报告题目：Adaptive testing for alphas in high-dimensional factor pricing models
报 告 人：夏强 教授
所在单位：华南农业大学
报告时间：2023年5月12日 星期五 13:30-14:30
报告地点：腾讯会议147655560
校内联系人：朱复康 zhufk@126.com
摘要：This paper proposes a new procedure to validate the multi-factor pricing theory by testing the presence of alpha in linear factor pricing models with a large number of assets. Because the market's inefficient pricing is likely to occur to a small fraction of exceptional assets, we develop a testing procedure that is particularly powerful against sparse signals. Based on the high-dimensional Gaussian approximation theory, we propose a simulation-based approach to approximate the limiting null distribution of the test. Our numerical studies show that the new procedure can deliver a reasonable size and achieve substantial power improvement compared to the existing tests under sparse alternatives, and especially for weak signals.
报告人简介：夏强，教授，博士生导师，现为华南农业大学数学与信息学院、软件学院副院长。主要从事时间序列分析和高维数据分析的研究，已经在Journal of Business & Economic Statistics、mBio、Statistica Sinica、Journal of Time Series Analysis、中国科学《数学》等国内外学术期刊上发表30余篇，出版专著2部。近年来主持国家自然科学基金重大研究计划培育项目，国家自然科学基金面上项目，国家社科基金青年项目各1项。目前担任美国数学评论评论员；广东省统计学会常务理事；广东省现场统计学会副理事长。
