance of various multivariate generalised autoregressive conditional heteroskedasticity (GARCH) models. In particular, we propose two bivariate GARCH models to examine the evidence of volatility asymmetry and time-varying correlations concurrently, and then apply the proposed models to five sectors of Industrial Production of the United States. Our findings provide strong evidence of asymmetric conditional volatility in all sectors, and some support of time-varying correlations in various sectoral pairs. This has important policy implications for government to consider the effective countercyclical measures during recessions. © 2008 IMACS.
Source Title: Mathematics and Computers in Simulation
URI: http://scholarbank.nus.edu.sg/handle/10635/22333
ISSN: 03784754
DOI: 10.1016/j.matcom.2008.08.015
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