The Neyman--Pearson Lemma for convex risk measures

报告时间:2021-12-02 14:00

报告地址:腾讯会议 410 805 593

主讲人:嵇少林

主讲人中文简介:

嵇少林教授现为山东大学金融研究院教授、博士生导师,山东大学金融研究院常务副院长。1971年12月生人,1999年获得博士学位,2011 年入选度教育部新世纪优秀人才支持计划,主持国家自然科学基金面上项目4项,研究领域为机器学习、金融数学、金融经济学、随机优化和非线性期望理论。

活动内容摘要:

We study the Neyman-Pearson theory for convex risk measures on L∞(μ). Without assuming that the level sets of penalty functions are weakly compact, a fixed representative pair (P∗,Q∗) is found by a new method different from the convex duality method. Then we show that the optimal tests are just the classical Neyman-Pearson tests between the representative probabilities P∗ and Q∗. Finally, we apply our results to a shortfall risk minimizing problem in an incomplete financial market.

主持人:张菁 闫理坦