依赖建模中的优控问题
On Majorization in Dependence Modeling
摘要：
我们应用优化理论的概念，在极值依赖结构领域获得新的见解。特别是，我们认为Puccetti和Rueschendorf的重排算法，其中优参数产生一个声明，统一和扩展现有的理论在两个方面。第一个扩展考虑非线性风险聚集的凸函数，第二个扩展考虑非对称费用函数。文章最后通过算例进行了分析。
英文摘要：
We apply concepts of majorization theory to derive new insights in the field of extremal dependence structures. In particular, we consider the Rearrangement Algorithm by Puccetti and Rueschendorf, where majorization arguments yield a statement that unifies and extends the existing theory in two ways. The first extension considers convex functions of non-linear risk aggregation and the second allows for non-symmetric cost functions. The article is concluded by computing an example.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
