We examine the impact of short selling by conducting a randomized stock lending experiment. Working with a large, anonymous money manager, we create an exogenous and sizeable shock to the supply of lendable shares by taking high loan fee stocks in the manager's portfolio and randomly making available and withholding stocks from the lending market. The experiment ran in two independent phases: the first, from September 5 to 18, 2008, with over $580 million of securities lent, and the second, from June 5 to September 30, 2009, with over $250 million of securities lent. While the supply shocks significantly reduce market lending fees and raise quantities, we find no evidence that returns, volatility, skewness, or bid–ask spreads are affected. The results provide novel evidence on the impact of shorting supply and do not indicate any adverse effects on stock prices from securities lending.

We provide new evidence on the success of long-run risks in asset pricing by focusing on the risks borne by stockholders. Exploiting microlevel household consumption data, we show that long-run stockholder consumption risk better captures cross-sectional variation in average asset returns than aggregate or nonstockholder consumption risk, and implies more plausible risk aversion estimates. We find that risk aversion around 10 can match observed risk premia for the wealthiest stockholders across sets of test assets that include the 25 Fama and French portfolios, the market portfolio, bond portfolios, and the entire cross-section of stocks.

This paper documents a strong and prevalent momentum effect in industry components of stock returns which accounts for much of the individual stock momentum anomaly. Specifically, momentum investment strategies, which buy past winning stocks and sell past losing stocks, are significantly less profitable once we control for industry momentum. By contrast, industry momentum investment strategies, which buy stocks from past winning industries and sell stocks from past losing industries, appear highly profitable, even after controlling for size, book‐to‐market equity, individual stock momentum, the cross‐sectional dispersion in mean returns, and potential microstructure influences.

Stock momentum, long-term reversal, and other past return characteristics that predict future returns also predict future realized betas, suggesting these characteristics capture time-varying risk compensation. We formalize this argument with a conditional factor pricing model. Using instrumented principal components analysis, we estimate latent factors with time-varying factor loadings that depend on observable firm characteristics. We show that factor loadings vary significantly over time, even at short horizons over which the momentum phenomenon operates (one year), and this variation captures reliable conditional risk premia missed by other factor models commonly used in the literature. Our estimates of conditional risk exposure can explain a sizable fraction of momentum and long-term reversal returns and can be used to generate even stronger return predictions.

We find consistent evidence of negative autocorrelation in decision making that is unrelated to the merits of the cases considered in three separate high-stakes field settings: refugee asylum court decisions, loan application reviews, and Major League Baseball umpire pitch calls. The evidence is most consistent with the law of small numbers and the gambler’s fallacy—people underestimating the likelihood of sequential streaks occurring by chance—leading to negatively autocorrelated decisions that result in errors. The negative autocorrelation is stronger among more moderate and less experienced decision makers, following longer streaks of decisions in one direction, when the current and previous cases share similar characteristics or occur close in time, and when decision makers face weaker incentives for accuracy. Other explanations for negatively autocorrelated decisions such as quotas, learning, or preferences to treat all parties fairly are less consistent with the evidence, though we cannot completely rule out sequential contrast effects as an alternative explanation.

We examine the impact of asset liquidation value on debt contracting using a unique set of commercial property non-recourse loan contracts.We employ commercial zoning regulation to capture the flexibility of a property's permitted uses as a measure of an asset's redeployability or value in its next best use.Within a census tract, more redeployable assets receive larger loans with longer maturities and durations, lower interest rates, and fewer creditors, controlling for the current value of the property, its type, and neighborhood.These results are consistent with incomplete contracting and transaction cost theories of liquidation value and financial structure.

We examine the impact of asset liquidation value on debt contracting using a unique set of commercial property loan contracts. We employ commercial zoning regulation to capture the flexibility of a property's permitted uses as a measure of an asset's redeploy ability or value in its next best use. Within a census tract, more redeployable assets receive larger loans with longer maturities and durations, lower interest rates, and fewer creditors, controlling for the property's type, sale price, and earnings-to-price ratio. These results are consistent with incomplete contracting and transaction cost theories of liquidation value and financial structure.

We document significant “time series momentum” in equity index, currency, commodity, and bond futures for each of the 58 liquid instruments we consider. We find persistence in returns for one to 12 months that partially reverses over longer horizons, consistent with sentiment theories of initial under-reaction and delayed over-reaction. A diversified portfolio of time series momentum strategies across all asset classes delivers substantial abnormal returns with little exposure to standard asset pricing factors and performs best during extreme markets. Examining the trading activities of speculators and hedgers, we find that speculators profit from time series momentum at the expense of hedgers.

We provide a model of the effects of catastrophic risk on real estate financing and prices and demonstrate that insurance market imperfections can restrict the supply of credit for catastrophe‐susceptible properties. Using unique micro‐level data, we find that earthquake risk decreased commercial real estate bank loan provision by 22% in California properties in the 1990s, with more severe effects in African–American neighborhoods. We show that the 1994 Northridge earthquake had only a short‐term disruptive effect. Our basic findings are confirmed for hurricane risk, and our model and empirical work have implications for terrorism and political perils.

Using a unique sample of commercial loans and mergers between large banks, we provide micro‐level (within‐county) evidence linking credit conditions to economic development and find a spillover effect on crime. Neighborhoods that experience more bank mergers are subject to higher interest rates, diminished local construction, lower prices, an influx of poorer households, and higher property crime in subsequent years. The elasticity of property crime with respect to merger‐induced banking concentration is 0.18. We show that these results are not likely due to reverse causation, and confirm the central findings using state branching deregulation to instrument for bank competition.