时间：2017年6月15日下午2:00

地点：浦东校区1号教学楼308室

题目：A rank test for the number of factors with high-frequency data

摘要：In the literature, consistency of the estimates of the number of factors for large dimensional factor models had been extensively studied recently. But the testing procedure has long been unsolved due to lack of limiting distribution of the estimates. In this paper, we propose a rank test of the number of factors using large panel high-frequency data contaminated with microstructure noise. The rank test is realized by forming a fixed number of portfolios which reduces a large panel dimension to a finite number. In the process of constructing portfolios, the number of factors underlying a large panel is inherited into the rank of volatility matrix of diversified portfolios. Via estimating the volatility rank of a low dimensional price dynamics of the portfolios, we establish a central limit theorem of the estimated factor number. We then apply the asymptotic normality to testing on the number of factors. Our test of the factor number are robust to the microstructure noise. Numerical experiments including the monte-carlo simulations and real data analysis justify our theory.

主讲人简介：

孔新兵现为南京审计大学教授，主要研究方向为高频数据统计，高维数据统计。迄今为止在统计学和计量经济学顶级期刊Annals of Statistics, JASA, Biometrika，Journal of Econometrics发表论文6篇，其中独立作者2篇。主持国家面上、青年项目，教育部人文社会科学项目等。2012年获复旦大学管理学院新星奖，2015年入选江苏省双创计划之双创博士，苏州市高层人才引进计划。2017年入选国际统计学会当选会员。现为中国现场统计研究会资源环境统计分会常务理事，高维统计分会理事。

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统计与数学学院

2017年6月7日