News Movers and Shakers in Finance

Besides more traditional quant factors including market capitalization and book-to-market, news availability or "liquidity" may be considered an important dimension when explaining portfolio excess returns.

Normally, news flow can be defined as a simple count of stories where for example a company is mentioned, while the idea of “news liquidity” is to capture “novel” and “actionable“ content about companies based on key events. Examples of company events include product recalls, lawsuits, analyst ratings, or bankruptcy announcements.

In a normal day, a company like "Apple Inc." will see a lot of media buzz impacting its news flow. In contrast, news liquidity would only get impacted if an actual company-specific event is disclosed e.g. "Steve Jobs resigns from his position as CEO". Basically, news liquidity refers to how much new and actionable information is available to investors.

While larger companies can be expected to receive greater media attention than smaller companies, even on a normal day, news flow and news liquidity may not be adequate measures to capture the likely stock price impact caused by public information. Instead, I propose measuring the “abnormal news liquidity” to capture changes in media attention from one period to the next, and more specifically companies that are moving in or out of the media spotlight. Interestingly, I find a 20% turnover per year in a ranking of the Top 100 and Top 1000 most news liquid companies in the US, indicating that companies do in fact move in and out of the media spotlight over time.

Without knowing whether the news about a company is good or bad, In my latest study, I consider abnormal news liquidity when trying to predict future price volatility (see Figure 5). Looking at the quantile distribution for news liquidity movers, ignoring whether the company is ranking up or down, I find that the more extreme a mover, the greater the price volatility in the following period. These results indicate that abnormal news liquidity could potentially be an attractive addition to a stochastic volatility model.



To form opinions about stock price direction, I introduce news sentiment to learn about whether a company is portrayed positively or negatively in the news. Not only do I find that sentiment can add value as part of a stock selection framework, but also that the price reaction patterns are different depending on whether the company is moving in or out of the media spotlight. Further details of my findings will be revealed in my next blog posting.