Template-type: ReDIF-Paper 1.0
Author-Name: David E. Allen
Author-Email: d.allen@ecu.edu.au
Author-Person: pal66
Author-Workplace-Name: School of Accounting, Finance and Economics Edith Cowan University, Australia.
Author-Name: Michael McAleer
Author-Person: pmc90 
Author-Workplace-Name: Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute,
	The Netherlands, Department of Quantitative Economics, Complutense University of Madrid, and Institute of
	Economic Research, Kyoto University. 
Author-Name: Robert J. Powell
Author-Workplace-Name: School of Accounting, Finance and Economics, Edith Cowan University
Author-Name: Abhay K. Singh
Author-Workplace-Name: School of Accounting, Finance and Economics, Edith Cowan University, Australia
Title: Multivariate Volatility Impulse Response Analysis 
 of GFC News Events 
Abstract: This paper applies the Hafner and Herwartz (2006) (hereafter HH) approach to the analysis of multivariate GARCH models using 
	volatility impulse response analysis. The data set features ten years of daily returns series for the New York Stock Exchange 
	Index and the FTSE 100 index from the London Stock Exchange, from 3 January 2005 to 31 January 2015. This period captures both 
	the Global Financial Crisis (GFC) and the subsequent European Sovereign Debt Crisis (ESDC). The attraction of the HH approach 
	is that it involves a novel application of the concept of impulse response functions, tracing the effects of independent shocks 
	on volatility through time, while avoiding typical orthogonalization and ordering problems. Volatility impulse response functions 
	(VIRF) provide information about the impact of independent shocks on volatility. HH’s VIRF extends a framework provided by Koop 
	et al. (1996) for the analysis of impulse responses. This approach is novel because it explores the effects of shocks to the 
	conditional variance, as opposed to the conditional mean. HH use the fact that GARCH models can be viewed as being linear in 
	the squares, and that multivariate GARCH models are known to have a VARMA representation with non-Gaussian errors. They use this 
	particular structure to calculate conditional expectations of volatility analytically in their VIRF analysis. A Jordan decomposition 
	of Σt is used to obtain independent and identically distributed innovations. A general issue in the approach is the choice of baseline 
	volatilities. VIRF is defined as the expectation of volatility conditional on an initial shock and on history, minus the baseline 
	expectation that conditions on history. This makes the process endogenous, but the choice of the baseline shock within the data 
	set makes a difference. We explore the impact of three different shocks, the first marking the onset of the GFC, which we date as 
	9 August 2007 (GFC1). This began with the seizure in the banking system precipitated by BNP Paribas announcing that it was ceasing 
	activity in three hedge funds that specialised in US mortgage debt. It took a year for the financial crisis to come to a head, but 
	it did so on 15 September 2008, when the US government allowed the investment bank Lehman Brothers to go bankrupt (GFC2). The third 
	shock is 9 May 2010, which marked the point at which the focus of concern switched from the private sector to the public sector. A 
	further contribution of this paper is the inclusion of leverage, or asymmetric effects. Our modelling is undertaken in the context 
	of a multivariate GARCH model featuring pre-whitened return series, which are then analysed using both BEKK and diagonal BEKK models 
	with the t-distribution. A key result is that the impact of negative shocks is larger, in terms of the effects on variances and 
	covariances, but shorter in duration, in this case a difference between three and six months, in the context of the return series.
Classification-JEL: C22, C32, C58, G32.
Keywords: Volatility impulse response functions (VIRF); BEKK; DBEKK; Asymmetry; GFC; ESDC.

Note: For financial support, the first author wishes to thank the Australian Research Council and the second author wishes to acknowledge 
	the Australian Research Council and the National Science Council, Taiwan. The authors are grateful to Tom Doan and Estima for helpful 
	assistance with RATS coding.
Length: 27 pages 
Creation-Date: 2015-07  
Number: 2015-10 
X-File-Ref: http://america.sim.ucm.es/repec/ucm/ref/doicae1510.txt
File-URL: https://eprints.ucm.es/id/eprint/33041/1/1510.pdf
File-Format: Application/pdf
Handle: RePEc:ucm:doicae:1510