2019年4月22日上午，应广州大学经济与统计学院和岭南统计科学研究中心的邀请，在行政东前座412会议室，香港大学朱柯教授作了题为“Testing and modelling for the structural change in matrix time series”的学术报告——暨“羊城讲坛”第五十四讲，旨在进一步提高年轻学者及研究生对相关研究的理解。此次讲座由崔霞教授主持，相关专业的师生参加了此次讲座。

 

朱柯教授是香港大学统计与精算系的助理教授、博士生导师，于2011年获得香港科技大学统计学博士学位。主要研究方向为时间序列计量经济和统计，包括稳健统计、拟合优度检验、变点问题、bootstrap方法及应用计量经济。目前，他已经发表学术论文20余篇，其中包括Journal of the American Statistical Association, Annals of  Statistics, Journal of the Royal Statistical Society Series B, Journal of Econometrics, Econometric Theory ,Journal of Business and Economic Statistics等国际顶尖统计和计量经济学期刊。

 

 

本次讲座的主要内容是：Matrix time series are frequently observed in many applications, while no formal study has been given to test and model for their structural changes. This paper first constructs a new generalized Hausman test for detecting the structural change in a multiplicative form of matrix time series model. This generalized Hausman test is asymptotically pivotal, and it has nontrivial power to detect a broad class of abrupt and smooth change alternatives. Moreover, this paper proposes a new semiparametric matrix time series model, which has a time varying long run component to take the structural change into account, and a BEKK type short run component to capture the temporal dependence. A two-step estimation procedure is given to estimate this semiparametric model, and the asymptotics of the related estimators are established. Finally, the importance of the generalized Hausman test and the semiparametric model is illustrated by simulations and an application to realized covariance matrix data.