Existing theories advocate the exclusive use of equity-like instruments in executive compensation. However, recent empirical studies document the prevalence of debt-like instruments such as pensions. This paper justifies the use of debt as efficient compensation. Inside debt is a superior solution to the agency costs of debt than the solvency-contingent bonuses and salaries proposed by prior literature, since its payoff depends not only on the incidence of bankruptcy but also firm value in bankruptcy. Contrary to intuition, granting the manager equal proportions of debt and equity is typically inefficient. In most cases, an equity bias is desired to induce effort. However, if effort is productive in increasing liquidation value, or if bankruptcy is likely, a debt bias can improve effort as well as alleviate the agency costs of debt. The model generates a number of empirical predictions consistent with recent evidence.

We model an investment bank's choice of resource allocation by the probability of acquirers' mergers and acquisitions frequency in the future to theoretically link the role of investment banks to the acquirer returns. Our model predicts the heterogeneity in the quality of advisory services provided by the same investment bank that leads to the heterogeneity in acquirer returns. Such heterogeneity declines as the likelihood of an industry merger wave rises. Controlling for investment bank fixed effects, acquirer fixed effects and potential self-selection bias, we find empirical evidence supporting our hypotheses.

The structural approach offers an integrated framework to deal with yield spreads and default probability simultaneously. However, structural models perform poorly in predicting corporate bond spreads. It is unclear whether this poor performance is caused by characteristics of individual models, missing factors, or different calibration procedures. This study evaluates the performance of four structural models by incorporating two important factors, personal taxes and the liquidity factor, and calibrating these models to data. To ensure our results are not contingent on the calibration method, we further apply the maximum likelihood estimation method to a large sample of individual bonds. Results consistently show that the ability of structural models to predict spreads improves considerably when personal taxes and liquidity are taken into account. Our findings suggest that the poor performance of standard structural models is more likely due to missing factors than the characteristics of individual models or the calibration procedure.

We study the effect of financial market frictions on managerial compensation. We embed a market microstructure model into an otherwise standard contracting framework, and analyze optimal pay-for-performance when managers use information they learn from the market in their investment decisions. In a less frictional market, the improved information content of stock prices helps guide managerial decisions and thereby necessitates lower-powered compensation. Exploiting a randomized experiment, we document evidence that pay-for-performance is lowered in response to reduced market frictions. Firm investment also becomes more sensitive to stock prices during the experiment, consistent with increased managerial learning from the market. (JEL D83, G12, G14, G32, G34, M12, M52)

We analyze a model in which an anomaly is unknown to arbitrageurs until its discovery, and test the model implications on both asset prices and arbitrageurs’ trading activities. Using data on 99 anomalies documented in the existing literature, we find that the discovery of an anomaly reduces the correlation between the returns of its decile-1 and decile-10 portfolios. This discovery effect is stronger if the aggregate wealth of hedge funds is more volatile. Finally, hedge funds increase (reverse) their positions in exploiting anomalies when their aggregate wealth increases (decreases), further suggesting that these discovery effects operate through arbitrage trading.