I study how the density of executive labor markets affects managerial incentives and thereby firm performance. I find that U.S. executive markets are locally segmented rather than nationally integrated, and that the density of a local market provides executives with non-compensation incentives. Empirical results show that in denser labor markets, executives face stronger performance-based dismissal threats as well as better outside opportunities. These incentives result in higher firm performance in denser markets, especially when executives have longer career horizons. Using state-level variation in the enforceability of covenants not to compete, I find that the positive effects of market density on incentive alignment and firm performance are stronger in markets where executives are freer to move. This evidence further supports the argument that local labor market density works as an external incentive alignment mechanism.

Abstract Contrary to the prediction of the standard portfolio diversification theory, many investors place a large fraction of their stock investment in a small number of stocks. I show that underdiversification may be caused by solvency requirements. My model predicts that for quite general preferences and return distributions: (1) underdiversification decreases in discretionary wealth; and (2) expected return and covariance determine which stocks to invest in, but variance, higher moments, and Sharpe ratio do not matter for this choice. In addition, a less-diversified stock portfolio has a higher expected return, a higher volatility, and a higher skewness, and idiosyncratic risks are priced.

Nearly one in five hedge funds change their share restrictions (e.g., lockup) from 2007 to 2012. Using a large panel dataset, this paper is the first to empirically examine the incidence, determinants, and consequences of share restriction changes. We find that funds with high asset liquidity and low liquidity risk are more likely to decrease share restrictions and funds with good performance are more likely to increase share restrictions. A hazard model indicates that funds who actively manage liquidity concerns live longer by adjusting share restrictions. We examine whether changes in share restrictions create an endogeneity bias in the share illiquidity premium (Aragon, 2007) and find that 18% of the premium can be explained by the dynamic nature of contract changes.

Chew Soo Hong, A Generalization of the Quasilinear Mean with Applications to the Measurement of Income Inequality and Decision Theory Resolving the Allais Paradox, Econometrica, Vol. 51, No. 4 (Jul., 1983), pp. 1065-1092

We develop a nonparametric specification test for continuous-time models using the transition density. Using a data transform and correcting for the boundary bias of kernel estimators, our test is robust to serial dependence in data and provides excellent finite sample performance. Besides univariate diffusion models, our test is applicable to a wide variety of continuous-time and discrete-time dynamic models, including time-inhomogeneous diffusion, GARCH, stochastic volatility, regime-switching, jump-diffusion, and multivariate diffusion models. A class of separate inference procedures is also proposed to help gauge possible sources of model mis-specification. We strongly reject a variety of univariate diffusion models for daily Eurodollar spot rates and some popular multivariate affine term structure models for monthly U.S. Treasury yields.

We examine the optimal trading strategy for a CRRA investor who maximizes the expected utility of wealth on a finite date and faces transaction costs. Closed-form solutions are obtained when this date is uncertain. We then show a sequence of analytical solutions converge to the solution to the problem with a deterministic finite horizon. Consistent with the common life-cycle investment advice, the optimal trading strategy is found to be horizon dependent and largely buy and hold. Moreover, it might be optimal for the investor in our model not to buy any stock, even when the risk premium is positive. Further analysis of the optimal policy is also provided.