Knowledge that Transforms

We show that installing stronger risk management into financial institutions—a proposal widely discussed following the 2008 financial crisis—is insufficient to constrain institutions’ exposure to investment with lurking risk, such as asset-backed securities (ABS). Regulations affect the functioning of risk management: risk management constrains institutions’ exposure to risky ABS when they face mark-to-market reporting combined with capital requirements; however, this role is considerably weaker when capital requirements are combined with historical cost accounting. We find suggestive evidence that financial regulations affect risk management functions through promoting risk managers’ efforts in uncovering ABS risk and curbing executives’ incentives to take excessive risk. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

We present resiliency as a measure of liquidity and assess its relationship to expected returns. We establish a covariance-based measure, RES, that captures opening period resiliency, and use it to find a significant nonresiliency premium that ranges from 33 to 57 basis points per month. The premium persists after accounting for an extensive list of other liquidity-related measures and control variables. The results are significant for both value-weighted and equal-weighted returns, when micro-cap stocks are excluded, and for a sample of large cap stocks. The premium is particularly pronounced when trading volume is high. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

We use the cross-section regression approach of Fama and MacBeth (1973) to construct cross-section factors corresponding to the time-series factors of Fama and French (2015). Time-series models that use only cross-section factors provide better descriptions of average returns than time-series models that use time-series factors. This is true when we impose constant factor loadings and when we use time-varying loadings that are natural for time-series factors and time-varying loadings that are natural for cross-section factors. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Recent reforms have given regulators broad powers to “bail-in” bank creditors during financial crises. We analyze efficient bail-ins and their implementation. To preserve liquidity, regulators must avoid signaling negative private information to creditors. Therefore, optimal bail-ins in bad times only depend on public information. As a result, the optimal policy cannot be implemented if regulators have wide discretion, due to an informational time-inconsistency problem. Rules mandating tough bail-ins after bad public signals, or contingent convertible (co-co) bonds, improve welfare. We further show that bail-in and bailout policies are complementary: if bailouts are possible, then discretionary bail-ins are more effective.

Over-the-counter (OTC) markets attract substantial trading volume despite exhibiting frictions absent in centralized limit-order markets. We compare the efficiency of OTC and limit-order markets when traders’ expertise is endogenous. We show that asymmetric access to counterparties in OTC markets yields increased rents from expertise acquisition for a few well-connected core traders. When the existence of gains to trade is uncertain, traders’ higher expertise in OTC markets can improve allocative efficiency. In contrast, when expertise primarily causes adverse selection, competitive limit-order markets tend to dominate. Our model provides guidance for policy makers and empiricists evaluating the efficiency of market structures.

We analyze the impact ofa unanticipated monetary policy changes on the cross-section of U.S. equity returns. Financially constrained firms earn a significantly lower (higher) return following surprise interest rate increases (decreases) as compared to unconstrained firms. This differential return response between constrained and unconstrained firms appears after a delay of 3 to 4 days. Further, unanticipated Federal funds rate increases are associated with a larger decrease in expected cash flow news, but not discount rate news, for constrained firms relative to unconstrained firms. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

We study when and why firms exercise real options. Using detailed project-level investment data, we find that the likelihood that a firm exercises a real option is strongly related to peer exercise behavior. Peer exercise decisions are as important in explaining exercise behavior as variables commonly associated with standard real option theories, such as volatility. We identify peer effects using localized exogenous variation in peer project exercise decisions and find evidence consistent with information externalities being important for exercise behavior. (JEL G30, G31, G32)

We perform a comparative analysis of machine learning methods for the canonical problem of empirical asset pricing: measuring asset risk premiums. We demonstrate large economic gains to investors using machine learning forecasts, in some cases doubling the performance of leading regression-based strategies from the literature. We identify the best-performing methods (trees and neural networks) and trace their predictive gains to allowing nonlinear predictor interactions missed by other methods. All methods agree on the same set of dominant predictive signals, a set that includes variations on momentum, liquidity, and volatility. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

We establish a link between firms managing investors’ performance expectations, earnings announcement premiums, and cyclical patterns (i.e., seasonalities) in returns. Firms that are more likely to manage expectations toward beatable levels predictably earn lower returns before, and higher returns during, their earnings announcements. This pattern repeats across firms’ fiscal quarters, suggesting firms manufacture positive “surprises” by negatively biasing investors’ expectations ahead of announcing earnings. We corroborate these findings using non-price-based outcomes indicative of expectations management. Together, our findings are consistent with the pressure for firms to meet earnings targets shaping the cross-section of firms’ stock returns.

We propose a theoretically motivated factor model based on investor psychology and assess its ability to explain the cross-section of U.S. equity returns. Our factor model augments the market factor with two factors that capture long- and short-horizon mispricing. The long-horizon factor exploits the information in managers’ decisions to issue or repurchase equity in response to persistent mispricing. The short-horizon earnings surprise factor, which is motivated by investor inattention and evidence of short-horizon underreaction, captures short-horizon anomalies. This 3-factor risk-and-behavioral model outperforms other proposed models in explaining a broad range of return anomalies. (JEL G12, G14) Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.