I analyze the behavior of risk premia in financial crises, wars, and recessions in an international panel spanning over 140 years and 14 countries. I document that expected returns, or risk premia, increase substantially in financial crises, but not in the other episodes. Asset prices decline in all episodes, but the decline in financial crises is substantially larger than the decline in fundamentals so that expected returns going forward are large. However, drops in consumption and consumption volatility are fairly similar across financial crises and recessions and are largest during wars, so asset pricing models based on aggregate consumption have trouble matching these facts. Comparing crises to “deep” recessions strengthens these findings further. By disentangling financial crises from other bad macroeconomic times, the results suggest that financial crises are particularly important to understanding why risk premia vary. I discuss implications for theory more broadly and discuss both rational and behavioral models that are consistent with the facts. Theories where asset prices are related to the health of the financial sector appear particularly promising.

A long-term investor who ignores variation in volatility gives up the equivalent of 2.4% of wealth per year. This result holds for a wide range of parameters that are consistent with US stock market data, and it is robust to estimation uncertainty. We propose and test a new channel, the volatility composition channel, for how investment horizon interacts with volatility timing. Investors respond substantially less to volatility variation if the amount of mean reversion in returns disproportionally increases with volatility and also if mean reversion happens quickly. We find that these conditions are unlikely to hold in the data.

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.

At the announcement of a new policy, agents form a view of state-contingent policy actions and impact. We develop a method to estimate this state-contingent perception and implement it for many asset-purchase interventions worldwide. Expectations of larger support in bad states—“policy puts”—explain a large fraction of the announcements' impact. For example, when the Fed introduced purchases of corporate bonds in March 2020, markets expected five times more price support had conditions worsened relative to the median scenario. Perceived promises of additional support in bad states alter asset prices, risk, and the response to future announcements.

We study data on commercial banks and securities firms across multiple countries since 1870. Balance sheet expansion of leveraged intermediaries negatively predicts returns of stocks, bonds, currencies, and housing. The predictability is stronger at shorter horizons, is robust to macroeconomic controls, and holds outside distress periods, in contrast to models featuring nonlinearities during distress. Intermediaries in global financial centers predict international equity returns. A new data set on individual stock holdings of Japanese intermediaries since 1955 shows intermediaries affect returns of stocks directly held. Our results suggest a strong universal link between intermediaries and asset returns distinct from macroeconomic channels.

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.