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计量、金融与大数据分析Workshop：Uniform Inference for High-Frequency Data
发布日期：2024-04-19 10:29 来源：
题目：Uniform Inference for High-Frequency Data
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：Qiyuan Li, Singapore Management University
主持人：（国发院）黄卓、张俊妮、孙振庭
（北大新结构经济学研究院）胡博
（经济学院）王一鸣、王熙、刘蕴霆、王法
时间：2024年4月19日（周五）10:00 AM -- 11:30 AM
地点：经济学院107
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.
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首页
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计量、金融与大数据分析Workshop：Uniform Inference for High-Frequency Data
发布日期：2024-04-19 10:29 来源：
题目：Uniform Inference for High-Frequency Data
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：Qiyuan Li, Singapore Management University
主持人：（国发院）黄卓、张俊妮、孙振庭
（北大新结构经济学研究院）胡博
（经济学院）王一鸣、王熙、刘蕴霆、王法
时间：2024年4月19日（周五）10:00 AM -- 11:30 AM
地点：经济学院107
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.
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