学术讲座【Identifying Cointegration by Eigenanalysis】
时间：2018年5月30日(星期三)上午10:30 -11:30
地点：旗山校区理工北楼601报告厅
主办：数学与信息学院、福建省分析数学及应用重点实验室
主讲：浙江大学，张荣茂教授
参加对象：相关研究生及教师
专家简介：张荣茂博士现为浙江大学数学系教授，统计研究所副所长。长期从事非线性、非平稳时间序列和空间数据分析的研究。已在国际统计和经济学杂志“Annals of Statistics”、“Journal of the American Statistical Association”、“Econometric Theory”、“Stochastic Processes and their Applications”等发表近30 篇论文。现担任“International Journal of Mathematics and Statistics”和“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 the
observable series to be unknown, and to possibly dier. Consistency of estimates of the
cointegration 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.