英文标题：
《Tails of weakly dependent random vectors》
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作者：
Peter Tankov
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最新提交年份：
2016
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英文摘要：
We introduce a new functional measure of tail dependence for weakly dependent (asymptotically independent) random vectors, termed weak tail dependence function. The new measure is defined at the level of copulas and we compute it for several copula families such as the Gaussian copula, copulas of a class of Gaussian mixture models, certain Archimedean copulas and extreme value copulas. The new measure allows to quantify the tail behavior of certain functionals of weakly dependent random vectors at the log scale.
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中文摘要：
对于弱相关（渐近独立）随机向量，我们引入了一种新的尾相关函数测度，称为弱尾相关函数。新的度量是在copula的层次上定义的，我们计算了几个copula族，例如高斯copula、一类高斯混合模型的copula、某些阿基米德copula和极值copula。新的度量允许在对数尺度上量化弱相关随机向量的某些泛函的尾部行为。
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分类信息：

一级分类：Mathematics 数学
二级分类：Probability 概率
分类描述：Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
概率论与随机过程的理论与应用：例如中心极限定理，大偏差，随机微分方程，统计力学模型，排队论
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一级分类：Quantitative Finance 数量金融学
二级分类：Risk Management 风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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