主讲人：陈亮助理教授（北京大学汇丰商学院）

主持人：张岸洲助理教授（辽宁大学李安民经济研究院）

嘉宾介绍：毛明海助理教授（辽宁大学李安民经济研究院）

时间：2023年3月24日（周五）  14：00-15：30（北京时间）

地点：辽宁大学崇山校区五洲园一楼会议室

线上地址：腾讯会议：300 7551 6895

语言：中文/英文

摘要：

This paper studies the estimation of characteristic-based quantile factor models where the factor loadings are unknown functions of observed individual characteristics while the idiosyncratic error terms are subject to conditional quantile restrictions. We propose a three stage estimation procedure that is easily implementable in practice and has nice properties. The convergence rates, the limiting distributions of the estimated factors and loading functions, and a consistent selection criterion for the number of factors at each quantile are derived under general conditions. The proposed estimation methodology is shown to work satisfactorily when: (i) the idiosyncratic errors have heavy tails, (ii) the time dimension of the panel dataset is not large, and (iii) the number of factors exceeds the number of characteristics. Finite sample simulations and an empirical application aimed at estimating the loading functions of the daily returns of a large panel of S&P500 index securities help illustrate these properties. 

主讲人简介：陈亮，北京大学汇丰商学院助理教授，西班牙马德里卡洛斯三世大学经济学博士，主要研究领域为计量经济学理论、应用计量经济学，曾在Econometrica, Journal of Econometrics, Econometric Theory, The Econometrics Journal, Economic Letters等国际一流期刊发表论文多篇。