报告题目： Estimation of high-dimensional factor models with multiple structural changes

报告摘要：This study considers a high-dimensional factor model with an unknown number of breaks. A simple two-step procedure is proposed for determining the number of breaks and identifying the break dates. The estimator of the number of breaks is consistent and the distance between the estimated and actual break dates is stochastically bounded under certain mild conditions. Monte Carlo simulations demonstrate that the proposed method has the desired performance in finite samples. Two real data are analyzed for illustrations. Overall, the proposed method is expected to be less complex to determine the number of breaks in the underlying factor model.

报告人简介： 吴鑑洪，上海师范大学统计学教授，博士生导师，统计教研室主任、博士点学位负责人，主要从事经济金融时间序列分析、面板数据分析、高维因子分析等大数据计量经济学研究工作，浙江省中青年学科带头人，浙江省新世纪151人才工程第二层次培养人员。先后在《Journal of Econometrics》等国内外重要期刊发表论文40余篇，担任国内多个统计研究学会的常务理事和理事。

报告时间： 2022/12/07（星期三） 09:30-10:30 (GMT+08:00)

报告地点：腾讯会议：111-466-164，

链接：https://meeting.tencent.com/dm/Ay2QNnP6rfxR

主办单位：统计与数据科学学院