wish to thank Andre Haris, Lozan Bakayatov, and Davron Yakubov for their excellent data collection efforts. In addition, we thank the financial assistance of the Social Sciences and Humanities Research Council of Canada. All errors remain the responsibility of the authors. Corporate Yield Spreads and Bond Liquidity We examine whether liquidity is priced in corporate yield spreads. Using a battery of liquidity measures covering over 4000 corporate bonds and spanning investment grade and speculative categories, we find that more illiquid bonds earn higher yield spreads; and that an improvement of liquidity causes a significant reduction in yield spreads. These results hold after controlling for common bond-specific, firm-specific, and macroeconomic variables, and are robust to issuers ’ fixed effect and potential endogeneity bias. Our finding mitigates the concern in the default risk literature that neither the level nor the dynamic of yield spreads can be fully explained by default risk determinants, and suggests that liquidity plays an important role in corporate bond valuation.

Given the cross-sectional and temporal variation in their liquidity, emerging equity markets provide an ideal setting to examine the impact of liquidity on expected returns. Our main liquidity measure is a transformation of the proportion of zero daily firm returns, averaged over the month. We find that it significantly predicts future returns, whereas alternative measures such as turnover do not. Consistent with liquidity being a priced factor, unexpected liquidity shocks are positively correlated with contemporaneous return shocks and negatively correlated with shocks to the dividend yield. We consider a simple asset pricing model with liquidity and the market portfolio as risk factors and transaction costs that are proportional to liquidity. The model differentiates between integrated and segmented countries and time periods. Our results suggest that local market liquidity is an important driver of expected returns in emerging markets, and that the liberalization process has not fully eliminated its impact.

This paper derives in closed form the optimal dynamic portfolio policy when trading is costly and security returns are predictable by signals with different mean reversion speeds. The optimal updated portfolio is a linear combination of the existing portfolio, the optimal current portfolio absent trading costs, and the optimal portfolio based on future expected returns. Predictors with slower mean reversion (alpha decay) get more weight since they lead to a favorable positioning both now and in the future. We implement the optimal policy for commodity futures and show that the resulting portfolio has superior returns net of trading costs relative to more naive benchmarks. Finally, we derive natural equilibrium implications, including that demand shocks with faster mean reversion command a higher return premium.

This paper presents an equilibrium model for the demand and supply of liquidity and its impact on asset prices and welfare. We show that when constant market presence is costly, purely idiosyncratic shocks lead to endogenous demand of liquidity and large price deviations from fundamentals. Moreover, market forces fail to lead to efficient supply of liquidity, which calls for potential policy interventions. However, we demonstrate that different policy tools can yield different efficiency consequences. For example, lowering the cost of supplying liquidity on the spot (e.g., through direct injection of liquidity or relaxation of ex post margin constraints) can decrease welfare while forcing more liquidity supply (e.g., through coordination of market participants) can improve welfare.

We use a novel framework that integrates standard asset pricing and microstructure models to study how asymmetric information, imperfect competition among market makers, and risk aversion affect equilibrium illiquidity and asset pricing. All the main results are obtained in closed-form. In our model, market power, asymmetric information, and market-making cost drive market illiquidity. This model can potentially explain some of the puzzling empirical findings such as (1) the bid-ask spread can be lower with asymmetric information; (2) the bid-ask spread can be positively correlated with trading volume; (3) stock volatility tends to decrease trading volume; (4) the bid-ask spread is positively correlated with market makers ’ inventory; (5) trading volume may increase with information asymmetry. In addition, we find that information asymmetry may reduce the welfare loss due to market power. Furthermore, the equilibrium number of market makers decreases with the market-making cost and increases with trading volume, and may increase with information asymmetry.

We examine the liquidity premium in a dynamic model with price impact. The liquidity premium is defined as the additional return necessary to compensate the investor for the adverse price impact of trading. Our study reveals that with price impact the optimal stock investment increases with the investment horizon and decreases with the investor’s initial wealth. The liquidity premium is increasing and concave in price impact. It also increases with the investor’s initial wealth and decreases with the investment horizon and the investor’s risk aversion. Allowing for stochastic liquidity, our analysis offers an intuitive theoretical explanation for the “puzzling ” empirical finding that the liquidity premium decreases with the volatility of liquidity. Further, we find that uncertainty about the investment horizon substantially increases the liquidity premium.