时间：2018年5月30日（星期三）10：30
地点：旗山校区理工北楼601报告厅
主讲：浙江大学 张荣茂副教授
主办：数学与信息学院、福建省分析数学及应用重点实验室
专家简介：张荣茂，博士，浙江大学数学系副教授，长期从事非线性、非平稳时间序列和空间数据分析的研究。发表近30篇SCI学术论文。International Journal of Mathematics and Statistics、Journal of the Korean Statistical Society副主编。
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 denite matrix. Our setting is model-free, and we allow the integer-valued integration orders of theobservable series to be unknown, and to possibly dier. Consistency of estimates of thecointegration space and cointegration rank is established both when the dimension of the observable time series is as sample size increases, and when it diverges slowly. The proposed methodology is also extended and justied in a fractional setting. A Monte Carlo study of nite-sample performance, and a small empirical illustration, are reported.