报告题目：Estimation of the Adjusted Standard-deviatile for Extreme Risks

报告所属学科：管理科学与工程

报告人：杨璠（加拿大滑铁卢大学）

报告时间：2022年12月23日 9:00-10:30

报告地点：腾讯会议：584-249-3538

报告摘要：

In this paper, we propose a new risk measure called the adjusted standard-deviatile by making adjustments to the variantile, which is the Bayes risk for the expectile. First, we derive the asymptotic expansions of the adjusted standard-deviatile. Next, based on the first-order asymptotic expansion, we propose two efficient estimation methods for the adjusted standard-deviatile at intermediate and extreme levels. By using techniques from extreme value theory, the asymptotic normality is proved for both estimators. Simulations and real data applications are conducted to examine the performance of the proposed estimators.

This is based on a joint work with Tiantian Mao and Haoyu Chen from the University of Science and Technology of China.

报告人简介：

现任加拿大滑铁卢大学统计与精算系助理教授。2008年本科毕业于西安交通大学信息与计算科学系。2013年博士毕业于美国爱荷华大学应用数学与计算科学专业。科研方向包含：精算，量化风险管理，极值理论，相依模型，以及风险度量。