The relation between trading volume and price movements has long been the subject of academic study, resulting in a voluminous literature. Early studies focus on the contemporaneous relation between trading volume and price changes and find that trading volume is positively related with the absolute value of price changes (e.g., Karpoff, 1986; Gallant, Rossi, and Tauchen, 1992; Blume, Easley, and O’Hara, 1994). More recent studies focus on whether there exists a relation between trading volume and expected returns. The seminal work of Gervais, Kaniel, and Mingelgrin (2001) documents that stocks with an unusually high trading volume over a day or a week (compared with their own trading volumes in the prior 50 days or 10 weeks) have higher subsequent returns than stocks with an unusually low trading volume. This finding results in a high volume return premium implying that abnormal trading volume contains information about future price movements. Gervais et al. (2001) interpret the high volume return premium following the investor recognition hypothesis originated by Miller (1977). Abnormal trading volume can be driven by factors such as hedging, overconfidence, differences of opinion, liquidity, and the portfolio rebalancing needs of investors. However, Chuang and Lee (2006) and Hong and Stein (2007) argue that hedging, liquidity, and portfolio rebalancing needs are too small to account for the large trading activity observed in the markets. Thus, abnormal trading volume is more likely attributable to the result of differences of opinion or overconfidence (Glaser and Weber, 2007; 2009). However, each explanation results in a different relation between volume shocks and subsequent stock returns. According to Gervais et al. (2001), a high volume shock induced by a high level of differences of opinion causes a stock to have higher subsequent returns after increased visibility.1 The high volume shock therefore acts as an attention-grabbing event that draws investors’ attention to the stock (Miller, 1977).