Journal Article10.1093/RFS/HHG058
Extreme Value Dependence in Financial Markets: Diagnostics, Models, and Financial Implications
TL;DR: In this article, the authors present a general framework for identifying and modeling the joint-tail distribution based on multivariate extreme value theories, arguing that the multivariate approach is the most efficient and effective way to study extreme events such as systemic risk and crisis.
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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.
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Citations
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An examination of bank risk measures and their relationship to systemic risk measurement : a dissertation presented in partial fulfilment of the requirements for the degree of Doctoral of Philosophy in Finance at Massey University, Manawatu (Turitea), New Zealand
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