This dissertation joins the vibrant debate in the empirical finance literature about the cross-sectional stock return anomalies. The endless effort by the finance community to find profitable stock-picking rules has raised questions of data-snooping bias in the empirical findings. The two main chapters of this dissertation investigate the cross-section of stock returns with multiple testing method to eliminate the data-snooping bias concern. The first one examines the efficiency of multi-factor investment strategies prevalent in the equity ETF market. The second one explores the relevance of group information in testing the stock market anomalies.