The relation between trading volume and stock returns has been an active area of research for many decades. The popularization of high-speed (high-frequency) trading, a conspicuous aspect of financial markets in the past two decades, has attracted increasing attention to the relation from both academicians and practitioners. Not surprisingly, it also figures prominently in the debate about the revived proposals to impose Tobin-type securities transaction taxes to reduce trading volume following the recent financial crisis. Better understanding of the volume-return relation clearly can also shed light on the ongoing debate about whether modern finance is too big (Cochrane, 2013; Greenwood and Scharfstein, 2013). The questions at issue are whether there is any relation between trading volume and stock returns and, if the answer is yes, whether such a relation is economically significant. The latter is probably more important in the current debate. Market microstructure theory suggests that both trading volume and price changes (returns) are related to the arrival of information to the market. Thus volume and price movement may jointly depend on the intensity of information flow. Much of the early theoretical work on the volume-return relation therefore focuses primarily on the contemporaneous relation between volume and price changes (Karpoff, 1987; Gallant, Rossi, and Tauchen, 1992). However, considering the long-standing controversy about the simultaneous determination of price and quantity in economics, it is not surprising that such contemporaneous causality between volume and stock returns has proven difficult to sort out empirically given the observational nature of data. Extending the early work but paying more attention to its dynamic nature, later research generally finds positive evidence on the volume-return relation under different assumptions. First, trading volume is a measure of liquidity, which is significantly related to future stock returns (Amihud and Mendelson, 1986; Datar, Naik, and Radcliffe, 1998; Lesmond, Ogden, and Trzcinka, 1999; Amihud, 2002; Lesmond, 2005; Liu, 2006). Second, trading volume indicates how investors trade on individual stocks to share risk or speculate on private information, which further induces different subsequent reversal or continuation patterns (Llorente, Michaely, Saar, and Wang, 2002). Third, trading volume describes investors’ learning curve that leads to overconfidence and further affects future stocks returns (Gervais and Odean, 2001; Statman, Thorley, and Vorkink, 2006). Finally, trading volume is related to investor attention and reflects how investors react to the news of the firm (Hou, Peng, and Xiong, 2009). While many of these studies examine the cross sectional volume-return relation in individual stocks, there is another line of research explicitly investigating the dynamic relation between volume and stock returns via testing Granger (non-) causality since Hiemstra and Jones (1994). The intent is to determine whether including past volume information can help predict stock returns after controlling for past returns and other relevant information. Other important contributions in this sub-field include Easley, O’Hara, and Srinivas (1998), Chordia and Swaminathan (2000), Lee and Rui (2002), Malcolm and Stein (2004), Chuang, Kuang, and Lin (2009), and Chen (2012).