Liquidity And Expected Stock Returns

Abstract

Liquidity is among the primary attributes of many investment plans and financial instruments. In the Financial Services industry, portfolio managers tailor portfolios to fit their clients’ investment horizons and liquidity objectives and consider illiquidity costs in managing their portfolios. The impact of illiquidity on expected stock returns has been the centre of many studies over the past decade. This thesis employs a low-frequency proxy for the effective spreads, recently developed by Holden (2009) and examines three research problems in liquidity-equity pricing. In research problem 1, I re-examine the liquidity effect on expected stock returns in the NYSE over the period 1926–2008, the pre-1963 period, for which there is a lack of research, and the post-1963 period. The results from the entire sample of 1926–2008 show that expected returns increase with the stock level illiquidity. However, illiquidity level has explanatory power in the cross-sectional variation of expected stock returns only over the post-1963 period, and is, both economically and statistically, insignificant for the whole sample and the pre-1963 period. These findings are robust after taking into account various characteristics and risk controls. On the other hand, evidence from the pre-1963 sample suggests that the systematic market liquidity risk is significant in association with cross-sectional expected stock returns. Nevertheless, the most accurate evidence is provided over the entire sample. The analysis over the whole period of 1926–2008 shows that the systematic liquidity risk plays a significant role in the cross-sectional variation of expected stock returns. In research problem 2, I investigate whether the effect of liquidity on equity returns can be attributed to the liquidity level, as a stock characteristic, or a market-wide systematic liquidity risk. I develop a CAPM liquidity-augmented risk model and test the characteristic hypothesis against the systematic risk hypothesis for the liquidity effect. I find that the two-factor systematic risk model explains the liquidity premium. The hypothesis that the liquidity characteristic is compensated irrespective of liquidity risk loadings is not supported in the data. This result is robust over 1930–2008 data and subsamples of pre-1963 and post-1963 data both in the time-series and the cross-sectional analysis. The results demonstrate that the liquidity augmented CAPM approach is the correct way to incorporate the liquidity risk. In research problem 3, I explore liquidity costs as the explanation for the idiosyncratic volatility premium documented in the literature. Liquidity costs may affect the estimation of idiosyncratic volatility through the microstructure-induced noise in closing equity returns. I eliminate the microstructure influences from the returns and re-estimate the idiosyncratic volatility. I show that liquidity can explain the pricing ability of idiosyncratic volatility reported in the literature for value-weighted portfolios after controlling for the three Fama–French factors and also the Carhart momentum factor. The findings are robust in both the regression and double sorting portfolio analyses. The results from the equally-weighted portfolios indicate that idiosyncratic volatility cannot predict returns ahead either before or after correcting for the microstructure-induced bias. This research provides new empirical evidence which can assist academics, portfolio managers and practitioners to develop a broader understanding of the impact of liquidity costs on stock returns, and to incorporate liquidity in their pricing models.