Template-type: ReDIF-Paper 1.0
Author-Name: Manabu Asai
Author-Email: m-asai@soka.ac.jp
Author-Workplace-Name: Faculty of Economics Soka University, Japan.
Author-Name: Michael McAleer
Author-Workplace-Name:
 Department of Quantitative Finance National Tsing Hua University, Taiwan and Econometric Institute, Erasmus 
	School of Economics Erasmus University Rotterdam and Tinbergen Institute, The Netherlands and Department of Quantitative 
	Economics Complutense University of Madrid, Spain.
Title: Asymptotic Theory for Extended Asymmetric Multivariate GARCH Processes
Abstract: The paper considers various extended asymmetric multivariate conditional volatility models, and derives appropriate 
	regularity conditions and associated asymptotic theory. This enables checking of internal consistency and allows valid 
	statistical inferences to be drawn based on empirical estimation. For this purpose, we use an underlying vector random 
	coefficient autoregressive process, for which we show the equivalent representation for the asymmetric multivariate 
	conditional volatility model, to derive asymptotic theory for the quasi-maximum likelihood estimator. As an extension, we 
	develop a new multivariate asymmetric long memory volatility model, and discuss the associated asymptotic properties.
Classification-JEL: C13, C32, C58.
Keywords: Multivariate conditional volatility, Vector random coefficient autoregressive process, Asymmetry, Long memory, Dynamic 
	conditional correlations, Regularity conditions, Asymptotic properties.
Length: 23 pages 
Creation-Date: 2016-09
Number: 2016-14
X-File-Ref: http://america.sim.ucm.es/repec/ucm/ref/doicae1614.txt
File-URL: https://eprints.ucm.es/id/eprint/39131/1/1614.pdf
File-Format: Application/pdf
Handle: RePEc:ucm:doicae:1614