Uniform Inference for High-Frequency Data

主讲人：Qiyuan Li, Singapore Management University

主持老师：（北大经济学院）王熙

参与老师：  （北大经院）王一鸣、王法、刘蕴霆

（北大国发院）黄卓、张俊妮、孙振庭

（北大新结构）胡博

时间：2024年4月19日（周五） 10:00-11:30

地点（线下）： 北京大学经济学院107会议室

报告摘要：

We address the uniform inference problem for high-frequency data that includes prices, volumes, and trading flows. Such data is modeled with a general state-space framework, where latent state process is the corresponding risk indicators, e.g., volatility, price jump, average order size, and arrival of events. The functional estimators are formed as the collection of localized estimates across different time points. Although the proposed estimators do not admit a functional central limit theorem, a Gaussian strong approximation, or coupling, is established under in-fill asymptotics to facilitate feasible inference. We apply the proposed methodology to distinguish the informative part from the Federal Open Market Committee speeches, and to analyze the impact of social media activities on cryptocurrency markets.

主讲人简介：

Dr Qiyuan Li is interested in the fields of econometric theory, with a specialization in financial econometrics. He has published papers in Journal of Econometrics, Oxford Bulletin of Economics and Statistics, and Quantitative Economics.