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Disentangling the causal impact of media reporting from the impact of the events being reported is challenging. We solve this problem by comparing the behaviors of investors with access to different media coverage of the same information event. We use zip codes to identify 19 mutually exclusive trading regions corresponding with large U.S. cities. For all earnings announcements of S&P 500 Index firms, we find that local media coverage strongly predicts local trading, after controlling for earnings, investor, and newspaper characteristics. Moreover, local trading is strongly related to the timing of local reporting, a particular challenge to nonmedia explanations.

We propose a new and direct measure of investor attention using search frequency in Google (Search Volume Index (SVI)). In a sample of Russell 3000 stocks from 2004 to 2008, we find that SVI (1) is correlated with but different from existing proxies of investor attention; (2) captures investor attention in a more timely fashion and (3) likely measures the attention of retail investors. An increase in SVI predicts higher stock prices in the next 2 weeks and an eventual price reversal within the year. It also contributes to the large first-day return and long-run underperformance of IPO stocks.

Short sellers face unique risks, such as the risk that stock loans become expensive and the risk that stock loans are recalled. We show that short-selling risk affects prices among the cross-section of stocks. Stocks with more short-selling risk have lower returns, less price efficiency, and less short selling.

We use the popular television show Mad Money , hosted by Jim Cramer, to test theories of attention and limits to arbitrage. Stock recommendations on Mad Money constitute attention shocks to a large audience of individual traders. We find that stock recommendations lead to large overnight returns that subsequently reverse over the next few months. The spike-reversal pattern is strongest among small, illiquid stocks that are hard to arbitrage. Using daily Nielsen ratings as a direct measure of attention, we find that the overnight return is strongest when high-income viewership is high. We also find weak price effects among sell recommendations. Taken together, the evidence supports the retail attention hypothesis of Barber and Odean (Barber, B., T. Odean. 2008. All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors. Rev. Financial Stud. 21 (2) 785-818) and illustrates the potential role of media in generating mispricing. This paper was accepted by Brad Barber, Teck Ho, and Terrance Odean, special issue editors.

We use data from the Survey of Professional Forecasters (SPF) to compare point predictions of gross domestic product (GDP) growth and inflation with the subjective probability distributions held by forecasters. We find that most SPF point predictions are quite close to the central tendencies of forecasters subjective distributions tend to be asymmetric, with SPF forecasters tending to report point predictions that give a more favorable view of the economy than do their subjective means/medians/modes.

We use daily Internet search volume from millions of households to reveal market-level sentiment. By aggregating the volume of queries related to household concerns (e.g., \"recession,\" \"unemployment,\" and \"bankruptcy\"), we construct a Financial and Economic Attitudes Revealed by Search (FEARS) index as a new measure of investor sentiment. Between 2004 and 2011, we find FEARS (i) predict short-term return reversals, (ii) predict temporary increases in volatility, and (iii) predict mutual fund flows out of equity funds and into bond funds. Taken together, the results are broadly consistent with theories of investor sentiment.

Using a sample of 97 stock return anomalies, we find that anomaly returns are 50% higher on corporate news days and six times higher on earnings announcement days. These results could be explained by dynamic risk, mispricing due to biased expectations, or data mining. We develop and conduct several unique tests to differentiate between these three explanations. Our results are most consistent with the idea that anomaly returns are driven by biased expectations, which are at least partly corrected upon news arrival.

CEOs with large networks earn more than those with small networks. An additional connection to an executive or director outside the firm increases compensation by about $17,000 on average, more so for \"important\" members, such as CEOs of big firms. Pay-for-connectivity is unrelated to several measures of corporate governance, evidence in favor of an efficient contracting explanation for CEO pay.

Using individual patient records for every hospital in California from 1983 to 2011, we find a strong inverse link between daily stock returns and hospital admissions, particularly for psychological conditions such as anxiety, panic disorder, and major depression. The effect is nearly instantaneous (within the same day) for psychological conditions, suggesting that anticipation over future consumption directly influences instantaneous utility.

We use exogenous scheduling of Wall Street Journal columnists to identify a causal relation between financial reporting and stock market performance. To measure the media's unconditional effect, we add columnist fixed effects to a daily regression of excess Dow Jones Industrial Average returns. Relative to standard control variables, these fixed effects increase the R² by about 35%, indicating each columnist's average persistent \"bullishness\" or \"bearishness.\" To measure the media's conditional effect, we interact columnist fixed effects with lagged returns. This increases explanatory power by yet another one-third, and identifies amplification or attenuation of prevailing sentiment as a tool used by financial journalists.