Innovations in textual analysis help investors identify the relevance and content of firm-level public news. When relevant news can be identified, stock prices tend to be closely linked to the arrival of this information. For instance, variance ratios of returns on identified-news days can be more than double those on no-news and unidentified-news days.
What Is the Investment Issue?
Standard models in finance suggest that asset prices should reflect both public and private information. Prior researchers have concluded that the revelation of private information through trading, rather than public news, is the main driver of stock prices. The authors demonstrate that firm-level public news can actually be a meaningful component of stock return variance.
How Did the Authors Conduct This Research?
The authors use textual analysis and news stories to identify relevant public information linked to specific firm events.
The authors limit their research to S&P 500 companies with at least 20 trading days during the period—that is, 896 companies. Data from all documents that passed through Dow Jones Newswire between 2000 and 2015 are used.
Open–close news is defined as news arriving during trading hours; close–open news is defined as news arriving outside of trading hours. The authors then isolate the portion of return variance resulting solely from the arrival of firm-level event news. They apply the methodology to overnight and trading hours, conditional on different types of information (such as unidentified or no news, identified news, complex news, and specific events) and compare the results from this decomposition. The authors further decompose the contribution of news to overall return variance into the intensity of news arrival and the impact of news conditional on news arrival.
What Are the Findings and Implications for Investors and Investment Professionals?
The authors find that such public information accounts for 49.6% of overnight idiosyncratic volatility compared with 12.4% during trading hours. They also note that higher noise trading (proxied by a lower fraction of news variance contribution) is associated with higher expected returns. Moreover, they document a large negative correlation over time (–0.5) between average idiosyncratic volatility during overnight hours and the contribution of identified news to overnight return volatility.
“The bottom line of the paper is that, when relevant news can be identified, stock price movements are closely linked to the arrival of this information.”
The authors moreover differentiate between market-wide and idiosyncratic volatility. Even though only 27% (22%) of news days are complex news days during overnight (trading) hours, 32.4% (6.1%) of all the idiosyncratic variance can be explained by such news. The variance contributions from all news days are higher for firms that have higher trading volume—that is, 57.0% overnight and 14.15% during trading hours. Moreover, finance-related events tend to have the most important effect on volatility. Less common information, such as ratings news of the company or financing, can also have an important effect on stock prices.