Essays on Liquidity Risk and Asset Pricing
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This dissertation consists of two essays on liquidity risk and asset pricing. In the first essay, I diagnose the impact of error-in-variables (EIV) on inferences in asset pricing models. I test the CAPM and the liquidity-adjusted CAPM in a manner that explicitly accounts for EIV, without pooling stocks into portfolios. I find that the single-factor CAPM beta is not priced. I document that the aggregate liquidity risk in the liquidity-adjusted CAPM of Acharya and Pedersen (2005) is priced, and the portfolio-based approach is unable to capture this relationship. The cumulant-based approach used in my paper to handle EIV enables me to test the effects of the individual components of aggregate liquidity risk, and I find that the risk associated with the commonality in illiquidity has a positive premium and the risk associated with the sensitivity of a stock's illiquidity to the value-weighted market return has a negative premium. I also show that for microcap stocks, the risk attributable to the covariance between stock return and market-wide liquidity has a negative relationship with average returns. I find that the LCAPM cannot be rejected when the betas are estimated at the stock-level, and the intercept of the model is insignificant. In the second essay, I explore the relation between idiosyncratic volatility and the cross-section of expected returns. I use an EGARCH model to estimate the forecasted idiosyncratic volatility (FIVOL) and find that this estimate is not affected by the microstructure biases embodied by bid-ask spreads and the percentage of zero returns. I document a positive relation between FIVOL and expected returns. However, contrary to the models in the existing literature (such as Merton (1987)), I find that the cross-sectional differences in levels of idiosyncratic volatility are not priced. The positive relation is mainly driven by stocks that rise in their FIVOL quintile ranking. These transitions in FIVOL ranking are a consequence of return shocks that result in the sudden changes in FIVOL. I explore earnings surprises as a potential explanation for these return shocks and find that standardized unexpected earnings cannot completely explain the pricing ability of these transitions in FIVOL. Even after controlling for earnings surprises, I find that the stocks that move from a low FIVOL quintile to a higher quintile earn high returns.