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Extreme Value Dependence in Financial Markets: Diagnostics, Models, and Financial Implications

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  • Ser-Huang Poon
Abstract
This article presents a general framework for identifying and modeling the joint-tail distribution based on multivariate extreme value theories. We argue that the multivariate approach is the most efficient and effective way to study extreme events such as systemic risk and crisis. We show, using returns on five major stock indices, that the use of traditional dependence measures could lead to inaccurate portfolio risk assessment. We explain how the framework proposed here could be exploited in a number of finance applications such as portfolio selection, risk management, Sharpe ratio targeting, hedging, option valuation, and credit risk analysis. Copyright 2004, Oxford University Press.

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  • Ser-Huang Poon, 2004. "Extreme Value Dependence in Financial Markets: Diagnostics, Models, and Financial Implications," The Review of Financial Studies, Society for Financial Studies, vol. 17(2), pages 581-610.
    • Handle: RePEc:oup:rfinst:v:17:y:2004:i:2:p:581-610
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    File URL: http://hdl.handle.net/10.1093/rfs/hhg058
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