Price revelation from insider trading: Evidence from hacked earnings news

• 成果类型: Article
• 署名作者: Akey, Pat; Gregoire, Vincent; Martineau, Charles
• 署名单位: University of Toronto; Universite de Montreal; HEC Montreal
• 刊物名称: JOURNAL OF FINANCIAL ECONOMICS
• ISSN/ISSBN: 0304-405X
• DOI: 10.1016/j.jfineco.2021.12.006
• 发表日期: 2022
• 页码: 1162-1184
• 关键词: Cyber risks; earnings announcements; Hard and soft information; Informed trading; liquidity; Machine Learning; Market microstructure; Price discovery

摘要

A B S T R A C T From 2010 to 2015, a group of traders illegally accessed earnings information before their public release by hacking several newswire services. We use this scheme as a natural experiment to investigate how informed investors select among private signals and how efficiently financial markets incorporate private information contained in trades into prices. We construct a measure of qualitative information using machine learning and find that the hackers traded on both qualitative and quantitative signals. The hackers' trading caused 15% more of the earnings news to be incorporated in prices before their public release. Liquidity providers responded to the hackers' trades by widening spreads. (c) 2021 Elsevier B.V. All rights reserved.