Poor financial health of intermediaries coincides with low asset prices and high risk premiums. Is this because intermediaries matter for asset prices, or because their health correlates with economy‐wide risk aversion? In the first case, return predictability should be more pronounced for asset classes in which households are less active. We provide evidence supporting this prediction, suggesting that a quantitatively sizable fraction of risk premium variation in several large asset classes such as credit or mortgage‐backed securities (MBS) is due to intermediaries. Movements in economy‐wide risk aversion create the opposite pattern, and we find this channel also matters.

Managed portfolios that take less risk when volatility is high produce large alphas, increase Sharpe ratios, and produce large utility gains for mean‐variance investors. We document this for the market, value, momentum, profitability, return on equity, investment, and betting‐against‐beta factors, as well as the currency carry trade. Volatility timing increases Sharpe ratios because changes in volatility are not offset by proportional changes in expected returns. Our strategy is contrary to conventional wisdom because it takes relatively less risk in recessions. This rules out typical risk‐based explanations and is a challenge to structural models of time‐varying expected returns.

We provide evidence that agents have slow‐moving beliefs about stock market volatility that lead to initial underreaction to volatility shocks followed by delayed overreaction. These dynamics are mirrored in the VIX and variance risk premiums, which reflect investor expectations about volatility, and are also supported in both surveys and firm‐level option prices. We embed these expectations into an asset pricing model and find that the model can account for a number of stylized facts about market returns and return volatility that are difficult to reconcile, including a weak or even negative risk‐return trade‐off.

We analyze the behavior of credit and output in financial crises using data on credit spreads and credit growth. Crises are marked by a sharp rise in credit spreads, signaling sudden shifts in expectations. The severity of a crisis can be predicted by the extent of credit losses (spread increases) and financial sector fragility (precrisis credit growth). This interaction is a key feature of crises. Postcrisis recessions are typically severe and prolonged. Notably, precrisis spreads tend to drop to low levels while credit growth accelerates, indicating that credit supply expansions often precede crises. The 2008 crisis aligns with these patterns.

Financial intermediaries trade frequently in many markets using sophisticated models. Their marginal value of wealth should therefore provide a more informative stochastic discount factor (SDF) than that of a representative consumer. Guided by theory, we use shocks to the leverage of securities broker‐dealers to construct an intermediary SDF. Intuitively, deteriorating funding conditions are associated with deleveraging and high marginal value of wealth. Our single ‐factor model prices size, book‐to‐market, momentum, and bond portfolios with an R 2 of 77% and an average annual pricing error of 1%—performing as well as standard multifactor benchmarks designed to price these assets.