报告题目：A General Family of Coherent Risk Measure in Finance
报 告 人：虞克明 英国布鲁内尔大学
报告时间：2025年7月15日（周二）下午15:30
报告地点：经管学院C301会议室
报告人简介：
虞克明（Keming Yu），英国伦敦布鲁内尔大学统计学与数据科学讲座教授 (Chair Professor)、布鲁内尔大学数学学科研究影响中心主任、统计与数据分析硕士研究生课程主任、英国皇家统计协会会士。虞克明教授已在 Journal of the American Statistical Association , Journal of the Royal Statistical Society , Journal of Econometrics , Journal of Business & Economics Statistics , Electronic Journal of Statistics , Statistica Sinica , Bernoulli , Journal of Multivariate Analysis , Journal of Time Series Analysis , Technometrics , Neurocomputing 等国际权威统计学期刊发表论文160余篇，其研究成果获得广泛引用（Google学术总引用量 10,190余次，H-index 36）。在美国斯坦福大学发布的全球前2%顶尖科学家排行榜（World's Top 2% Scientists）中，虞教授自该榜单2019年首次发布起，连续多年入选。虞教授还受邀担任 Journal of the American Statistical Association , A&CS , The Royal Statistical Society Series A , The Royal Statistical Society Series C , Statistical Science and Its Interface , Journal of Statistical Theory and Practice Review 等国际期刊的 Associate Editor。
报告内容简介：
This talk introduces the innovative concept of General Quantile Regression (GQR), which not only applies to regression models beyond the mean but also serves as a coherent risk measure. Many traditional regression models and risk measures can be viewed as special cases of GQR. As a flexible non-parametric regression model, GQR demonstrates outstanding performance in handling high-dimensional and large datasets, particularly those generated by distributed systems, offering a convenient framework for their statistical analysis. We derive the corresponding estimators and develop their asymptotic properties. Simulations and real data analyses are conducted to illustrate the finite-sample performance of the proposed methods.
