I build a dynamic capital structure model that demonstrates how business cycle variation in expected growth rates, economic uncertainty, and risk premia influences firms' financing policies. Countercyclical fluctuations in risk prices, default probabilities, and default losses arise endogenously through firms' responses to macroeconomic conditions. These comovements generate large credit risk premia for investment grade firms, which helps address the credit spread puzzle and the under‐leverage puzzle in a unified framework. The model generates interesting dynamics for financing and defaults, including market timing in debt issuance and credit contagion. It also provides a novel procedure to estimate state‐dependent default losses.

We propose a measure of the valuation gap between debt and equity—debt‐equity spread (DES)—based on the difference between actual and equity‐implied credit spreads. DES predicts cross‐sectional stock and bond returns in opposite directions. This predictability is unique compared to existing mispricing measures and cannot be explained by exposures to various risk factors. High‐DES firms are more likely to issue equity and retire debt, and have more insider equity selling. These findings are consistent with DES capturing relative mispricing between debt and equity, and provide empirical support for the model of partially segmented markets in Greenwood, Hanson, and Liao (2018, Review of Financial Studies 31, 3307–3343).

We study the dynamic profit‐maximizing selling mechanism in a merger and acquisitions (M&A) environment with costly bidder entry and without entry fees. Depending on the parameters, the optimal mechanism is implemented by a standard auction or by a two‐stage procedure with exclusive offers to one bidder followed by an auction potentially favoring that bidder. The optimal mechanism may involve common deal protections like termination fees, asset lockups, or stock option lockups. Our proposed procedures resemble sales of targets filing Chapter 11 bankruptcy or M&A involving public targets, and they shed light on how to use deal protections in practice.

We provide causal evidence on the value of asset pledgeability by exploiting a unique feature of Chinese corporate bond markets: bonds with identical fundamentals are traded on two segmented markets with different rules for repo transactions. Using a policy shock that rendered AA+ and AA bonds ineligible for repo on one market only, we compare how bond prices changed across markets and rating classes around this event. When the haircut increases from 0% to 100%, bond yields increase by 39 bps to 85 bps. These estimates help us infer the magnitude of the shadow cost of capital in China.

We study the price effects of changes to the S&P 500 index and document an asymmetric price response: There is a permanent increase in the price of added firms but no permanent decline for deleted firms. These results are at odds with extant explanations of the effects of index changes that imply a symmetric price response to additions and deletions. A possible explanation for asymmetric price effects arises from the changes in investor awareness. Results from our empirical tests support the thesis that changes in investor awareness contribute to the asymmetric price effects of S&P 500 index additions and deletions.

This paper examines venture capital's (VC) role in the geographic clustering of high‐growth startups. We exploit a rule change that disproportionately impacted U.S. regions that historically lacked VC financing via a restriction of banks to invest in the asset class. A one‐standard‐deviation increase in VCs' exposure to the rule led to a 20% decline in fund size and a 10% decrease in the likelihood of raising a follow‐on fund. Startups were not wholly cushioned: financing and valuations declined. Startups also moved out of impacted states after the rule change, likely exacerbating existing geographic disparity in entrepreneurship.

Mortgage refinancing activity associated with extraction of home equity contains a strongly countercyclical component consistent with household demand for liquidity. We estimate a structural model of liquidity management featuring countercyclical idiosyncratic labor income uncertainty, long‐ and short‐term mortgages, and realistic borrowing constraints. We empirically evaluate its predictions for households' choices of leverage, liquid assets, and mortgage refinancing using microlevel data. Taking the observed historical paths of house prices, aggregate income, and interest rates as given, the model accounts for many salient features in the evolution of balance sheets and consumption in the cross‐section of households over 2001 to 2012.

Substantial progress has been made in developing more realistic option pricing models. Empirically, however, it is not known whether and by how much each generalization improves option pricing and hedging. We fill this gap by first deriving an option model that allows volatility, interest rates and jumps to be stochastic. Using S&P 500 options, we examine several alternative models from three perspectives: (1) internal consistency of implied parameters/volatility with relevant time‐series data, (2) out‐of‐sample pricing, and (3) hedging. Overall, incorporating stochastic volatility and jumps is important for pricing and internal consistency. But for hedging, modeling stochastic volatility alone yields the best performance.

We formalize the concept of “dark matter” in asset pricing models by quantifying the additional informativeness of cross‐equation restrictions about fundamental dynamics. The dark‐matter measure captures the degree of fragility for models that are potentially misspecified and unstable: a large dark‐matter measure indicates that the model lacks internal refutability (weak power of optimal specification tests) and external validity (high overfitting tendency and poor out‐of‐sample fit). The measure can be computed at low cost even for complex dynamic structural models. To illustrate its applications, we provide quantitative examples applying the measure to (time‐varying) rare‐disaster risk and long‐run risk models.

We find that liquidity is priced in corporate yield spreads. Using a battery of liquidity measures covering over 4,000 corporate bonds and spanning both investment grade and speculative categories, we find that more illiquid bonds earn higher yield spreads, and an improvement in liquidity causes a significant reduction in yield spreads. These results hold after controlling for common bond‐specific, firm‐specific, and macroeconomic variables, and are robust to issuers' fixed effect and potential endogeneity bias. Our findings justify the concern in the default risk literature that neither the level nor the dynamic of yield spreads can be fully explained by default risk determinants.