Past Informed Trading and Past Dealer Inventory in US Equity Markets

Several studies document that past returns and past trading volume predict shortterm stock returns. This study considers two new variables: the past number of trades signed as purchase and sale. These variables also predict weekly US stock returns and contain information that is distinct from past returns and past trading volume. Combined trading strategies outperform strategies based on past returns and past trading volume alone. A form of market inefficiency, lagged information dissemination, best explains the predictive power of the past number of signed trades. It cannot be explained by overreaction, biased self-attribution or systematic risk. I also find that the return predictability varies across exchanges and after tick size reductions. Several studies including Hasbrouck (1988, 1991a and 1991b) demonstrate that informed trading activity and dealer inventory costs can explain firm-by-firm spread width. Madhavan and Smidt (1991) and Hasbrouck and Sofianos (1993) show that informed trading activity and dealer inventory can also explain how individual trades impact the stock price. My study explores whether proxies for past informed trading activity and past dealer inventory constructed from order flow can predict future one-week stock returns. In a comprehensive dataset covering the major exchanges from 1993 to 2002, it considers 4 items: past informed trading proxies, past dealer inventory proxies, past returns and past trading volume. I find that past returns, past informed trading and past trading volume make distinct and economically relevant contributions to future returns. Past dealer inventory proxies make little or no contribution. It is a puzzle why variables constructed from observed order flow can predict future returns. The common theoretical perspective is to assume that they do not predict returns. For example, Kyle (1985) and many studies that follow assume that market makers set prices so that expected returns are zero given observed order flow. However, these same studies also conclude that informed traders place trades over time so that information dissemination is lagged. Intuitively, if the zero expected returns assumption is violated, agents could infer the direction of informed trading by observing order flow. Because information disseminates slowly, these inferences imply future informed trading in the same direction. In turn, these inferences can then predict future price changes. This form of market inefficiency can be large because an informed trader’s private information may include the existence of new product markets, knowledge of acquirers, or entry by rivals. My study shows that Kyle’s assumption is often violated and contributes to the literature of short-term return predictability. I find that inferences can be made about the actions of informed traders during the lagged process of price adjustment. In turn, agents can use these inferences to predict future returns. Moreover, these returns are permanent and cannot be explained by overreaction or biased self-attribution. The empirical results of this study, which are based on a comprehensive TAQ database that spans 1993 to 2002, can be summarized as follows: