报告题目：Identifying Cointegration by Eigenanalysis
报告人：姚琦伟 教授
报告时间：2019年7月4日15:30—16:30，
报告地点：理学院212会议室
报告摘要：We propose a new and easy-to-use method for identifying cointegrated components of nonstationary time series, consisting of an eigenanalysis for a certain non-negative definite matrix. Our setting is model-free, and we allow the integer-valued integration orders of the observable series to be unknown, and to possibly differ. Consistency of estimates of the cointegration space and cointegration rank is established both when the dimension of the observable time series is fixed as sample size increases, and when it diverges slowly. The proposed methodology is also extended and justified in a fractional setting. A Monte Carlo study of finite-sample performance, and a small empirical illustration, are reported.
姚琦伟教授简介：英国伦敦经济与政治科学学院(London School of Economics and Political Sciences)统计系教授（2006 -2009 期间任系主任），北京大学光华管理学院特聘教授，英国皇家统计学会会士，美国统计协会会士，数理统计学会会士，国际统计研究学会选举会员。