Title

Volatility dynamics of the US business cycle: A multivariate asymmetric GARCH approach

Document Type

Journal Article

Publisher

Elsevier BV

Faculty

Business and Law

School

Accounting, Finance and Economics

RAS ID

8213

Comments

Originally published as: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. Original article available here

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.

Article Location

 
COinS
 

Link to publisher version (DOI)

10.1016/j.matcom.2008.08.015