Although the media is often modeled as a faceless institution, its main output news content is generated by specific people. This is important because unlike, say, making tires or processing paper, writing is a fiercely individualistic craft that allows the author’s style, persuasion, views, or bias to be injected into the finished product. In this paper, we present direct evidence that the writing of specific journalists has a casual effect on aggregate market outcomes.
This finding is surprising because, at any point in time, individual columnists are unlikely to possess information advantages relative to the market as a whole, let alone consistently over a period of several years. Thus, any persistent return predictability related to specific authors must arise from their “sentiment” or spin of public information. From 1970 to 2007, the short-term returns on the Dow Jones Industrial Average (DJIA) can be predicted knowing only the author of a widely read market summary article, the Wall Street Journal’s column entitled “Abreast of the Market” (AOTM).
Ordinarily we would be concerned about the endogenous nature of news coverage in a column summarizing market events. As Tetlock (2007) notes, “It is unclear whether the financial news media induces, amplifies, or simply reflects investors’ interpretations of stock market performance” (p.1139). Making a distinction between a reflective and a causal role for financial media thus requires exogenous variation in news content i.e., reporting uncorrelated with underlying events. In this regard, our setting is useful: what a journalist writes may be endogenous to market events, but which journalist writes is not. Columnists for the AOTM are assigned weeks in advance and appear to alternate based on quasi-regular schedules (e.g., every other Friday), such that their rotations bear no systematic relation to past or future market returns. These exogenous rotations imply that simple tests are sufficient for identification of a casual relationship between news’ content and market returns.
In our main tests, the dependent variable in a linear regression is the daily excess return on the DJIA Index. The control variables include several lags of returns, day of the week dummies, and lagged volume. Our interest is in the twenty-six vectors of journalist fixed effects, one for each financial columnist writing for the Wall Street Journal (WSJ) during our sample period. Given their apparently random assignment, we take these indicators as exogenous with respect to DJIA market returns.
