演讲人： 任玥璇（新加坡管理大学）

时间：2024年12月24日（周二）12:00-13:00

地点：同济大厦A楼505室

同步#腾讯会议：952710081

会议密码：676496

链接：https://meeting.tencent.com/dm/MNA27j8OfnvD

摘要：We propose using a conformal predictive analysis for high-frequency event studies. Unlike existing literature, we recast the inference problem of cumulative abnormal return (CAR) as a counterfactual prediction problem for cumulative return. The general continuous-time model for spot regression can be approximated by a linear regression model with independent and stable-distributed random variables under the fixed-$k$ asymptotic setting, thereby establishing the asymptotic validity of the conformal prediction interval. Extending the theory to incorporate a counterfactual model with many control units, the proposed prediction interval remains valid when using the synthetic control estimator. An intraday event study of AMD’s conference session illustrates the empirical application.

个人简介： Yuexuan Ren is a job market candidate from Singapore Management University. Her research interest is econometrics theory with a specialization in financial econometrics. She holds a master’s degree in Statistics from Renmin University of China and a bachelor’s degree in Economics from Shandong University.