Please use this identifier to cite or link to this item:
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
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.
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
ISSN: 03784754
DOI: 10.1016/j.matcom.2008.08.015
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.


checked on Feb 28, 2018


checked on Feb 19, 2018

Page view(s)

checked on Mar 12, 2018

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.