英文标题：
《Bounds for randomly shared risk of heavy-tailed loss factors》
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作者：
Oliver Kley and Claudia Kluppelberg
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最新提交年份：
2016
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英文摘要：
For a risk vector $V$, whose components are shared among agents by some random mechanism, we obtain asymptotic lower and upper bounds for the individual agents\' exposure risk and the aggregated risk in the market. Risk is measured by Value-at-Risk or Conditional Tail Expectation. We assume Pareto tails for the components of $V$ and arbitrary dependence structure in a multivariate regular variation setting. Upper and lower bounds are given by asymptotically independent and fully dependent components of $V$ with respect to the tail index $\\alpha$ being smaller or larger than 1. Counterexamples, where for non-linear aggregation functions no bounds are available, complete the picture.
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中文摘要：
对于一个风险向量$V$，其组成部分通过某种随机机制在代理之间共享，我们得到了单个代理的暴露风险和市场中总风险的渐近上下界。风险由风险价值或条件尾部预期来衡量。我们假设$V$的成分为帕累托尾，并且在多元规则变化环境中具有任意依赖结构。上界和下界由$V$的渐近独立和完全依赖分量给出，尾指数$\\alpha$小于或大于1。反例，对于非线性聚合函数，没有可用的边界，请完成图片。
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分类信息：

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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