TY - JOUR

T1 - Extreme Value Dependence in Financial Markets: Diagnostics, Models, and Financial Implications.

AU - Poon, Ser-Huang;

AU - Rockinger, Michael;

AU - Tawn, Jonathan

PY - 2004

Y1 - 2004

N2 - 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.

AB - 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.

U2 - 10.1093/rfs/hhg058

DO - 10.1093/rfs/hhg058

M3 - Journal article

VL - 17

SP - 581

EP - 610

JO - Review of Financial Studies

JF - Review of Financial Studies

SN - 1465-7368

IS - 2

ER -