This paper investigates how a firm’s capital structure choice affects the informational efficiency of its security prices in the secondary markets. We identify two new determinants of a firm’s capital structure policy: the liquidity (adverse selection) premium due to investors’ anticipated losses to informed trading, and operating efficiency improvement due to information revelation from the firm’s security prices. We show that the capital structure decision affects traders’ incentives to acquire information and subsequently, the distribution of informed traders across debt and equity claims. When information is less imperative for improving its operating decisions, a firm issues zero or negative debt (i.e., holding excess cash reserves) in order to reduce socially wasteful information acquisition and the liquidity premium associated with it. When information is crucial for a firm’s operating decisions, the optimal debt level is one that achieves maximum information revelation at the lowest possible liquidity cost. Our model can explain why many firms consistently hold no debt. It also provides new implications for financial system design and for the relationship among leverage, liquidity premium, profitability, and the cost of information acquisition.

We study pre‐trade transparency by looking at the introduction of NYSE's OpenBook service that provides limit‐order book information to traders off the exchange floor. We find that traders attempt to manage limit‐order exposure: They submit smaller orders and cancel orders faster. Specialists' participation rate and the depth they add to the quote decline. Liquidity increases in that the price impact of orders declines, and we find some improvement in the informational efficiency of prices. These results suggest that an increase in pre‐trade transparency affects investors' trading strategies and can improve certain dimensions of market quality.

Cross-stock momentum builds on the asymmetry in lead-lag linkages and the difference between long-run and short-run contemporaneous co-movements. Data-driven cross-stock linkages generate a monthly alpha of 1.62% ( t -stat=10.03). The asymmetry distinguishes cross-stock momentum from factor momentum, and industry momentum is not subsumed by factor momentum. Factor momentum profit is mostly due to the high cross-stock links. The data-driven linkages vary faster over time than those in previous studies because short-run co-movements incorporate persistent linkages.

We document that leased capital accounts for about 20% of total physical productive assets used by US public firms, and its proportion is more than 40% among small and financially constrained firms. The leased capital ratio exhibits a strong countercyclical pattern over business cycles and a positive correlation with cross-sectional idiosyncratic uncertainty. We argue that existing macro models with financial frictions assume that firms cannot rent capital and overlook the effects of leasing activities on business cycle dynamics. We explicitly introduce a buy-versus-lease decision into the Bernanke–Gertler–Gilchrist financial accelerator model setting to demonstrate a novel and quantitatively important economic mechanism: that the increased use of leased capital when financial constraints become tighter in bad states significantly mitigates the financial accelerator mechanism and thus also mitigates the response of macroeconomic variables to negative total factor productivity shocks and risk shocks. We provide strong empirical evidence to support our mechanism.

A four-factor model with two "mispricing" factors, in addition to market and size factors, accommodates a large set of anomalies better than notable four-and five-factor alternative models. Moreover, our size factor reveals a small-firm premium nearly twice usual estimates. The mispricing factors aggregate information across 11 prominent anomalies by averaging rankings within two clusters exhibiting the greatest return co-movement. Investor sentiment predicts the mispricing factors, especially their short legs, consistent with a mispricing interpretation and the asymmetry in ease of buying versus shorting. A three-factor model with a single mispricing factor also performs well, especially in Bayesian model comparisons.

This paper examines the return spillovers between Exchange-Traded Funds (ETFs) and stocks. While traditional approaches focus on proportional relationships between ETFs and their underlying assets, we develop a high-dimensional network framework that captures spillover effects between any ETF-stock pair, regardless of their compositional relationship. By separating idiosyncratic and systematic risks, we investigate potential drivers of contagion. We document substantial heterogeneity in spillover patterns across sectors, which is previously unaddressed in the literature. Sectors such as Utilities and Real Estate exhibit robust spillovers to both their component stocks and assets in other sectors. Conversely, in sectors such as Consumer Discretionary and Finance , cross-sector influences dominate intra-sector ETF-constituent linkages. Our results also highlight that during periods of high market volatility, sources of idiosyncratic contagion become more diverse, suggesting the need for broader market surveillance beyond the few most influential ETFs.

Recent research suggesting that shareholders demand conservative financial reporting raises the question: Which shareholders demand conservatism? We find that higher ownership by institutions that are likely to monitor managers is associated with more conservative financial reporting. This positive association is more pronounced among firms with more growth options and higher information asymmetry, where direct monitoring is more difficult and the potential governance benefits of conservatism are greater. Further, lead-lag tests of the direction of causality suggest that ownership by monitoring institutions leads to more conservative reporting, rather than the reverse. Collectively, these results are consistent with monitoring institutions demanding conservatism.

A seller and a buyer bargain over the terms of trade for an object. The seller receives a perfect signal that determines the value of the object to both players, whereas the buyer remains uninformed. We analyze the infinite-horizon bargaining game in which the buyer makes all the offers. When the static incentive constraints permit first-best efficiency, then under some regularity conditions the outcome of the sequential bargaining game becomes arbitrarily efficient as bargaining frictions vanish. When the static incentive constraints preclude first-best efficiency, the limiting bargaining outcome is not second-best efficient and may even perform worse than the outcome from the one-period bargaining game. With frequent buyer offers, the outcome is then characterized by recurring bursts of high probability of agreement, followed by long periods of delay in which the probability of agreement is negligible.

We find that bond issues have substantially increased since the onset of the COVID-19 crisis in calendar week 12 (March 16-20) for bonds rated A or higher, but surprisingly also for bonds rated BBB or lower. In contrast to existing evidence on bond maturities in economic downturns, we document that maturities exceed those of bonds issued before by the same firms as well as the average maturities during normal times. Determinants of corporate bond spreads substantially differ between COVID-19 and normal times. Most prominently, asset tangibility has a highly significant negative effect on spreads during normal times. During COVID-19, this is reversed, especially in industries heavily affected by lockdown measures, reflecting the inflexibility associated with fixed assets. A different picture emerges for equity issues, which slowed considerably during the first 4 weeks of the pandemic, before accelerating again. Capital raised during COVID-19 via equity issues is approximately 5% of capital raised via bond issues.

This paper develops a model to estimate the implied default probability of corporate bonds. The model explicitly considers the risk averse behavior of investors to provide a more precise framework for estimating the implied default probability. A Kalman filter method is used to estimate time-varying risk premium associated with the investor's risk aversion. The results of nonlinear regressions indicate that previous risk-neutrality models consistently overestimate the implied default rates of corporate bonds. The results also suggest that investors may have been adequately compensated for investment in risky bonds.