Fake News: Evidence from Financial Markets

Abstract

We examine fake news in financial markets, a laboratory that offers an opportunity to quantify its direct and indirect impact. We study three experimental settings. The first is a unique dataset of unambiguous fake articles on financial news platforms prosecuted by the Securities and Exchange Commission. The second applies a linguistic algorithm to detect deception in expression on the universe of articles on these platforms, using the first sample to validate and calibrate the algorithm. The third is an event study exploiting the SEC investigation as a public shock to investor awareness of fake news. We find that trading activity and price volatility rise with fake news about the firms mentioned in the articles. Following public revelation of the existence of fake news, we find an immediate decrease in reaction to all news, including legitimate news, on these platforms, consistent with indirect spillover effects of fake news conjectured by theory. These findings are predominant among small firms with high retail ownership, and are stronger for more circulated articles. Our results are consistent with economic theory on media bias and its application to fake news.