Template-type: ReDIF-Paper 1.0
Author-Name: D.E. Allen
Author-Email: d.allen@ecu.edu.au
Author-Person: pal66 
Author-Workplace-Name: School of Accounting Finance and Economics Edith Cowan University Joondalup Drive Joondalup Western Australia 6027 
Author-Name: A. Kramadibrata
Author-Workplace-Name: School of Accounting Finance and Economics Edith Cowan University Joondalup Drive Joondalup Western Australia 6027 
Author-Name: Michael McAleer
Author-Person: pmc90 
Author-Workplace-Name: Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam.
Author-Name: R. Powell
Author-Email: r.powell@unsw.edu.au 
Author-Person: ppo357 
Author-Workplace-Name: School of Accounting Finance and Economics Edith Cowan University Joondalup Drive Joondalup Western Australia 6027 
Author-Name: A. K. Singh
Author-Workplace-Name: School of Accounting Finance and Economics Edith Cowan University Joondalup Drive Joondalup Western Australia 6027 
Title: A non-parametric and entropy based analysis of the relationship between the VIX and S&P500
Abstract: This paper features an analysis of the relationship between the S&P500 Index and the VIX using
	daily data obtained from both the CBOE website and SIRCA (The Securities Industry Research
	Centre of the Asia Pacific). We explore the relationship between the S&P500 daily continuously
	compounded return series and a similar series for the VIX in terms of a long sample drawn from the
	CBOE running from 1990 to mid 2011 and a set of returns from SIRCA's TRTH datasets running
	from March 2005 to-date. We divide this shorter sample, which captures the behaviour of the new
	VIX, introduced in 2003, into four roughly equivalent sub-samples which permit the exploration of
	the impact of the Global Financial Crisis. We apply to our data sets a series of non-parametric
	based tests utilising entropy based metrics. These suggest that the PDFs and CDFs of these two
	return distributions change shape in various subsample periods. The entropy and MI statistics
	suggest that the degree of uncertainty attached to these distributions changes through time and
	using the S&P500 return as the dependent variable, that the amount of information obtained from
	the VIX also changes with time and reaches a relative maximum in the most recent period from
	2011 to 2012. The entropy based non-parametric tests of the equivalence of the two distributions
	and their symmetry all strongly reject their respective nulls. The results suggest that parametric
	techniques do not adequately capture the complexities displayed in the behaviour of these series.
	This has practical implications for hedging utilising derivatives written on the VIX, which will be
	the focus of a subsequent study.
Keywords: S&P500, VIX, Entropy, Non-Parametric Estimation, Quantile Regressions.
Length: 19 pages 
Creation-Date: 2012-05 
Number: 2012-19 
X-File-Ref: http://america.sim.ucm.es/repec/ucm/ref/doicae1219.txt
File-URL: https://eprints.ucm.es/id/eprint/16222/1/1219.pdf
File-Format: Application/pdf
Handle: RePEc:ucm:doicae:1219