统计与数据科学系系列学术报告之四百二十二期

时   间： 2024年3月19日（周二）16:00-17:00

地   点：史带楼502室

主持人：复旦大学 管理学院 统计与数据科学系 蒋斐宇 青年副研究员

报告人：王迪 副教授  上海交通大学 数学科学学院

题   目：Vector and matrix autoregressive model with common response and predictor factors

摘   要：The reduced-rank vector autoregressive (VAR) model can be interpreted as a supervised factor model, where two factor modelings are simultaneously applied to response and predictor spaces. This talk introduces a new model, called vector autoregression with common response and predictor factors, to explore further the common structure between the response and predictors in the VAR framework. The new model can provide better physical interpretations and improve estimation efficiency. In conjunction with the tensor operation, the model can easily be extended to any finite-order VAR model. A regularization-based method is considered for the high-dimensional estimation with the gradient descent algorithm, and its computational and statistical convergence guarantees are established. Furthermore, the model and methodology are extended to the matrix autoregressive model. Simulation experiments confirm our theoretical findings and macroeconomic applications showcase the appealing properties of the proposed model in structural analysis and forecasting.

个人简介：王迪，于2020年在香港大学获得统计学博士学位，毕业后在美国芝加哥大学商学院任职博士后研究员，于2022年7月加入上海交通大学数学科学学院，任职长聘教轨副教授。主要研究领域是时间序列分析和高维数据统计推断，在统计学和计量经济顶级期刊Journal of the American Statistical Association, Annals of Statistics, Journal of Econometrics等发表论文多篇。目前主持国自然青年项目和上海市科委启明星项目。

统计与数据科学系

2024-3-11