Individual investors who hold common stocks directly pay a tremendous performance penalty for active trading. Of 66,465 households with accounts at a large discount broker during 1991 to 1996, those that trade most earn an annual return of 11.4 percent, while the market returns 17.9 percent. The average household earns an annual return of 16.4 percent, tilts its common stock investment toward high‐beta, small, value stocks, and turns over 75 percent of its portfolio annually. Overconfidence can explain high trading levels and the resulting poor performance of individual investors. Our central message is that trading is hazardous to your wealth.

Retail order imbalance positively predicts returns, but on average retail investor trades lose money. Why? Order imbalance tests equal-weighted stocks, but retail purchases concentrate on attention-grabbing stocks that subsequently underperform. Long–short strategies based on extreme quintiles of retail order imbalance earn dismal annualized returns of −14.8% among stocks with heavy retail trading but earn 6.6% among other stocks. Our results reconcile the literatures on the performance of retail investors, the predictive content of retail order imbalance, and attention-induced trading and returns. Smaller retail trades concentrate more on attention-grabbing stocks and perform worse.

When assessing a fund manager's skill, sophisticated investors will consider all factors (priced and unpriced) that explain cross-sectional variation in fund performance. We investigate which factors investors attend to by analyzing mutual fund flows as a function of recent returns decomposed into alpha and factor-related returns. Surprisingly, investors attend most to market risk (beta) when evaluating funds and treat returns attributable to size, value, momentum, and industry factors as alpha. Using proxies for investor sophistication (wealth, distribution channels, and periods of high investor sentiment), we find that more sophisticated investors use more sophisticated benchmarks when evaluating fund performance.

Based on a survey of American Finance Association members, we analyze how demographics, time allocation, production mechanisms, and institutional factors affect research production during the pandemic. Consistent with the literature, research productivity falls more for women and faculty with young children. Independently, and novel, extra time spent on teaching (much more likely for women) negatively affects research productivity. Also novel, concerns about feedback, isolation, and health have large negative research effects, which disproportionately affect junior faculty and PhD students. Finally, faculty who express greater concerns about employers’ finances report larger negative research effects and more concerns about feedback, isolation, and health.

We placed 85,000 retail trades in six retail brokerage accounts from December 2021 to June 2022 to validate the Boehmer et al. algorithm, which uses subpenny trade prices to identify and sign retail trades. The algorithm identifies 35% of our trades as retail, incorrectly signs 28% of identified trades, and yields uninformative order imbalance measures for 30% of stocks. We modify the algorithm by signing trades using the quoted spread midpoints. The quote midpoint method does not affect identification rates but reduces the signing error rates to 5% and provides informative order imbalance measures for all stocks.