学术沙龙主题:Linear regression estimation using intraday high frequency data

报告人:张兴发 广州大学经济与统计学院统计系主任

邀请人：李本崇

报告时间:2023年10月25日(周三)；上午9:00—10:30

报告地点：腾讯会议：607 681 071

报告人简介：张兴发，博士毕业于香港理工大学应用数学系，现为广州大学经济与统计学院副教授，硕士生导师，统计系主任。兼任中国现场统计研究会理事、资源与环境统计分会秘书长、广东省现场统计学会副理事长。研究兴趣为时间序列分析。完成国家自然科学基金项目一项，在研广东省、广州市自然科学基金各一项，省市级教改项目各一项，在《Journal of Econometrics》、《SCIENCE CHINA Mathematics》、《Statistics and its interface》、《Quality and Reliability Engineering International》等期刊发表科研论文30余篇。

报告摘要:Intraday high frequency data have shown important values in econometric modeling and have been extensively studied in recent years. Following this point, in this paper, we study the linear regression model for variables which have intraday high frequency data. To overcome the nonstationarity of the intraday data, intraday sequences are aggregated to the daily series by weighted mean. A lower bound for the trace of the asymptotic variance of model estimator is given, and a data-driven method for choosing the weight is also proposed, with the aim to obtain a smaller sum of asymptotic variance for parameter estimators. Simulation and empirical studies show that using intraday high frequency data can significantly improve the estimation accuracy of the regression coefficient. The results of this paper may have potential applications to the models where aggregation of high frequency data are needed.