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: Abhay K. Singh
Author-Workplace-Name: School of Accounting, Finance and Economics, Edith Cowan University
Title: Risk Measurement and risk modelling using applications of Vine Copulas
Abstract: This paper features an application of Regular Vine copulas which are a novel and recently developed 
	statistical and mathematical tool which can be applied in the assessment of composite financial risk. 
	Copula-based dependence modelling is a popular tool in financial applications, but is usually applied 
	to pairs of securities. By contrast, Vine copulas provide greater flexibility and permit the modelling 
	of complex dependency patterns using the rich variety of bivariate copulas which may be arranged and 
	analysed in a tree structure to explore multiple dependencies. The paper features the use of Regular Vine 
	copulas in an analysis of the co-dependencies of 10 major European Stock Markets, as represented by 
	individual market indices and the composite STOXX 50 index. The sample runs from 2005 to the end of 2011 
	to permit an exploration of how correlations change indiferent economic circumstances using three diferent 
	sample periods: pre-GFC pre-GFC (Jan 2005- July 2007), GFC (July 2007-Sep 2009), and post-GFC periods 
	(Sep 2009 - Dec 2011). The empirical results suggest that the dependencies change in a complex manner, 
	and are subject to change in diferent economic circumstances. One of the attractions of this approach 
	to risk modelling is the flexibility in the choice of distributions used to model co-dependencies. The 
	practical application of Regular Vine metrics is demonstrated via an example of the calculation of the 
	VaR of a portfolio made up of the indices.
Keywords: Regular Vine Copulas; Tree structures; Co-dependence modelling; European stock markets.
Classification-JEL: G11, C02.
Length: 29 pages
Creation-Date: 2014-05-06 
Number: 2014-09 
X-File-Ref: http://america.sim.ucm.es/repec/ucm/ref/doicae1409.txt
File-URL: https://eprints.ucm.es/id/eprint/25298/1/1409.pdf
File-Format: Application/pdf
Handle: RePEc:ucm:doicae:1409