Hedging the black swan: conditional heteroskedasticity and tail dependence in S&P500 and VIX

Hedging the black swan: conditional heteroskedasticity and tail dependence in S&P500 and VIX
Document type
Working Paper
Author(s)
Abbas, Sawsan; Poon, Ser-Huang; Tawn, Jonathan
Publisher
Manchester Business School
Date of publication
30 July 2009
Series
University of Manchester Business School Working Papers. No. 591
Subject(s)
Trends: economic, social and technology trends affecting business
Collection
Business and management
Material type
Reports

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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.

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