I find that approximately 30% of price fluctuations in the Fama-French size and value factors are nonfundamental price pressures driven by correlated fund flows, which generate price movements that revert over time. Is this really demand-based price pressure? I show that the price effects happen exclusively in periods when mutual funds place trades, a fact that is difficult to explain using traditional mechanisms such as unobserved investor preference changes. The estimated price elasticity is also consistent with other studies. Overall, my findings show that a sizable fraction of size and value factor movements do not represent economic risk.

Classical asset pricing models predict that optimizing investors exhibit extremely high demand elasticities, while empirical estimates are significantly lower—by three orders of magnitude. To reconcile this disparity, we introduce a novel decomposition of investor demand elasticity into two key components: “price pass-through”, which captures how price movements forecast returns, and “unspanned returns”, reflecting a stock’s lack of perfect substitutes. In a factor model framework, we show that unspanned returns become significant when models include “weak factors”. Classical models overestimate demand elasticity by assuming both very low unspanned returns and high price pass-throughs, assumptions that are inconsistent with empirical evidence.

We show that demand effects generated by institutional frictions can influence systematic return predictability patterns in stocks and mutual funds. Identification relies on a reform to the Morningstar rating system, which we show caused a structural break in style-level positive feedback trading by mutual funds. As a result, momentum-related factors in stocks, as well as performance persistence and the “dumb money effect” in mutual funds, experienced a sharp decline. Consistent with the proposed channel, return predictability declined right after the reform, was limited to the U.S. market, and was concentrated in factors and mutual funds most exposed to the mechanism.

We show that attention constraints on decision-makers create barriers to financial inclusion. Using administrative data on retail loan-screening processes, we find that attention-constrained loan officers exert less effort reviewing applicants of lower socioeconomic status (SES) and reject them more frequently. More importantly, when externally imposed increases in loan officers’ workloads tighten attention constraints, loan officers are even more prone to quickly reject low-SES applicants but quickly accept very high-SES applicants without careful review. Such selective attention allocation further widens the approval rate gap between high- and low-SES applicants—a unique prediction of this attention-based mechanism.