We show that idiosyncratic jumps are a key determinant of mean stock returns from both an ex post and ex ante perspective. Ex post, the entire annual average return of a typical stock accrues on the four days on which its price jumps. Ex ante, idiosyncratic jump risk earns a premium: a value-weighted weekly long-short portfolio that buys (sells) stocks with high (low) predicted jump probabilities earns annualized mean returns of 9.4% and four-factor alphas of 8.1%. This strategy’s returns are larger when there are greater limits to arbitrage. These results are consistent with investor aversion to idiosyncratic jump risk.

We show that a firm’s financial constraints trigger investment disruptions that propagate through the production network. Propagation effects account for about half of the total investment reduction due to constraints. Network rigidities such as high input specificity and the scarcity of alternative partners amplify these spillovers. Firms mitigate investment disruptions by supporting constrained partners through trade credit or equity stakes. To bolster identification, we employ a Network Regression Discontinuity Design that accounts for spillovers. Our estimates are robust to network measurement error, endogenous selection, and various constraint measures. The results demonstrate that interdependent investments amplify the consequences of capital-market frictions.

Stocks that hedge sustained market downturns should have low expected returns, but they do not. We use ex ante firm characteristics and covariances to construct a tradable safe minus risky (SMR) portfolio that hedges market downturns out of sample. Although downturns (peaks to troughs in market index levels at the business-cycle frequency) predict significant declines in gross domestic product growth, SMR has significant positive average returns and 4-factor alphas (both around 0.8% per month). Risk-based models do not explain SMR’s returns, but mispricing does. Risky stocks are overpriced when sentiment is high, resulting in subsequent returns of -0.9% per month.

We use a matching method that constructs synthetic counterfactual states to identify the channels that link bank deregulation to financial integration, and thereby to economic growth. We document a positive, but conditional, effect of financial integration on economic growth. We explore the heterogeneous effects of financial integration across states depending on the capital mobility in each state. Our results reveal a correlation between financial integration and subsequent banking sector changes related to an expansion in loan recipients. We show that financial integration democratizes lending and spurs economic growth.

We present a spatial econometrics framework for estimating peer effects in capital structure. This approach exploits the heterogeneous and intransitive nature of peer networks to identify economically informative structural coefficients. In models of leverage levels, we detect significant peer-effect leverage coefficients that are on the order of 0.20, indicating a moderate but substantive level of strategic complementarity in capital structure decisions. We argue that prior estimates in the literature substantially overstate the magnitude of the underlying relation. Our evidence is robust to a wide variety of model modifications and supports the hypothesis that leverage is an important strategic choice variable.