Extreme Value Dependence in Financial Markets: Diagnostics, Models, and Financial Implications
基于多元极值理论，提出识别和建模联合尾部分布的通用框架，并用五大股指数据说明传统依赖测度会导致投资组合风险评估不准确，该框架可用于投资组合选择、风险管理、对冲等金融应用。
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.