In these essays, I identify the effects of earnings seasons (i.e., the clustering of earnings releases), on stock market liquidity and asset pricing. In the first essay, I document strong seasonal regularities associated with aggregate earnings announcements. Applying the large body of literature linking earnings announcements to liquidity effects, I argue that these earnings seasons create market-wide liquidity shocks and I show that both liquidity betas and liquidity risk change during earnings seasons In the second essay, I test the impact of earnings seasons on commonality in liquidity as measured by both spreads and depths. I find that commonality significantly decreases during the four weeks of each calendar quarter when most companies release their earnings. These findings contribute to the literature by identifying and examining the clustering effect of firm-specific information on commonality in liquidity. In the third essay, I extend the study of the liquidity effects of earnings seasons to a sample of 20 countries. I find that the international data corroborate both hypotheses. I also find that the aggregate quality of accounting information, and the duration and frequency of interim reporting periods are important determinants of the liquidity effects (both liquidity betas and commonality in liquidity) during earnings seasons.

The Efficient Market Hypothesis believes that it is impossible for an investor to outperform the market because all available information is already built into stock prices. However, some anomalies could persist in stock markets while some other anomalies could appear, disappear and re-appear again without any warning. A Special Issue on "Efficiency and Anomalies in Stock Markets" will be devoted to advancements in the theoretical development of market efficiency and anomaly in the Stock Market, as well as applications in Stock Market efficiency and anomalies.

Liquidity and Asset Prices reviews the literature that studies the relationship between liquidity and asset prices. The authors review the theoretical literature that predicts how liquidity affects a security's required return and discuss the empirical connection between the two. Liquidity and Asset Prices surveys the theory of liquidity-based asset pricing followed by the empirical evidence. The theory section proceeds from basic models with exogenous holding periods to those that incorporate additional elements of risk and endogenous holding periods. The empirical section reviews the evidence on the liquidity premium for stocks, bonds, and other financial assets.

We provide a synthesis of the empirical evidence on market liquidity. The liquidity measurement literature has established standard measures of liquidity that apply to broad categories of market microstructure data. Specialized measures of liquidity have been developed to deal with data limitations in specific markets, to provide proxies from daily data, and to assess institutional trading programs. The general liquidity literature has established local cross-sectional patterns, global cross-sectional patterns, and time-series patterns.

Quantitative equity management techniques are helping investors achieve more risk efficient and appropriate investment outcomes. Factor investing, vetted by decades of prior and current research, is growing quickly, particularly in in the form of smart-beta and ETF strategies. Dynamic factor-timing approaches, incorporating macroeconomic and investment conditions, are in the early stages but will likely thrive. A new generation of big data approaches are rendering quantitative equity analysis even more powerful and encompassing.