Essays in Empirical Asset Pricing

In my dissertation, I study different channels through which shocks in the real economy can affect financial asset returns. The first chapter studies immigration policy shocks as a source of risk in the financial markets. Using a comprehensive set of data on H-1B visa petitions, I construct an occupation-level measure for labor market competition between skilled immigrant and local workers. I find that stocks of firms with a high share of labor for which skilled immigrants are close substitutes outperform their peers with a low share. I show that this premium is explained by firms' differential exposures to priced immigration policy shocks that shift the supply of skilled immigrant labor. These shocks differentially impact wages across occupations, leading to an asymmetric effect on firms' cash flows through labor expenditure. In the second chapter, based on a joint work with Esther Eiling and Raymond Kan, we investigate the asset pricing implications of sectoral labor reallocation shocks that change the optimal allocation of workers across industries. We find that a proxy for this type of labor market shocks has very strong predictive power for future stock market returns. We propose a production-based asset pricing model that links the return predictability to time-varying labor adjustment costs. When human capital is tied to the industry, hiring workers from other industries involves more search and training costs. Hence, sectoral reallocation shocks lead to lower returns to hiring and therefore lower future stock returns. In the third chapter, we identify inter-sectoral trade networks as important conduits of industry shocks and provide the first explanation for an empirical regularity in the term structure of industry returns. Specifically, my co-author Mikhail Simutin and I show that industry shocks propagating along this network can feed back to the originating industry, causing an "echo'' - intermediate-term autocorrelation in returns. Adopting techniques from graph theory, we find that the strength of the trade network feedback is a crucial determinant of the echo effect in industry returns. Consistent with limited-information models, the relation between feedback strength and echo profits is strongest in industries with information diffusion frictions along the feedback loop.Ph.D