Trade Size and the Cross Section of Stock Returns: Informed versus Noise Traders in the Chinese Growth Enterprise Market

I. INTRODUCTION The trade characteristics of informed versus noise traders are of great research interest. DeLong, et al. (1990) theorize that noise traders could earn higher expected return than risk averse informed traders by creating more noise risks than arbitrageurs are willing to bet against. Odean (1999), Barber and Odean (2000), and Hvidkjaer (2008) find that stocks bought by individual noise traders tend to significantly underperform those stocks they sold. Researchers have also presented opposing evidence of trade size impact on stock returns. On one hand, trade size is significant in addition to number of trades and trade imbalance so that trade size and information set are positively correlated (Kim and Verrecchia, 1991; Chan and Fong, 2000), adverse selection (when small traders piggyback on large informed trades) is therefore a problem. Large trades impose greater price impacts than smaller trades do (Dufour and Engle, 2000; Easley and O'Hara, 1987; Easley et al., 1997; Holthausen et al., 1987, 1990; Lin et al., 1995). On the other hand, Jones et al. (1994) find that the number of trades is significant, but not the size of trade. In addition, informed investors may camouflage or cloak their trades in package by splitting orders to reduce the adverse selection, thus medium-sized (or even small) trades have bigger price impact than large trades. (Alexander and Peterson, 2007; Chakravarty, 2001; Chan and Lakonishok, 1995; Hasbrouck, 1995; Keim and Madhavan, 1995; Barclay and Warner, 1993; Kyle, 1985). (1) Chan and Lakonishok (1995) also find that the order-splitting behavior often takes four or more days. (2) Chordia and Subrahmanyam (2004) provide theoretical framework that motivates traders to split their orders. Griffin et al. (2003) find that "stocks with the largest institutional sell imbalances experience an extremely low (contemporaneous) excess return of -4.29%, whereas stocks with the largest institutional buying activity experience a 3.69% excess return" (p. 2295). Campbell et al. (2009) also find that institutions tend to be daily momentum traders that demand liquidity with near-term negative returns but contrarian investors for relatively longer term that earn positive returns. Also, the demand for liquidity is higher for sales than for buys. The finding seems to suggest that large traders may not have trading advantage over small traders in the short term. Asthana et al. (2004) show that small traders do trade correctly on and benefit (more than large traders) from annual report filings on EDGAR. However, the direct gains or losses of small versus large trades are not directly tested. Foster et al. (2011) find that "neither the number of funds trading, nor the volume of shares purchased and sold by institutions is correlated with contemporaneous stock returns" (p. 3384) because the dynamics of growth and value managers tend to offset the impact on price changes. Their sample includes only the largest 50 stocks listed on the Australian Securities Exchange. Kaniel et al. (2008) find that contrarian individuals gain positive subsequent excess monthly returns trading against institutions demanding for immediacy. Dorn et al. (2008) and Barber et al. (2009) both find that individual investors herd--they tend to trade the same stocks in the same direction at the same time. The former find that individual investors' net limit buy orders are negatively (positively) correlated with contemporaneous (following) weekly returns. The latter, however, find that stocks mostly purchased (sold) by small investors yield significantly positive (negative) returns in the current and following week; the subsequent weekly pattern is opposite for stocks dominated by large trades. In this paper, we examine the impact of trade size on stock returns on China's recently established Growth Enterprise Market (GEM). The GEM started trading on Oct. 1, 2009 and is China's own NASDAQ-style market to foster the growth of young, entrepreneurial type of high-growth high-risk companies. …