学术报告

题      目：Testing Alpha in High Dimensional Linear Factor Pricing Models with Dependent Observations

报  告  人：冯龙  副教授  (邀请人：吴琴 )

                                    南开大学

时      间：5月12日  15：00-16：00

地     点：数学科学学院西楼二楼会议室

报告人简介:

        冯龙现任南开大学统计与数据科学学院副教授、特聘研究员、博士生导师。入选教育部青年人才计划、南开大学百名青年学科带头人。曾获得教育部学术新人奖，南开大学优秀博士论文奖。主要从事高维数据分析方面的研究，在统计学国际顶尖杂志JRSSB, JASA、Biometrika、Annals of Statistics、JOE、JBES等发表40余篇论文。主持一项天津市杰出青年基金、国家自然科学基金面上项目和青年项目。

摘      要：

       In this study, we introduce three distinct testing methods for testing alpha in high dimensional linear factor pricing model that deals with dependent data. The first method is a sum-type test procedure, which exhibits high performance when dealing with dense alternatives. The second method is a max-type test procedure, which is particularly effective for sparse alternatives. For a broader range of alternatives, we suggest a Cauchy combination test procedure. This is predicated on the asymptotic independence of the sum-type and max-type test statistics. Both simulation studies and practical data application demonstrate the effectiveness of our proposed methods when handling dependent observations.

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