事件(粒子物理)
贝叶斯概率
事件研究
证券欺诈
计算机科学
计量经济学
精算学
业务
经济
人工智能
政治学
历史
法学
物理
背景(考古学)
最高法院
考古
量子力学
作者
Jonah B. Gelbach,Jenny R. Hawkins
出处
期刊:JITE
[Mohr Siebeck Verlag]
日期:2020-01-01
卷期号:176 (1): 86-86
标识
DOI:10.1628/jite-2020-0012
摘要
We propose a Bayesian method for econometric event studies commonly usedin U.S. securities litigation. We show that our approach may be based on the Bayes factor, which has a simple form when inference is based on the empirical distribution function of abnormal returns; it also avoids problems related to nonnormality of abnormal returns. We use data from litigation related to alleged fraud by the Apollo Education Group (University of Phoenix's parent) to illustrate the method. Results are similar to frequentist hypothesis testing with a large event-date effect, but they can be importantly different with a small or moderate effect.
科研通智能强力驱动
Strongly Powered by AbleSci AI