The frequency with which a stock price is expected to respond to news is an important issue in securities litigation. Among the various tests employed to assess market efficiency in such cases, whether a stock, or other security, responds to news has emerged as the key consideration.

In many cases, the “FDT Test” (proposed by Paul A. Ferrillo, Frederick C. Dunbar, and David Tabak in 2004) has been used to examine stock-price movements on news days and on non-news days to see if they are statistically different. In particular, the FDT Test examines the frequency with which stock-price movements are above the threshold for statistical significance—a result that has often been considered in securities litigation to address whether investors should have been able to rely on the price of the stock to reflect public information.

This paper describes new empirical analyses that are intended to provide additional context around the results of FDT Tests, such as what percent of news days is empirically associated with a statistically significant stock-price movement.