Asset Pricing With Liquidity Risk PDF Download

Abstract: In this dissertation, I investigate the effect of liquidity risk on asset pricing. In the first essay, I test the liquidity-adjusted capital asset pricing model (LCAPM) of Acharya and Pedersen (2005) for 1962-2004 in the US market using various liquidity proxies. In a time-series test with a one-factor (market model), three-factor (excess market return, SMB, and HML) and four-factor model (excess market return, SMB, HML and MOM) as well as in a Fama-MacBeth regression, I find that test results vary according to the liquidity measures used, to the test methodology, to the test assets, and to the weighting scheme. Tests based on the liquidity measure of Amihud (2002), Pastor and Stambaugh (2003) and zero-return proportion show some evidence that liquidity risks are priced, but in most cases, I could not find evidence that supports the LCAPM. The second essay specifies and tests an equilibrium asset pricing model with liquidity risk at the global level. The analysis encompasses 25,000 individual stocks from 48 developed and emerging countries around the world from 1988 to 2004. Though I cannot find evidence that the LCAPM holds in international financial markets, cross-sectional as well as time-series tests show that liquidity risks arising from the covariances of individual stocks' return and liquidity with local and global market factors are priced. Furthermore, I show that the US market is an important driving force of world-market liquidity risk. I interpret our evidence as consistent with an intertemporal capital asset pricing model Merton (1973) in which stochastic shocks to global liquidity serve as a priced state variable. The third essay investigates how and why liquidity is transmitted across stocks. In a vector autoregressive framework, I uncover a dynamic interaction of liquidity across size portfolios in that past changes of liquidity of large stocks are positively correlated with current changes of liquidity of small stocks. Furthermore, liquidity spillovers are not restricted among fundamentally-related stocks and are independent of the dynamics in return and volatility spillovers. This finding implies that the process of liquidity generation is independent of information flows and that portfolio diversification strategies should consider different patterns in return, volatility and liquidity spillovers.