Hedging short gamma exposure requires trading in the direction of price movements, thereby creating price momentum. Using intraday returns on over 60 futures on equities, bonds, commodities, and currencies between 1974 and 2020, we find strong market intraday momentum everywhere. The return during the last 30 minutes before the market close is positively predicted by the return during the rest of the day (from previous market close to the last 30 minutes). The predictive power is economically and statistically highly significant, and reverts over the next days. We provide novel evidence that links market intraday momentum to the gamma hedging demand from market participants such as market makers of options and leveraged ETFs.

Using novel data from a crowdsourcing platform for ranking stocks, we investigate how investors form expectations about stock returns over the next week. We find that investors extrapolate from stocks’ recent past returns, with more weight on more recent returns, especially when recent returns are negative, salient, or from a dispersed cross-section. Such extrapolative beliefs are stronger among nonprofessionals and large stocks. Moreover, consensus rankings negatively predict returns over the next week, more so among stocks with low institutional ownership and a high degree of extrapolation. A trading strategy that sorts stocks on investor beliefs generates an economically significant profit.

We study whether firm and macroeconomic announcements that convey systematic information generate a return premium for firms that experience information spillovers. We use information consumption to proxy for investor learning during these announcements and construct ex ante measures of expected information consumption (EIC) to calibrate whether learning is priced. On days when there are information spillovers, affected stocks earn a significant return premium (5% annualized) and the capital asset pricing model performs better. The positive effect of the Federal Reserve Open Market Committee announcements on the risk premia of individual stocks appears to be modulated by EIC. Our findings are most consistent with a risk‐based explanation.