Jonathan Clarke,Hailiang Chen,Ding Du,Yu Jeffrey Hu
出处
期刊:Information Systems Research [Institute for Operations Research and the Management Sciences] 日期:2020-07-23卷期号:32 (1): 35-52被引量:126
标识
DOI:10.1287/isre.2019.0910
摘要
Does fake news in financial markets attract more investor attention and have a significant impact on stock prices? The authors use the SEC crackdown of stock promotion schemes in April 2017 to examine investor attention and the stock price reaction to fake news articles. Using data from Seeking Alpha, the authors find that fake news stories generate significantly more attention than a control sample of legitimate articles. The authors find no evidence that article commenters can detect fake news, and they find that Seeking Alpha editors have only modest ability to detect fake news. However, the authors implement several well-known machine learning algorithms based on linguistic characteristics and show that machine learning algorithms can successfully identify fake news. In addition, the stock market appears to price fake news correctly. While abnormal trading volume increases around the release of fake news, the increase is less than that observed for legitimate news. The stock price reaction to fake news is discounted when compared with legitimate news articles.