Hedging the Black Swan: Conditional Heteroskedasticity and Tail Dependence in S&P500 and Vix

36 Pages Posted: 7 Feb 2010

See all articles by Sawsan Abbas

Sawsan Abbas

University of Bahrain

Ser-Huang Poon

University of Manchester - Manchester Business School

Jonathan Tawn

Lancaster University - Mathematics and Statistics

Date Written: July 30, 2009

Abstract

The recent financial crisis has accentuated the fact that extreme outcomes have been overlooked and not dealt with adequately. While extreme value theories have existed for a long time, the multivariate variant is difficult to handle in the financial markets due to the prevalent heteroskedasticity embedded in most financial time series, and the complex extremal dependence that cannot be conveniently captured by a single structure. Moreover, most of the existing approaches are based on a limiting argument in which all variables become large at the same rate. In this paper, we show how the conditional approach of Heffernan and Tawn (2004) can be implemented to model extremal dependence between financial time series. A hedging example based on VIX futures is used to demonstrate its flexibility and superiority against the conventional OLS regression approach.

Keywords: Financial Time Series, Extreme Value Theory, Extremal Dependence Structure, Downside Risk, Optimal Hedge Ratio

JEL Classification: G01, G11, G17, C46, C14, C22

Suggested Citation

Abbas, Sawsan and Poon, Ser-Huang and Tawn, Jonathan, Hedging the Black Swan: Conditional Heteroskedasticity and Tail Dependence in S&P500 and Vix (July 30, 2009). Available at SSRN: https://ssrn.com/abstract=1549164 or http://dx.doi.org/10.2139/ssrn.1549164

Sawsan Abbas

University of Bahrain ( email )

P.O Box 32038
Sukhair Campus, 32038
Bahrain

Ser-Huang Poon (Contact Author)

University of Manchester - Manchester Business School ( email )

Crawford House
Oxford Road
Manchester, Manchester M13 9PL
United Kingdom
+44 161 275 4031 (Phone)
+44 161 275 4023 (Fax)

HOME PAGE: http://www.manchester.ac.uk/research/Ser-huang.poon/

Jonathan Tawn

Lancaster University - Mathematics and Statistics ( email )

Department of Mathematics and Statistics
Lancaster University
Lancaster, LA1 4YF
United Kingdom
+44 1524 59 3965 (Phone)
+44 1524 59 2681 (Fax)

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