Date Available


Year of Publication


Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation


Business and Economics


Finance and Quantitative Methods

First Advisor

Dr. Christopher Clifford


In the first essay, I create a hedge fund informed trading measure (ITM) that separates information related trades from liquidity driven trades. The results indicate that ITM predicts future stock returns at the trade level, thus is associated with information. By aggregating the most informed trades at the stock level, I find that stocks heavily purchased by informed hedge funds earn a significant alpha. The results indicate that the ITM performs better than some previously documented measures and is robust to two different versions of the measure. The second essay exploits the expiring nature of hedge fund lockups to create a new, within-fund proxy of funding liquidity risk. When funds have lower funding liquidity risk, risk-adjusted performance improves and exposure to tail risk increases. We use fund fixed-effect, a placebo approach, and a regression discontinuity design to establish a link between funding liquidity risk and the ability of funds to capitalize on risky mispricing. The third essay explores hedge fund managers ability to identify and trade on stock mispricing opportunity. We refer to the amount of capital that are is locked up and refrained from redemption as the stable capital, and study how it affects stock mispricing. We find that when funds have more lockup capital, they are more likely to take mispricing risks. Taking all funds together, more stable capital in the industry is driving the reduction or even correction of market-wide stock mispricing. Underpriced stocks benefit more than overpriced stock from hedge funds stable capital.

Digital Object Identifier (DOI)