We use the 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)...

We use party-identifying language – like “Liberal Media” and “MAGA”– to identify Republican users on the investor social platform StockTwits. Using a difference-in-difference design, we find that the beliefs of partisan Republicans about equities remain relatively unfazed during the...

We find evidence of selective exposure to confirmatory information among 300,000 users on the investor social network StockTwits. Self-described bulls are 5 times more likely to follow a user with a bullish view of the same stock than self-described bears. This tendency exists even among...