报告题目：Testing for Spurious Factor Analysis on High Dimensional Nonstationary Time Series
内容摘要：Spurious factor behaviors arise in large random matrices with high-rank random signal components and heavy-tailed spectral distributions. This paper establishes analytical probabilistic limits and a distribution theory for these spurious behaviors in high-dimensional non-stationary time series. We transform scree plots into Hill plots to detect spectral patterns in these spurious factor models and develop max-t tests to distinguish between spurious and genuine factor models. Simulations confirm the excellent size and power performance of our test in finite samples. Applying the tests to three real-life datasets, we detected spurious factors in both economic and climate data, and genuine factors in finance data.
主讲人简介：Yi He is an Associate Professor in the Quantitative Economic Section at the University of Amsterdam. He earned his master’s degree from the University of Cambridge and his PhD from Tilburg University in 2016. Prior to returning to the Netherlands, he served as a tenured Assistant Professor in the Department of Econometrics and Business Statistics at Monash University in Australia. His research focuses on high-dimensional econometrics, random matrix theory, extreme value statistics, bootstrapping, and machine learning. His work has been featured in prestigious journals, including the Journal of the American Statistical Association, The Annals of Statistics, Journal of the Royal Statistical Society - Series B, Journal of Business & Economic Statistics, and Journal of Econometrics. Yi's breakthroughs in extreme value statistics have earned him a nomination for the 2025 Van Dantzig Award in Statistics and Operations Research in the Netherlands. His current research explores dense time series models with complex network interactions in high-dimensional econometrics.
报告时间：2024年10月15日(周二)，16:30-18:00
线下地点：厦门大学经济楼N302
线上地点：腾讯会议 ID：894 124 194
