1052期 12月17日 :A Factor-Based Estimation of Integrated Covariance Matrix With Noisy High-Frequency Data(许文,助理教授,首都经贸大学)

时间:2019-12-12

【主题】 A Factor-Based Estimation of Integrated Covariance Matrix With Noisy High-Frequency Data
【报告人】许文(助理教授,首都经贸大学)
【时间】12月17日 星期二 15:30-17:00
【地点】 经济学院楼701室
【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.
返回原图
/