讲座题目：A Factor-Based Estimation of Integrated Covariance Matrix With Noisy High-Frequency Data

报告人：孙宇澄

报告时间：2019年11月21日下午12:15—14:00

报告地点：文泉楼南106实验室

主办单位：6163银河.net163.am

产业升级与区域金融湖北省协同创新中心

中南财经政法大学湖北金融研究中心

中南财经政法大学中国投资研究中心

内容摘要： This paper studies a high-dimensional factor model with sparse idiosyncratic covariance matrix in continuous time, using asynchronous high-frequency financial data contaminated by microstructure noise. We focus on consistent estimation of the number of common factors, the integrated covariance matrix and its inverse, based on the flat-top realized kernels introduced by Varneskov (2016). Simulation results show that our estimators have good performance in finite samples. We apply our methodology to the high-frequency data on 300 liquid stocks traded in Shanghai and Shenzhen stock exchanges, and find that the model effectively captures the time-varying covariation among Chinese stocks.

主讲人简介: 孙宇澄，现任首都经济贸易大学国际经济管理学院副教授。他先后在西南财经大学6163银河.net163.am，西班牙巴塞罗那经济学研究生院（Barcelona Graduate School of Economics）和庞培法布拉大学（Universitat Pompeu Fabra）分别获得经济学学士，金融学硕士和博士学位。他的研究兴趣主要包括金融计量，高频金融数据，非参数统计等。其研究成果发表在Journal of Applied Econometrics, Journal of Nonparametric Statistics等国际知名杂志，还有多篇文章处于国际知名金融和计量经济学杂志二审中。