AIMing at PIN: Order Flow, Information, and Liquidity, Manuscript, 2008. (Co-authored with Gautam Kaul and Noah Stoffman)

In this study, we model and measure the existence of informed trading. Specifically, we investigate the properties of the widely used measure of informed trading, PIN, developed by Easley and O'Hara, and establish three important features of informed trading. First, the existence of informed trading, and therefore PIN, should be estimated over different trading intervals for stocks of different characteristics. Second, we establish a direct relationship between PIN and the absolute (percentage) order imbalance (AIM). The latter is not only easier to measure, but can also be readily calculated over short horizons. Most importantly, we show that conditions for the theoretical equivalence between estimated PIN and AIM of a stock serve as a guide for the optimal estimation interval that should be used for that particular stock. Finally, and significantly, an investigation around exogenous national security events reveals strong evidence against interpreting PIN and order imbalance as a liquidity measure.

Momentum is Not an Anomaly, Manuscript, 2007. (Co-authored with Bob Dittmar and Gautam Kaul)

In this paper, we develop a new approach to test whether momentum is indeed an anomaly in that it reflects delayed reactions, or continued overreactions, to firm specific news. Our methodology does not depend on a specific model of expected returns and, more importantly, does not require a decomposition of momentum profits. Yet we provide distinct testable predictions that can discriminate between the two diametrically opposed causes for the profitability of momentum strategies: time-series continuation in the firm-specific component of returns, and cross-sectional differences in expected returns and systematic risks of individual securities. Our results show that, contrary to the common belief in the profession, momentum is not an anomaly; we find no evidence of continuation in the idiosyncratic component of individual-security returns. The evidence is instead consistent with momentum being driven entirely by cross-sectional differences in expected returns and risks of individual securities.

Cash Distributions and Returns, Manuscript, 2006.

Discounted cash flow analysis suggests that high cash-flow-to-price ratios should predict high future stock return, low future cash flow growth, or both. Existing studies on the predictive power of the dividend-price ratio, however, produce evidence largely inconsistent with this prediction. In this paper, we address this issue by focusing on the total cash distributions that include both dividends and share repurchases net of seasoned equity offerings. Utilizing a long time series of the total-cash-distributions-to-price (tp) ratio constructed from CRSP data since 1927, we establish strong and persistent evidence of stock return predictability at the annual horizon. Based on a wide variety of evaluation methods, the tp ratio is both statistically and economically significant in predicting future stock market returns, and serves as a pervasive state proxy.