讲座：Long-Range Dependent Curve Time Series
题 目：Long-Range Dependent Curve Time Series
演讲人： Degui Li , Reader in Statistics, University of York
主持人：张国雄 博士 上海交通大学安泰经济与管理学院经济系
时 间：2017年7月5日 (周三 ) 14:30-16:00
地 点： 上海交通大学 徐汇校区安泰经济与管理学院B1116室
We introduce methods and theory for functional time series with long-range dependence. The temporal sum of the curve process is shown to be asymptotically normally distributed. We show that the conditions for this cover a functional version of fractionally integrated autoregressive moving averages. We also construct an estimate of the long-run covariance function, which we use, via functional principal component analysis, in estimating the orthonormal functions spanning the dominant sub-space of the curves. In a more general, semiparametric context, we propose an estimate of the memory parameter, and derive its consistency result. A Monte-Carlo study of finite-sample performance is included, along with two empirical applications. The first of these finds a degree of stability and persistence in intra-day stock returns. The second finds similarity in the extent of long memory in age-specific fertility rates across some developed countries.
Professor Li is currently an Reader in Statistics at University of York in UK. His research area is time series econometrics. He obtained his Ph.D. degree in Statistics from Zhejiang University in 2008. He held research positions in University of Adelaide and Monash University before taking a Lecturer in Statistics position in University of York in 2013. His research has been published on top academic journals such as Journal of the American Statistical Association (*2), Annals of Statistics (*3), Journal of Econometrics (*6), Journal of Business and Economic Statistics(*2), among many others.