Examining the trades of company insiders, I find that a sale of stock at a loss is a much more negative signal about future returns than is a sale of stock at a gain. I consider a range of explanations for my results and find that the evidence is most consistent with the idea that investors derive direct disutility from selling a stock at a loss. Since selling a stock at a loss is painful, an investor who sells at a loss must have particularly negative information. This result offers a novel measurement of the strength of the disposition effect. Received December 7, 2015; editorial decision December 18, 2017 by Editor Robin Greenwood. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

A growing body of evidence suggests that Federal Open Market Committee (FOMC) announcements can affect private sector beliefs about near-term macroeconomic conditions. We measure the impact of central bank policy on index option trader beliefs about near-term economic conditions using the return of short-term dividend strips around each FOMC announcement (we term this short-term dividend strip return, “SDR”). Consistent with the idea that these announcements contain valuable information about macroeconomic conditions, we find that SDR predicts both future firm-level earnings and firm-level earnings announcement returns. Furthermore, using analyst earnings forecasts, we provide evidence of belief underreaction to FOMC announcements. We discuss how investor specialization and segmented markets can generate our empirical results.

Abstract We find evidence that investors value dividends differently depending on their level of trust. Our tests indicate that investor demand for dividend-paying stocks increases as trust decreases, and that this relationship affects market values. We begin with survey evidence showing that people think accounting fraud is less likely among dividend payers and that people with low trust are more likely to hold dividend-paying stocks. We then empirically exploit accounting fraud discoveries within a mutual fund’s portfolio as a shock to trust. In response to these shocks, we show that mutual funds tilt their portfolios toward dividend-paying stocks. This result is not explained by a shift in risk preferences, indicating that these institutional investors are seeking dividends in particular rather than stable firms that just happen to pay dividends. Finally, we provide evidence that dividend payers experience a premium in their market values relative to non-payers when their investor base becomes less trusting.

Abstract Existing research finds that investors’ returns vary with their wealth and level of sophistication. We bring a new perspective from the supply side by showing that return heterogeneity can be magnified as assets offered by the market become more complex. Using detailed account-level data, we examine the trading of B funds—complex, structured products in the Chinese market. During a 3-year market cycle, the return gap between the naive and sophisticated is an order-of-magnitude greater when trading B funds than when trading simple, non-structured funds. In an event study, we confirm that this disparity is driven by differences in investors’ understanding of product complexity.

Abstract We label the degree to which individuals are more optimistic at long horizons relative to short horizons as the horizon bias. We examine whether time-series variation in the horizon bias can explain the time-series variation in the equity term structure. We use analyst earnings forecasts to measure the degree of the horizon bias in the stock market. Consistent with the intuition from a stylized present value model, we find that periods of above-average horizon bias are associated with negative term premiums, whereas periods of below-average horizon bias are associated with positive term premiums. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.